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A Convolutional Neural Network for 6D Object Pose Estimation in Cluttered Scenes

Home Page: https://rse-lab.cs.washington.edu/projects/posecnn/

License: MIT License

Shell 4.82% Makefile 0.01% Python 37.18% C++ 47.96% CMake 1.13% C 0.05% GLSL 0.45% Cuda 8.33% MATLAB 0.08%

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callmeray ml-lab zengzhen xuanhan863 shubhampachori12110095 labimage dachengxiaocheng microcompunics hajungong007 haoruozhang goodmanwang haudren liyi2017 duotun wangg12 celesius mingliangfu jkznst rgbd-cnn messixpro zgl1113 fransicsxu cnchence ewenwan shlpu pchan-pipeline zuwuwang andudu debaraj-barua ubiqelife-lin leica8244 sedlaj45 opentld johndpope michaelchi08 thetesla sunjinghua j-polden asbe mirkow yangliupku armeen ritesh1991 panchos39 l0gicforce dc1991 bokorn tonyle9 zgsxwsdxg fendaq im2ex archive-git-repo hridaybavle kaju-bubanja sefrin hangwudy qiuyue1 fastlater zumbalamambo jwm111 moiseevigor borongyuan chenjianhua1992 chyphen777 galenooo mrlooi zk8888 sbpl-cruz ziqichai doctorwk007 qinhuaping seanyan604 eirikwha birlrobotics my3jie luolizhuiyuyun crazypandaxj evakacjn jinlinyi reach-xx sjtuytc tianzhouwang atabakd twtravel foolyc hwtwj elementli kurnianggoro haocou siddhantnadkarni alebasso80 ruichen-v sunbirddy sergioragostinho mrkcass yellowfighter r-pad lorenzograziano yunxijun st-le

posecnn's Issues

synthesizer argument error (python argument type does not match c++)

Hi
I was trying to run the training shell script: ./experiments/scripts/lov_color_2d_train.sh 0
When it runs it stops at render function and gives me this error: I guess it has problems matching str in python to string in c++ which could be cython error.
"
Exception in thread Thread-1:
Traceback (most recent call last):
File "/usr/lib/python2.7/threading.py", line 801, in __bootstrap_inner
self.run()
File "/usr/lib/python2.7/threading.py", line 754, in run
self.__target(*self.__args, *self.__kwargs)
File "./tools/train_net.py", line 160, in render
synthesizer = libsynthesizer.Synthesizer(cfg.CAD, cfg.POSE )
ArgumentError: Python argument types in
Synthesizer.init(Synthesizer, str, str)
did not match C++ signature:
init(_object, std::string, std::string)
"

The whole log file is attached:`+ echo Logging output to experiments/logs/lov_color_2d_train.txt.2018-07-10_15-39-28
Logging output to experiments/logs/lov_color_2d_train.txt.2018-07-10_15-39-28

export LD_PRELOAD=/usr/lib/libtcmalloc.so.4
LD_PRELOAD=/usr/lib/libtcmalloc.so.4
./tools/train_net.py --gpu 0 --network vgg16_convs --weights data/imagenet_models/vgg16.npy --imdb lov_train --cfg experiments/cfgs/lov_color_2d.yml --cad data/LOV/models.txt --pose data/LOV/poses.txt --iters 160000
shapenet_scene_train
shapenet_scene_val
shapenet_single_train
shapenet_single_val
gmu_scene_train
gmu_scene_val
rgbd_scene_train
rgbd_scene_val
rgbd_scene_trainval
lov_train
lov_val
lov_keyframe
lov_trainval
lov_debug
lov_train_few
lov_val_few
lov_single_002_master_chef_can_train
lov_single_002_master_chef_can_val
lov_single_002_master_chef_can_keyframe
lov_single_003_cracker_box_train
lov_single_003_cracker_box_val
lov_single_003_cracker_box_keyframe
lov_single_004_sugar_box_train
lov_single_004_sugar_box_val
lov_single_004_sugar_box_keyframe
lov_single_005_tomato_soup_can_train
lov_single_005_tomato_soup_can_val
lov_single_005_tomato_soup_can_keyframe
lov_single_006_mustard_bottle_train
lov_single_006_mustard_bottle_val
lov_single_006_mustard_bottle_keyframe
lov_single_007_tuna_fish_can_train
lov_single_007_tuna_fish_can_val
lov_single_007_tuna_fish_can_keyframe
lov_single_008_pudding_box_train
lov_single_008_pudding_box_val
lov_single_008_pudding_box_keyframe
lov_single_009_gelatin_box_train
lov_single_009_gelatin_box_val
lov_single_009_gelatin_box_keyframe
lov_single_010_potted_meat_can_train
lov_single_010_potted_meat_can_val
lov_single_010_potted_meat_can_keyframe
lov_single_011_banana_train
lov_single_011_banana_val
lov_single_011_banana_keyframe
lov_single_019_pitcher_base_train
lov_single_019_pitcher_base_val
lov_single_019_pitcher_base_keyframe
lov_single_021_bleach_cleanser_train
lov_single_021_bleach_cleanser_val
lov_single_021_bleach_cleanser_keyframe
lov_single_024_bowl_train
lov_single_024_bowl_val
lov_single_024_bowl_keyframe
lov_single_025_mug_train
lov_single_025_mug_val
lov_single_025_mug_keyframe
lov_single_035_power_drill_train
lov_single_035_power_drill_val
lov_single_035_power_drill_keyframe
lov_single_036_wood_block_train
lov_single_036_wood_block_val
lov_single_036_wood_block_keyframe
lov_single_037_scissors_train
lov_single_037_scissors_val
lov_single_037_scissors_keyframe
lov_single_040_large_marker_train
lov_single_040_large_marker_val
lov_single_040_large_marker_keyframe
lov_single_051_large_clamp_train
lov_single_051_large_clamp_val
lov_single_051_large_clamp_keyframe
lov_single_052_extra_large_clamp_train
lov_single_052_extra_large_clamp_val
lov_single_052_extra_large_clamp_keyframe
lov_single_061_foam_brick_train
lov_single_061_foam_brick_val
lov_single_061_foam_brick_keyframe
ycb_trainval
ycb_single_002_master_chef_can_train
ycb_single_003_cracker_box_train
ycb_single_004_sugar_box_train
ycb_single_005_tomato_soup_can_train
ycb_single_006_mustard_bottle_train
ycb_single_007_tuna_fish_can_train
ycb_single_008_pudding_box_train
ycb_single_009_gelatin_box_train
ycb_single_010_potted_meat_can_train
ycb_single_011_banana_train
ycb_single_019_pitcher_base_train
ycb_single_021_bleach_cleanser_train
ycb_single_024_bowl_train
ycb_single_025_mug_train
ycb_single_035_power_drill_train
ycb_single_036_wood_block_train
ycb_single_037_scissors_train
ycb_single_040_large_marker_train
ycb_single_051_large_clamp_train
ycb_single_052_extra_large_clamp_train
ycb_single_061_foam_brick_train
yumi_train
linemod_ape_train
linemod_ape_test
linemod_ape_train_few
linemod_ape_test_few
linemod_benchvise_train
linemod_benchvise_test
linemod_benchvise_train_few
linemod_benchvise_test_few
linemod_bowl_train
linemod_bowl_test
linemod_bowl_train_few
linemod_bowl_test_few
linemod_camera_train
linemod_camera_test
linemod_camera_train_few
linemod_camera_test_few
linemod_can_train
linemod_can_test
linemod_can_train_few
linemod_can_test_few
linemod_cat_train
linemod_cat_test
linemod_cat_train_few
linemod_cat_test_few
linemod_cup_train
linemod_cup_test
linemod_cup_train_few
linemod_cup_test_few
linemod_driller_train
linemod_driller_test
linemod_driller_train_few
linemod_driller_test_few
linemod_duck_train
linemod_duck_test
linemod_duck_train_few
linemod_duck_test_few
linemod_eggbox_train
linemod_eggbox_test
linemod_eggbox_train_few
linemod_eggbox_test_few
linemod_glue_train
linemod_glue_test
linemod_glue_train_few
linemod_glue_test_few
linemod_holepuncher_train
linemod_holepuncher_test
linemod_holepuncher_train_few
linemod_holepuncher_test_few
linemod_iron_train
linemod_iron_test
linemod_iron_train_few
linemod_iron_test_few
linemod_lamp_train
linemod_lamp_test
linemod_lamp_train_few
linemod_lamp_test_few
linemod_phone_train
linemod_phone_test
linemod_phone_train_few
linemod_phone_test_few
sym_train
Called with args:
Namespace(cad_name='data/LOV/models.txt', cfg_file='experiments/cfgs/lov_color_2d.yml', gpu_id=0, imdb_name='lov_train', max_iters=160000, network_name='vgg16_convs', pose_name='data/LOV/poses.txt', pretrained_ckpt=None, pretrained_model='data/imagenet_models/vgg16.npy', randomize=False, rig_name=None)
Using config:
{'ANCHOR_RATIOS': [0.5, 1, 2],
'ANCHOR_SCALES': [8, 16, 32],
'BACKGROUND': '',
'CAD': '',
'EPS': 1e-14,
'EXP_DIR': 'lov',
'FEATURE_STRIDE': 16,
'FLIP_X': False,
'GPU_ID': 0,
'INPUT': 'COLOR',
'NETWORK': 'VGG16',
'PIXEL_MEANS': array([[[102.9801, 115.9465, 122.7717]]]),
'POSE': '',
'RIG': '',
'RNG_SEED': 3,
'ROOT_DIR': '/home/mamad/PoseCNN',
'TEST': {'BBOX_REG': True,
'GAN': False,
'GRID_SIZE': 256,
'NMS': 0.3,
'POSE_REFINE': False,
'POSE_REG': True,
'RANSAC': False,
'RPN_NMS_THRESH': 0.7,
'RPN_POST_NMS_TOP_N': 300,
'RPN_PRE_NMS_TOP_N': 6000,
'SCALES_BASE': [1.0],
'SEGMENTATION': True,
'SINGLE_FRAME': True,
'SYNTHETIC': False,
'VERTEX_REG_2D': True,
'VERTEX_REG_3D': False,
'VISUALIZE': True,
'VOTING_THRESHOLD': -1},
'TRAIN': {'ADAPT': False,
'ADAPT_NUM': 400,
'ADAPT_RATIO': 1,
'ADAPT_ROOT': '',
'ADAPT_WEIGHT': 0.1,
'ADD_NOISE': True,
'BATCH_SIZE': 128,
'BBOX_INSIDE_WEIGHTS': [1.0, 1.0, 1.0, 1.0],
'BBOX_NORMALIZE_MEANS': [0.0, 0.0, 0.0, 0.0],
'BBOX_NORMALIZE_STDS': [0.1, 0.1, 0.2, 0.2],
'BBOX_NORMALIZE_TARGETS': True,
'BBOX_NORMALIZE_TARGETS_PRECOMPUTED': True,
'BG_THRESH_HI': 0.5,
'BG_THRESH_LO': 0.1,
'CHROMATIC': True,
'DISPLAY': 20,
'FG_FRACTION': 0.25,
'FG_THRESH': 0.5,
'GAMMA': 0.1,
'GAN': False,
'GRID_SIZE': 256,
'HAS_RPN': True,
'IMS_PER_BATCH': 2,
'LABEL_W': 1.0,
'LEARNING_RATE': 0.001,
'MATCHING': False,
'MOMENTUM': 0.9,
'NUM_CLASSES': 22,
'NUM_STEPS': 5,
'NUM_UNITS': 64,
'OPTIMIZER': 'MOMENTUM',
'POSE_REG': True,
'POSE_W': 1.0,
'RPN_BATCHSIZE': 256,
'RPN_BBOX_INSIDE_WEIGHTS': [1.0, 1.0, 1.0, 1.0],
'RPN_CLOBBER_POSITIVES': False,
'RPN_FG_FRACTION': 0.5,
'RPN_NEGATIVE_OVERLAP': 0.3,
'RPN_NMS_THRESH': 0.7,
'RPN_POSITIVE_OVERLAP': 0.7,
'RPN_POSITIVE_WEIGHT': -1.0,
'RPN_POST_NMS_TOP_N': 2000,
'RPN_PRE_NMS_TOP_N': 12000,
'SCALES_BASE': [1.0],
'SEGMENTATION': True,
'SINGLE_FRAME': True,
'SNAPSHOT_INFIX': 'lov',
'SNAPSHOT_ITERS': 10000,
'SNAPSHOT_PREFIX': 'vgg16_fcn_color_single_frame_2d_pose_add',
'STEPSIZE': 80000,
'SYMSIZE': 0,
'SYNITER': 0,
'SYNNUM': 80000,
'SYNROOT': 'data/LOV/data_syn/',
'SYNTHESIZE': True,
'SYN_CLASS_INDEX': -1,
'SYN_HEIGHT': 480,
'SYN_ONLINE': True,
'SYN_RATIO': 5,
'SYN_SAMPLE_OBJECT': True,
'SYN_SAMPLE_POSE': True,
'SYN_TFAR': 2.0,
'SYN_TNEAR': 0.5,
'SYN_WIDTH': 640,
'THRESHOLD_LABEL': 1.0,
'TRAINABLE': True,
'USE_FLIPPED': False,
'USE_GT': False,
'VERTEX_REG_2D': True,
'VERTEX_REG_3D': False,
'VERTEX_W': 1.0,
'VERTEX_W_INSIDE': 10.0,
'VISUALIZE': False,
'VOTING_THRESHOLD': -1,
'WEIGHT_REG': 0.0001},
'USE_GPU_NMS': True}
/home/mamad/PoseCNN/tools/../lib/datasets/../../data/LOV/models/002_master_chef_can/points.xyz
/home/mamad/PoseCNN/tools/../lib/datasets/../../data/LOV/models/003_cracker_box/points.xyz
/home/mamad/PoseCNN/tools/../lib/datasets/../../data/LOV/models/004_sugar_box/points.xyz
/home/mamad/PoseCNN/tools/../lib/datasets/../../data/LOV/models/005_tomato_soup_can/points.xyz
/home/mamad/PoseCNN/tools/../lib/datasets/../../data/LOV/models/006_mustard_bottle/points.xyz
/home/mamad/PoseCNN/tools/../lib/datasets/../../data/LOV/models/007_tuna_fish_can/points.xyz
/home/mamad/PoseCNN/tools/../lib/datasets/../../data/LOV/models/008_pudding_box/points.xyz
/home/mamad/PoseCNN/tools/../lib/datasets/../../data/LOV/models/009_gelatin_box/points.xyz
/home/mamad/PoseCNN/tools/../lib/datasets/../../data/LOV/models/010_potted_meat_can/points.xyz
/home/mamad/PoseCNN/tools/../lib/datasets/../../data/LOV/models/011_banana/points.xyz
/home/mamad/PoseCNN/tools/../lib/datasets/../../data/LOV/models/019_pitcher_base/points.xyz
/home/mamad/PoseCNN/tools/../lib/datasets/../../data/LOV/models/021_bleach_cleanser/points.xyz
/home/mamad/PoseCNN/tools/../lib/datasets/../../data/LOV/models/024_bowl/points.xyz
/home/mamad/PoseCNN/tools/../lib/datasets/../../data/LOV/models/025_mug/points.xyz
/home/mamad/PoseCNN/tools/../lib/datasets/../../data/LOV/models/035_power_drill/points.xyz
/home/mamad/PoseCNN/tools/../lib/datasets/../../data/LOV/models/036_wood_block/points.xyz
/home/mamad/PoseCNN/tools/../lib/datasets/../../data/LOV/models/037_scissors/points.xyz
/home/mamad/PoseCNN/tools/../lib/datasets/../../data/LOV/models/040_large_marker/points.xyz
/home/mamad/PoseCNN/tools/../lib/datasets/../../data/LOV/models/051_large_clamp/points.xyz
/home/mamad/PoseCNN/tools/../lib/datasets/../../data/LOV/models/052_extra_large_clamp/points.xyz
/home/mamad/PoseCNN/tools/../lib/datasets/../../data/LOV/models/061_foam_brick/points.xyz
Loaded dataset lov_train for training
symmetry
[0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1]
lov_train gt roidb loaded from /home/mamad/PoseCNN/data/cache/lov_train_gt_roidb.pkl
class weights: [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]
Output will be saved to /home/mamad/PoseCNN/output/lov/lov_train
/gpu:0
registered Poly3
registered Poly3
registered Linear
registered Linear
Start Rendering ...
Start Rendering fn
('CAD ', <type 'str'>)
('pose ', <type 'str'>)
Exception in thread Thread-1:
Traceback (most recent call last):
File "/usr/lib/python2.7/threading.py", line 801, in __bootstrap_inner
self.run()
File "/usr/lib/python2.7/threading.py", line 754, in run
self.__target(*self.__args, *self.__kwargs)
File "./tools/train_net.py", line 160, in render
synthesizer = libsynthesizer.Synthesizer(cfg.CAD, cfg.POSE )
ArgumentError: Python argument types in
Synthesizer.init(Synthesizer, str, str)
did not match C++ signature:
init(_object, std::string, std::string)

Tensor("fifo_queue_Dequeue:0", dtype=float32)
Tensor("conv5_3/conv5_3:0", shape=(?, ?, ?, 512), dtype=float32)
Tensor("conv4_3/conv4_3:0", shape=(?, ?, ?, 512), dtype=float32)
Tensor("score_conv4/score_conv4:0", shape=(?, ?, ?, 64), dtype=float32)
Tensor("upscore_conv5_1:0", shape=(?, ?, ?, 64), dtype=float32)
Tensor("upscore_1:0", shape=(?, ?, ?, 64), dtype=float32)
Tensor("score/score:0", shape=(?, ?, ?, 22), dtype=float32)
Tensor("div:0", shape=(?, ?, ?, 22), dtype=float32)
Tensor("fifo_queue_Dequeue:1", dtype=int32)
Tensor("conv5_3/conv5_3:0", shape=(?, ?, ?, 512), dtype=float32)
Tensor("conv4_3/conv4_3:0", shape=(?, ?, ?, 512), dtype=float32)
Tensor("score_conv4_vertex/BiasAdd:0", shape=(?, ?, ?, 128), dtype=float32)
Tensor("upscore_conv5_vertex_1:0", shape=(?, ?, ?, 128), dtype=float32)
Tensor("ToInt32:0", shape=(?, ?, ?), dtype=int32)
Tensor("vertex_pred/BiasAdd:0", shape=(?, ?, ?, 66), dtype=float32)
Tensor("fifo_queue_Dequeue:6", dtype=float32)
Tensor("fifo_queue_Dequeue:7", dtype=float32)
Tensor("fifo_queue_Dequeue:5", dtype=float32)
Tensor("conv5_3/conv5_3:0", shape=(?, ?, ?, 512), dtype=float32)
Tensor("hough:0", shape=(?, 7), dtype=float32)
Tensor("conv4_3/conv4_3:0", shape=(?, ?, ?, 512), dtype=float32)
Tensor("hough:0", shape=(?, 7), dtype=float32)
RoiPool(top_data=<tf.Tensor 'pool5:0' shape=(?, 7, 7, 512) dtype=float32>, argmax=<tf.Tensor 'pool5:1' shape=(?, 7, 7, 512) dtype=int32>)
RoiPool(top_data=<tf.Tensor 'pool4_1:0' shape=(?, 7, 7, 512) dtype=float32>, argmax=<tf.Tensor 'pool4_1:1' shape=(?, 7, 7, 512) dtype=int32>)
Tensor("poses_tanh:0", shape=(?, 88), dtype=float32)
Tensor("hough:3", shape=(?, 88), dtype=float32)
Tensor("poses_pred:0", shape=(?, 88), dtype=float32)
Tensor("hough:2", shape=(?, 88), dtype=float32)
Tensor("hough:3", shape=(?, 88), dtype=float32)
Tensor("fifo_queue_Dequeue:8", dtype=float32)
Tensor("fifo_queue_Dequeue:9", dtype=float32)
Use network vgg16_convs in training
2018-07-10 15:39:32.228268: I tensorflow/core/platform/cpu_feature_guard.cc:137] Your CPU supports instructions that this TensorFlow binary was not compiled to use: SSE4.1 SSE4.2 AVX
2018-07-10 15:39:32.337709: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1030] Found device 0 with properties:
name: TITAN X (Pascal) major: 6 minor: 1 memoryClockRate(GHz): 1.531
pciBusID: 0000:02:00.0
totalMemory: 11.90GiB freeMemory: 11.36GiB
2018-07-10 15:39:32.337748: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1120] Creating TensorFlow device (/device:GPU:0) -> (device: 0, name: TITAN X (Pascal), pci bus id: 0000:02:00.0, compute capability: 6.1)
lov_train backgrounds loaded from /home/mamad/PoseCNN/data/cache/backgrounds.pkl
lov_train backgrounds depth loaded from /home/mamad/PoseCNN/data/cache/backgrounds_depth.pkl
Solving...
('Layer.py back', [])
Loading pretrained model weights from data/imagenet_models/vgg16.npy
conv5_1
conv5_1 weights assigned
conv5_1 biases assigned
fc6
fc6 weights assigned
fc6 biases assigned
conv5_3
conv5_3 weights assigned
conv5_3 biases assigned
fc7
fc7 weights assigned
fc7 biases assigned
fc8
conv5_2
conv5_2 weights assigned
conv5_2 biases assigned
conv4_1
conv4_1 weights assigned
conv4_1 biases assigned
conv4_2
conv4_2 weights assigned
conv4_2 biases assigned
conv4_3
conv4_3 weights assigned
conv4_3 biases assigned
conv3_3
conv3_3 weights assigned
conv3_3 biases assigned
conv3_2
conv3_2 weights assigned
conv3_2 biases assigned
conv3_1
conv3_1 weights assigned
conv3_1 biases assigned
conv1_1
conv1_1 weights assigned
conv1_1 biases assigned
conv1_2
conv1_2 weights assigned
conv1_2 biases assigned
conv2_2
conv2_2 weights assigned
conv2_2 biases assigned
conv2_1
conv2_1 weights assigned
conv2_1 biases assigned`

Error about sophus/se3.hpp

Hi, does anybody came across this problem:

/PoseCNN/lib/synthesize/../kinect_fusion/include/df/camera/rig.h:7:26: fatal error: sophus/se3.hpp: No such file or directory

It seems I need to have se3.hpp in sophus, however I only have se3.h in my installation file of sophus, and it doesn't work for for me by altering the file name, so I was wondering if it's the problem with my installation of sophus?

How to build this?

More details and how to build this project can be found here

cannot import name gpu_normals

When I try to run the ./experiments/scripts/demo.sh $GPU_ID demo, I get the following error:

+ ./tools/demo.py --gpu 0 --network vgg16_convs --model data/demo_models/vgg16_fcn_color_single_frame_2d_pose_add_lov_iter_160000.ckpt --imdb lov_keyframe --cfg experiments/cfgs/lov_color_2d.yml --rig data/LOV/camera.json --cad data/LOV/models.txt --pose data/LOV/poses.txt --background data/cache/backgrounds.pkl
Traceback (most recent call last):
  File "./tools/demo.py", line 13, in <module>
    from fcn.test import test_net_images
  File "/root/PoseCNN/tools/../lib/fcn/test.py", line 29, in <module>
    from normals import gpu_normals
ImportError: cannot import name gpu_normals

There is only a gpu_normals.pyx and no gpu_normals.py. Am I missing any package that processes the gpu_normals.pyx to a normal python module?

AttributeError: 'vgg16_convs' object has no attribute 'state'

Hi,
I got the above error when I try running
/experiments/scripts/lov_color_2d_test.sh 0
And when I got into /lib/networks/vgg16_convs.py, there's indeed no attribute state. It is the same for weight and depth. The only network having these attributes is vgg16. However, when I input --network vgg16 instead of --network vgg16-convs, it raises the error

Traceback (most recent call last):
  File "./tools/test_net.py", line 105, in <module>
    network = get_network(args.network_name)
  File "/home/thomas/Desktop/Master_Project/PoseCNN/tools/../lib/networks/factory.py", line 50, in get_network
    raise KeyError('Unknown network: {}'.format(name))
KeyError: 'Unknown network: vgg16'

So I was wondering : what is the attribute ? what does it represent and where does it come from ?
How can I fix this ?
Thank you

when I execute sh make.sh I get some problem

/usr/bin/ld:Can not find -ltensorflow_framework
collect2: error: ld returned 1 exit status
hough_voting_gpu_layer
In file included from hough_voting_op.cc:25:0:
ransac.h:31:21: fatal error: nlopt.hpp: no such directory
compilation terminated.
hough_voting_layer

i install tensorflow-gpu through pip
my python version is 2.7

How can I solve this ??
thx!!!

ld cannot find -lkfusion

Hi,
When I Run make into the build directory, I got this issue :

[ 50%] Linking CXX shared library libsynthesizer.so
/usr/bin/ld: cannot find -lkfusion
collect2: error: ld returned 1 exit status
CMakeFiles/synthesizer.dir/build.make:417: recipe for target 'libsynthesizer.so' failed
make[2]: *** [libsynthesizer.so] Error 1
CMakeFiles/Makefile2:67: recipe for target 'CMakeFiles/synthesizer.dir/all' failed
make[1]: *** [CMakeFiles/synthesizer.dir/all] Error 2
Makefile:83: recipe for target 'all' failed
make: *** [all] Error 2

So I guess I have to build and compile the directory "kinect_fusion" in $ROOT/lib. but then, I receive this error:

[  1%] Building NVCC (Device) object CMakeFiles/kinectFusion.dir/src/voxel/kinectFusion_generated_voxelGrid.cu.o
#$ _SPACE_= 
#$ _CUDART_=cudart
#$ _HERE_=/usr/local/cuda-9.0/bin
#$ _THERE_=/usr/local/cuda-9.0/bin
#$ _TARGET_SIZE_=
#$ _TARGET_DIR_=
#$ _TARGET_DIR_=targets/x86_64-linux
#$ TOP=/usr/local/cuda-9.0/bin/..
#$ NVVMIR_LIBRARY_DIR=/usr/local/cuda-9.0/bin/../nvvm/libdevice
#$ LD_LIBRARY_PATH=/usr/local/cuda-9.0/bin/../lib:
#$ PATH=/usr/local/cuda-9.0/bin/../open64/bin:/usr/local/cuda-9.0/bin/../nvvm/bin:/usr/local/cuda-9.0/bin:/home/thomas/anaconda3/envs/poseCNN/bin:/usr/local/cuda-8.0/bin:/home/thomas/bin:/home/thomas/.local/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/games:/usr/local/games:/snap/bin:/usr/local/cuda-8.0/bin:/home/thomas/anaconda3/bin
#$ INCLUDES="-I/usr/local/cuda-9.0/bin/../targets/x86_64-linux/include"  
#$ LIBRARIES=  "-L/usr/local/cuda-9.0/bin/../targets/x86_64-linux/lib/stubs" "-L/usr/local/cuda-9.0/bin/../targets/x86_64-linux/lib"
#$ CUDAFE_FLAGS=
#$ PTXAS_FLAGS=
#$ "/usr/bin"/cc -std=c++11 -D__CUDA_ARCH__=610 -E -x c++  -DCUDA_DOUBLE_MATH_FUNCTIONS -D__CUDACC__ -D__NVCC__ -D__CUDACC_EXTENDED_LAMBDA__ -D__CUDACC_RELAXED_CONSTEXPR__  "-O3" "-DNDEBUG" -fPIC -O3 -I"/usr/local/cuda-9.0/include" -I"/home/thomas/Desktop/PoseCNN-master/lib/kinect_fusion/include" -I"/usr/local/include/pangolin" -I"/usr/include/eigen3" -I"/usr/include/suitesparse" -I"/usr/local/include" -I"/usr/include" "-I/usr/local/cuda-9.0/bin/../targets/x86_64-linux/include"   -D"__CUDACC_VER_BUILD__=176" -D"__CUDACC_VER_MINOR__=0" -D"__CUDACC_VER_MAJOR__=9" -D"__CUDACC__" -D"COMPILE_DIR=\"/home/thomas/Desktop/PoseCNN-master/lib/kinect_fusion\"" -D"BUILD_POLY3" -D"BUILD_LINEAR" -D"NVCC" -include "cuda_runtime.h" -m64 "/home/thomas/Desktop/PoseCNN-master/lib/kinect_fusion/./src/voxel/voxelGrid.cu" > "/tmp/tmpxft_0000180e_00000000-4_voxelGrid.cpp1.ii" 
In file included from /usr/local/cuda-9.0/include/common_functions.h:50:0,
                 from /usr/local/cuda-9.0/include/cuda_runtime.h:115,
                 from <command-line>:0:
/usr/local/cuda-9.0/include/crt/common_functions.h:64:24: error: token ""__CUDACC_VER__ is no longer supported.  Use __CUDACC_VER_MAJOR__, __CUDACC_VER_MINOR__, and __CUDACC_VER_BUILD__ instead."" is not valid in preprocessor expressions
 #define __CUDACC_VER__ "__CUDACC_VER__ is no longer supported.  Use __CUDACC_VER_MAJOR__, __CUDACC_VER_MINOR__, and __CUDACC_VER_BUILD__ instead."
                        ^
/usr/include/eigen3/Eigen/src/Core/util/Macros.h:364:33: note: in expansion of macro ‘__CUDACC_VER__’
 #if defined(__CUDACC_VER__) &&  __CUDACC_VER__ >= 70500 && __cplusplus > 199711L
                                 ^
# --error 0x1 --
CMake Error at kinectFusion_generated_voxelGrid.cu.o.Release.cmake:219 (message):
  Error generating
  /home/thomas/Desktop/PoseCNN-master/lib/kinect_fusion/build/CMakeFiles/kinectFusion.dir/src/voxel/./kinectFusion_generated_voxelGrid.cu.o


CMakeFiles/kinectFusion.dir/build.make:10209: recipe for target 'CMakeFiles/kinectFusion.dir/src/voxel/kinectFusion_generated_voxelGrid.cu.o' failed
make[2]: *** [CMakeFiles/kinectFusion.dir/src/voxel/kinectFusion_generated_voxelGrid.cu.o] Error 1
CMakeFiles/Makefile2:67: recipe for target 'CMakeFiles/kinectFusion.dir/all' failed
make[1]: *** [CMakeFiles/kinectFusion.dir/all] Error 2
Makefile:83: recipe for target 'all' failed
make: *** [all] Error 2

Has anyone encounter this ?

I am using :
Ubuntu 16.04
Cuda 9.0
Eigen3 : (3.3~beta1-2)

cannot handel opengl problem

Hi,here:
I met this kind errors,": error: ‘pangolin::GlBuffer::GlBuffer(const pangolin::GlBuffer&)’ is private",while using ubuntu14.04,the default opengl-version is 2.1.
some discussion say that,using opengl version4.1 can avoid these error,however,as I know,opengl version is depend on nvida-driver,and if I install nvidia driver without "--no-opengl-files",I get struck in circular login while turn on computer.So,do you know how to avoid or solve it?Thank you.

Error Running demo.sh

I am trying to run the demo :
./experiments/scripts/demo.sh $GPU_ID
but I get the following error :

Traceback (most recent call last):
  File "./tools/demo.py", line 84, in <module>
    imdb = get_imdb(args.imdb_name)
  File "/home/thomas/Desktop/PoseCNN-master/tools/../lib/datasets/factory.py", line 116, in get_imdb
    return __sets[name]()
  File "/home/thomas/Desktop/PoseCNN-master/tools/../lib/datasets/factory.py", line 57, in <lambda>
    datasets.lov(split))
  File "/home/thomas/Desktop/PoseCNN-master/tools/../lib/datasets/lov.py", line 55, in __init__
    'Data path does not exist: {}'.format(self._data_path)
AssertionError: Data path does not exist: /home/thomas/Desktop/PoseCNN-master/tools/../lib/datasets/../../data/LOV/data

If I get it right, it's trying to acces to a folder data that does not exist. Am I suppose to create it ? If yes, should I fill it and with what ?

Segmentation Fault while running demo

2018-07-06 09:39:07.632390: I tensorflow/core/platform/cpu_feature_guard.cc:140] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA Loading model weights from data/demo_models/vgg16_fcn_color_single_frame_2d_pose_add_lov_iter_160000.ckpt data/demo_images/000004-color.png ./experiments/scripts/demo.sh: line 17: 3175 Segmentation fault (core dumped) ./tools/demo.py --gpu 0 --network vgg16_convs --model data/demo_models/vgg16_fcn_color_single_frame_2d_pose_add_lov_iter_160000.ckpt --imdb lov_keyframe --cfg experiments/cfgs/lov_color_2d.yml --rig data/LOV/camera.json --cad data/LOV/models.txt --pose data/LOV/poses.txt --background data/cache/backgrounds.pkl

Hi, while running the demo it loads the network and starts with the first image and terminates with a segmentation fault as described above.

I am running it on:
32GB RAM
Nvidia GTX 1070
Ubuntu 16.04
CUDA 8.0
cudNN 7.05
Tensorflow 1.8

It was tested with multiple tensorflow versions from 1.4 to 1.8 with no success

GL_SHADER_STORAGE_BUFFER’ was not declared in this scope

(poseCNN) cxx@cxx:~/wzw/poseEstimate/poseCNN/lib/synthesize/build$ make
Scanning dependencies of target synthesizer
[ 25%] Building CXX object CMakeFiles/synthesizer.dir/synthesize.cpp.o
In file included from /home/cxx/wzw/third-party/Pangolin/include/pangolin/pangolin.h:33:0,
from /home/cxx/wzw/poseEstimate/poseCNN/lib/synthesize/synthesize.hpp:15,
from /home/cxx/wzw/poseEstimate/poseCNN/lib/synthesize/synthesize.cpp:1:
/home/cxx/wzw/third-party/Pangolin/include/pangolin/gl/gl.h:173:29: error: ‘GL_SHADER_STORAGE_BUFFER’ was not declared in this scope
GlShaderStorageBuffer = GL_SHADER_STORAGE_BUFFER
^
In file included from /home/cxx/wzw/third-party/Pangolin/include/pangolin/gl/gl.h:248:0,
from /home/cxx/wzw/third-party/Pangolin/include/pangolin/pangolin.h:33,
from /home/cxx/wzw/poseEstimate/poseCNN/lib/synthesize/synthesize.hpp:15,
from /home/cxx/wzw/poseEstimate/poseCNN/lib/synthesize/synthesize.cpp:1:
/home/cxx/wzw/third-party/Pangolin/include/pangolin/gl/gl.hpp: In member function ‘void pangolin::GlTexture::CopyFrom(const pangolin::GlTexture&)’:
/home/cxx/wzw/third-party/Pangolin/include/pangolin/gl/gl.hpp:298:40: error: ‘glCopyImageSubData’ was not declared in this scope
width, height, 1);

nvcc fatal : Stray '"' character

When trying to build kinect_fusion which is needed to build synthesize I get following error:

[  1%] Building NVCC (Device) object CMakeFiles/kinectFusion.dir/src/voxel/kinectFusion_generated_voxelGrid.cu.o
CMake Warning (dev) at kinectFusion_generated_voxelGrid.cu.o.Release.cmake:81:
  Syntax Warning in cmake code at column 49

  Argument not separated from preceding token by whitespace.
This warning is for project developers.  Use -Wno-dev to suppress it.

nvcc fatal   : Stray '"' character
CMake Error at kinectFusion_generated_voxelGrid.cu.o.Release.cmake:222 (message):
  Error generating
  ~/PoseCNN/lib/kinect_fusion/build/CMakeFiles/kinectFusion.dir/src/voxel/./kinectFusion_generated_voxelGrid.cu.o


CMakeFiles/kinectFusion.dir/build.make:266: recipe for target 'CMakeFiles/kinectFusion.dir/src/voxel/kinectFusion_generated_voxelGrid.cu.o' failed
make[2]: *** [CMakeFiles/kinectFusion.dir/src/voxel/kinectFusion_generated_voxelGrid.cu.o] Error 1
CMakeFiles/Makefile2:67: recipe for target 'CMakeFiles/kinectFusion.dir/all' failed
make[1]: *** [CMakeFiles/kinectFusion.dir/all] Error 2
Makefile:83: recipe for target 'all' failed
make: *** [all] Error 2

I tried the patch here recommended here but without success. If anybody got this code to run it would be nice to share all the necessary steps.

What cmake version and cuda version did you use? I tried to downgrade cmake to 3.6 which was proposed here to fix this issue, but now I get new errors. If you could tell us exactly what version of things you used to get this running, that would be a great help.

Compile Error

Since it said that '-lkfusion' is not found when compiling 'lib/syntheize', I compile the 'lib/kinect_fusion' with following command:

cd kinect_fusion
mkdir build && cd build && cmake ..
make

Then it comes out with cuda error:

/usr/local/cuda-8.0/include/cuda_runtime.h(546): warning: calling a __host__ function("Eigen::Quaternion<float, (int)2> ::Quaternion") from a __host__ __device__ function("") is not allowed

/usr/local/cuda-8.0/include/cuda_runtime.h(546): warning: calling a __host__ function("Eigen::Quaternion<float, (int)2> ::Quaternion") from a __host__ __device__ function("") is not allowed

PoseCNN/lib/kinect_fusion/./src/transform/nonrigid.cu(758): error: calling a __host__ function("Eigen::Quaternion<float, (int)2> ::Quaternion") from a __global__ function("df::initializeNewBaseLevelVertexTransformsKernel<float, (int)4> ") is not allowed

PoseCNN/lib/kinect_fusion/./src/transform/nonrigid.cu(758): error: calling a __host__ function("Eigen::Quaternion<float, (int)2> ::Quaternion") from a __global__ function("df::initializeNewBaseLevelVertexTransformsKernel<float, (int)4> ") is not allowed

PoseCNN/lib/kinect_fusion/./src/transform/nonrigid.cu(97): error: calling a __host__ function("Eigen::Quaternion<float, (int)2> ::Quaternion") from a __global__ function("df::warpMeshKernel<float, (int)4, (int)1, (int)3> ") is not allowed

PoseCNN/lib/kinect_fusion/./src/transform/nonrigid.cu(97): error: calling a __host__ function("Eigen::Quaternion<float, (int)2> ::Quaternion") from a __global__ function("df::warpMeshKernel<float, (int)4, (int)1, (int)3> ") is not allowed

PoseCNN/lib/kinect_fusion/./src/transform/nonrigid.cu(97): error: calling a __host__ function("Eigen::Quaternion<float, (int)2> ::Quaternion") from a __global__ function("df::warpMeshKernel<float, (int)4, (int)2, (int)4> ") is not allowed

PoseCNN/lib/kinect_fusion/./src/transform/nonrigid.cu(97): error: calling a __host__ function("Eigen::Quaternion<float, (int)2> ::Quaternion") from a __global__ function("df::warpMeshKernel<float, (int)4, (int)2, (int)4> ") is not allowed

6 errors detected in the compilation of "/tmp/tmpxft_0000d886_00000000-7_nonrigid.cpp1.ii".
# --error 0x2 --
CMake Error at kfusion_generated_nonrigid.cu.o.cmake:266 (message):
  Error generating file
PoseCNN/lib/kinect_fusion/build/CMakeFiles/kfusion.dir/src/transform/./kfusion_generated_nonrigid.cu.o


CMakeFiles/kinectFusion.dir/build.make:91: recipe for target 'CMakeFiles/kfusion.dir/src/transform/kfusion_generated_nonrigid.cu.o' failed
make[2]: *** [CMakeFiles/kfusion.dir/src/transform/kfusion_generated_nonrigid.cu.o] Error 1
CMakeFiles/Makefile2:67: recipe for target 'CMakeFiles/kinectFusion.dir/all' failed
make[1]: *** [CMakeFiles/kinectFusion.dir/all] Error 2
Makefile:83: recipe for target 'all' failed
make: *** [all] Error 2

I read several issues in DA-RNN, tried but still not solved.
Is there any suggestions?
The system is Ubuntu16.04, and Python 3.5.
Thanks a lot!

Cannot find the includes with 'df/*' while compiling synthesize lib

I get the following error while trying to compile the synthesis lib.

df/camera/camera.h: No such file or directory

I indeed see some hard-coded paths in the CMakeLists.txt. For example:

set(xFusion_ROOT "/home/yuxiang/Projects/Deep_Pose/lib/kinect_fusion")

Which could be reason.

yaml.constructor.ConstructorError: could not determine a constructor for the tag

I am trying to run the demo and run into the following issue on my Ubuntu 16.04 machine.

Called with args:
Namespace(background_name='data/cache/backgrounds.pkl', cad_name='data/LOV/models.txt', cfg_file='experiments/cfgs/lov_color_2d.yml', gpu_id=0, imdb_name='lov_keyframe', kfusion=False, model='data/demo_models/vgg16_fcn_color_single_frame_2d_pose_add_lov_iter_160000.ckpt', network_name='vgg16_convs', pose_name='data/LOV/poses.txt', pretrained_model=None, rig_name='data/LOV/camera.json', wait=True)
Traceback (most recent call last):
File "./tools/demo.py", line 77, in
cfg_from_file(args.cfg_file)
File "/home/nivedithak/Downloads/PoseCNN-master/tools/../lib/fcn/config.py", line 303, in cfg_from_file
yaml_cfg = edict(yaml.load(f))
File "/home/nivedithak/Downloads/PoseCNN-master/PYTHON_27/local/lib/python2.7/site-packages/yaml/init.py", line 74, in load
return loader.get_single_data()
File "/home/nivedithak/Downloads/PoseCNN-master/PYTHON_27/local/lib/python2.7/site-packages/yaml/constructor.py", line 39, in get_single_data
return self.construct_document(node)
File "/home/nivedithak/Downloads/PoseCNN-master/PYTHON_27/local/lib/python2.7/site-packages/yaml/constructor.py", line 48, in construct_document
for dummy in generator:
File "/home/nivedithak/Downloads/PoseCNN-master/PYTHON_27/local/lib/python2.7/site-packages/yaml/constructor.py", line 398, in construct_yaml_map
value = self.construct_mapping(node)
File "/home/nivedithak/Downloads/PoseCNN-master/PYTHON_27/local/lib/python2.7/site-packages/yaml/constructor.py", line 208, in construct_mapping
return BaseConstructor.construct_mapping(self, node, deep=deep)
File "/home/nivedithak/Downloads/PoseCNN-master/PYTHON_27/local/lib/python2.7/site-packages/yaml/constructor.py", line 133, in construct_mapping
value = self.construct_object(value_node, deep=deep)
File "/home/nivedithak/Downloads/PoseCNN-master/PYTHON_27/local/lib/python2.7/site-packages/yaml/constructor.py", line 88, in construct_object
data = constructor(self, node)
File "/home/nivedithak/Downloads/PoseCNN-master/PYTHON_27/local/lib/python2.7/site-packages/yaml/constructor.py", line 414, in construct_undefined
node.start_mark)
yaml.constructor.ConstructorError: could not determine a constructor for the tag 'tag:yaml.org,2002:python/tuple'
in "experiments/cfgs/lov_color_2d.yml", line 12, column 16

I don't see any unusual characters in that line and it is using the python specific tag !!python/tuple.

Make error for compiling synthesize

Hi Yu Xiang,

Thank you so much for providing the code of pose estimation.
I followed your README instructions and have been a problem with installing.

At step 4, the command "make" produced the errors related to pangolin and opengl.
For example,

home/PoseCNN/lib/synthesize/synthesize.cpp:748:58: error: no matching function for call to ‘df::GLRenderer<df::CanonicalVertRenderType>::setProjectionMatrix(pangolin::OpenGlMatrixSpec&)’
   renderer_->setProjectionMatrix(projectionMatrix_reverse);

/home/PoseCNN/lib/synthesize/synthesize.cpp:789:39: error: no matching function for call to ‘pangolin::OpenGlMatrix::OpenGlMatrix(Eigen::Matrix4f&)’
     pangolin::OpenGlMatrix mvMatrix(mv);

/home/PoseCNN/lib/synthesize/synthesize.cpp:1951:50: error: no matching function for call to ‘df::GLRenderer<df::CanonicalVertRenderType>::setProjectionMatrix(pangolin::OpenGlMatrixSpec&)’
   renderer_->setProjectionMatrix(projectionMatrix);

Do you have any ideas for solving these errors?

Thank you!

The system information follows.
OS: Ubuntu14.04
Python:3.5

Segmentation fault while running the demo

How to make a new object annotation?

i want add another object into the training dataset, do you have tool for fast annotation, can you share me!

YCB-Video dataset

@yuxng Hello Dr Xiang，the GoogleDrive is not available in China mainland, could you please provide an accessible link for downloading the YCB-video dataset?

ImportError while Running the demo

when Running the demo:

./experiments/scripts/demo.sh --gpu 0

I got the following error:

ImportError: /home/zgl/PoseCNN/tools/../lib/synthesize/synthesizer.so: undefined symbol: ZN11SynthesizerC1ENSt7__cxx1112basic_stringIcSt11char_traitsIcESaIcEEES5

anyone has gotten the same error and solved it?

Implementation problems

Hi Yu Xiang,

Thanks for providing the code for your paper. I have been having some problems downloading and running the commands that you provided.

When I run the demo file, I get the error "nError: Path does not exist: /home/rajatmittal/Documents/posecnn/tools/../lib/datasets/../../data/LOV/models/002_master_chef_can/points.xyz". Do you know why this is happening?
Your YCB dataset is huge. 265GB. Is it possible for you to provide a trimmed down version for it.
You mention in step 4 that it is optional. Do I still have to compile the cython interface that you mention in step 4?
The number of dependencies for lib/synthesize are huge. Again, do I have to install it.

Your help would be really appreciated.

Thanks.

compile tf with bazel with/without jemalloc?

Hi, did you compile tensorflow with or without jemalloc ?

Compile Error: fatal error: nlopt.hpp: No such file or directory

When compile in lib, after

sh make.sh

an error comes out as follows:

In file included from hough_voting_op.cc:25:0:
ransac.h:31:21: fatal error: nlopt.hpp: No such file or directory
compilation terminated.

I used Ubuntu 16.04, Python3.5, Tensorflow 1.4.1, CUDA 8.0.

Toolbox/Guidelines to run for Linemod Dataset?

Hi @yuxng ,

Thanks for providing a well structured code package. Could you also provide data pre-processing steps for the LINEMOD object dataset? I am unable to figure out ways to generate train/test index files.

P.S. - I am trying to train your network for benchvise object in linemod.

Thanks,

train and test error?

my hardware: ubuntu16.04, gcc5.4，cuda8.0, cudnn6.0, tensorflow1.4, when i run the train or test script, it happens "_ZTIN10tensorflow8OpKernelE". After i add -D_GLIBCXX_USE_CXX11_ABI=0 in the make.sh, it happen "_ZN10tensorflow8internal21CheckOpMessageBuilder9NewStringB5cxx11Ev".

I have tried many methods but can't solve above problem. can you tell me what's your implementation environment? thanks

Data folder not found while running the demo

Hi! Im having the following problem while running the demo:

Traceback (most recent call last):
  File "./tools/demo.py", line 84, in <module>
    imdb = get_imdb(args.imdb_name)
  File "/home/fmartinez/ERL/PoseCNN/tools/../lib/datasets/factory.py", line 116, in get_imdb
    return __sets[name]()
  File "/home/fmartinez/ERL/PoseCNN/tools/../lib/datasets/factory.py", line 57, in <lambda>
    datasets.lov(split))
  File "/home/fmartinez/ERL/PoseCNN/tools/../lib/datasets/lov.py", line 55, in __init__
    'Data path does not exist: {}'.format(self._data_path)
AssertionError: Data path does not exist: /home/fmartinez/ERL/PoseCNN/tools/../lib/datasets/../../data/LOV/data

Any idea of what should I do?

Where is the implementation of ShapeMatch-Loss?

I wonder whether the backward of ShapeMatch-Loss and PointMatch-Loss is the same.

Some toy, simple dataset

Work with 256 gb dataset is very, very inconvenient. It will be so great to have some toy, small dataset. Maybe 3d generated. Maybe someone has such kind of dataset that is able to work with PoseCNN?

KeyError: 'unknown network: vgg16_convs'

Hi, when i run the ./experiment/script/demo.sh, i meet the error, "KeyError: 'unknown network: vgg16_convs'". i don't know why, can you help me, thanks!

tensorflow.python.framework.errors_impl.NotFoundError: undefined symbol: nlopt_destroy

Hi Yu Xiang,
I have compiled successfully all your installation steps and I run this './experiments/scripts/demo.sh $GPU_ID' . However, I get the trouble:

Traceback (most recent call last): File "./tools/demo.py", line 113, in <module> from networks.factory import get_network File "/home/quannguyen/quan/Solomon/python/Deep Learning/PoseCNN-master/tools/../lib/networks/__init__.py", line 8, in <module> from .vgg16 import vgg16 File "/home/quannguyen/quan/Solomon/python/Deep Learning/PoseCNN-master/tools/../lib/networks/vgg16.py", line 2, in <module> from networks.network import Network File "/home/quannguyen/quan/Solomon/python/Deep Learning/PoseCNN-master/tools/../lib/networks/network.py", line 17, in <module> import hough_voting_layer.hough_voting_op as hough_voting_op File "/home/quannguyen/quan/Solomon/python/Deep Learning/PoseCNN-master/tools/../lib/hough_voting_layer/hough_voting_op.py", line 5, in <module> _hough_voting_module = tf.load_op_library(filename) File "/home/quannguyen/anaconda3/envs/CV_TF_python36/lib/python3.6/site-packages/tensorflow/python/framework/load_library.py", line 56, in load_op_library lib_handle = py_tf.TF_LoadLibrary(library_filename) tensorflow.python.framework.errors_impl.NotFoundError: /home/quannguyen/quan/Solomon/python/Deep Learning/PoseCNN-master/tools/../lib/hough_voting_layer/hough_voting.cpython-36m-x86_64-linux-gnu.so: undefined symbol: nlopt_destroy

#Update:
I have fix it follow thread #1, so I close this topic, thanks.

queastion about implementation

it this the right way to add the -D_GLIBCXX_USE_CXX11_ABI=0 ?

nvcc -std=c++11 -c -o average_distance_loss_op_gpu.cu.o average_distance_loss_op_gpu.cu.cc
-I $TF_INC -D_GLIBCXX_USE_CXX11_ABI=0 -I$TF_INC/external/nsync/public -D GOOGLE_CUDA=1 -x cu -Xcompiler -fPIC -arch=sm_50

g++ -std=c++11 -shared -o average_distance_loss.so average_distance_loss_op.cc
average_distance_loss_op_gpu.cu.o -I $TF_INC -D_GLIBCXX_USE_CXX11_ABI=0 -I$TF_INC/external/nsync/public -fPIC -lcudart -L$CUDA_PATH/lib64 -L$TF_LIB -ltensorflow_framework

error while running "python3 setup.py build_ext --inplace"

When I want to run the "python3 setup.py build_ext --inplace" I get following errors:

running build_ext
skipping 'normals/gpu_normals.cpp' Cython extension (up-to-date)
building 'normals.gpu_normals' extension
/usr/local/cuda-9.2/bin/nvcc -I/home/mgh/.local/lib/python3.5/site-packages/numpy/core/include -I/usr/local/cuda-9.2/include -I/usr/local/include/eigen3 -I/usr/include/python3.5m -c normals/compute_normals.cu -o build/temp.linux-x86_64-3.5/normals/compute_normals.o -arch=sm_35 --ptxas-options=-v -c --compiler-options '-fPIC'
/usr/local/include/eigen3/Eigen/src/Core/MathFunctions.h(1067): warning: calling a host function from a host device function is not allowed

/usr/local/include/eigen3/Eigen/src/Core/MathFunctions.h(1067): warning: calling a host function from a host device function is not allowed

/usr/local/include/eigen3/Eigen/src/Core/MathFunctions.h(1072): warning: calling a host function from a host device function is not allowed

/usr/local/include/eigen3/Eigen/src/Core/arch/CUDA/Half.h(241): warning: calling a host function from a host device function is not allowed

/usr/local/include/eigen3/Eigen/src/Core/arch/CUDA/Half.h(244): warning: calling a host function from a host device function is not allowed

/usr/local/include/eigen3/Eigen/src/Core/arch/CUDA/Half.h(285): error: no suitable user-defined conversion from "__half" to "Eigen::half_impl::__half" exists

/usr/local/include/eigen3/Eigen/src/Core/arch/CUDA/Half.h(340): error: no suitable user-defined conversion from "Eigen::half_impl::__half" to "__half" exists

/usr/local/include/eigen3/Eigen/src/Core/arch/CUDA/Half.h(432): error: no suitable user-defined conversion from "const Eigen::half" to "__half" exists

/usr/local/include/eigen3/Eigen/src/Core/arch/CUDA/Half.h(439): error: no suitable user-defined conversion from "const Eigen::half" to "__half" exists

/usr/local/include/eigen3/Eigen/src/Core/arch/CUDA/Half.h(612): warning: function "__shfl_xor(float, int, int)"
/usr/local/cuda-9.2/include/sm_30_intrinsics.hpp(294): here was declared deprecated ("__shfl_xor() is deprecated in favor of __shfl_xor_sync() and may be removed in a future release (Use -Wno-deprecated-declarations to suppress this warning).")

/usr/local/include/eigen3/Eigen/src/Core/arch/CUDA/PacketMathHalf.h(45): error: no suitable user-defined conversion from "const Eigen::half" to "__half" exists

/usr/local/include/eigen3/Eigen/src/Core/arch/CUDA/PacketMathHalf.h(53): error: no suitable user-defined conversion from "const Eigen::half" to "__half" exists

/usr/local/include/eigen3/Eigen/src/Core/arch/CUDA/PacketMathHalf.h(57): error: no suitable user-defined conversion from "const Eigen::half" to "__half" exists

/usr/local/include/eigen3/Eigen/src/Core/arch/CUDA/PacketMathHalf.h(65): error: no operator "=" matches these operands
operand types are: Eigen::half = __half

/usr/local/include/eigen3/Eigen/src/Core/arch/CUDA/PacketMathHalf.h(66): error: no operator "=" matches these operands
operand types are: Eigen::half = __half

/usr/local/include/eigen3/Eigen/src/Core/arch/CUDA/PacketMathHalf.h(81): error: no suitable user-defined conversion from "Eigen::half" to "__half" exists

/usr/local/include/eigen3/Eigen/src/Core/arch/CUDA/PacketMathHalf.h(88): error: no suitable user-defined conversion from "const Eigen::half" to "__half" exists

/usr/local/include/eigen3/Eigen/src/Core/arch/CUDA/PacketMathHalf.h(92): error: no operator "=" matches these operands
operand types are: Eigen::half = __half

/usr/local/include/eigen3/Eigen/src/Core/arch/CUDA/PacketMathHalf.h(93): error: no operator "=" matches these operands
operand types are: Eigen::half = __half

/usr/local/include/eigen3/Eigen/src/Core/arch/CUDA/PacketMathHalf.h(97): error: no suitable user-defined conversion from "__half" to "Eigen::half" exists

/usr/local/include/eigen3/Eigen/src/Core/arch/CUDA/PacketMathHalf.h(102): error: more than one conversion function from "const __half" to a built-in type applies:
function "__half::operator short() const"
function "__half::operator unsigned short() const"
function "__half::operator int() const"
function "__half::operator unsigned int() const"
function "__half::operator long long() const"
function "__half::operator unsigned long long() const"
function "__half::operator __nv_bool() const"

/usr/local/include/eigen3/Eigen/src/Core/arch/CUDA/PacketMathHalf.h(121): error: no suitable user-defined conversion from "const Eigen::half" to "__half" exists

/usr/local/include/eigen3/Eigen/src/Core/arch/CUDA/PacketMathHalf.h(122): error: no suitable user-defined conversion from "const Eigen::half" to "__half" exists

/usr/local/include/eigen3/Eigen/src/Core/arch/CUDA/PacketMathHalf.h(244): error: no suitable user-defined conversion from "__half" to "Eigen::half" exists

/usr/local/include/eigen3/Eigen/src/Core/arch/CUDA/PacketMathHalf.h(256): error: no suitable user-defined conversion from "__half" to "Eigen::half" exists

/usr/local/include/eigen3/Eigen/src/Core/arch/CUDA/TypeCasting.h(23): error: no suitable user-defined conversion from "__half" to "Eigen::half" exists

/usr/local/include/eigen3/Eigen/src/Core/arch/CUDA/TypeCasting.h(41): error: no suitable user-defined conversion from "__half" to "Eigen::half" exists

/usr/local/include/eigen3/Eigen/src/Core/arch/CUDA/TypeCasting.h(59): error: no suitable user-defined conversion from "const Eigen::half" to "__half" exists

26 errors detected in the compilation of "/tmp/tmpxft_00002061_00000000-6_compute_normals.cpp1.ii".
error: command '/usr/local/cuda-9.2/bin/nvcc' failed with exit status 1

where is file 'extents.txt'

I download the dataset YCB_Video_Dataset, but I cant find 'extents.txt', where is it?

Video Format

Hi @yuxng ,
I'd like to test the pre-trained model on my own recorded video (which also contains YCB-Object). Could you precise the format of the video you're providing so I can test it on my own sequences ?
(since the .zip file you're providing would take me 24 hours, so I can't tell the format form it)
Thank you

how to understand the result of demo?

how to understand the result of demo? when I run the demo.sh, I get the result as follows. what's the meaning of the 3*4 matrix? Is there any other graph result？

``data/demo_images/000001-color.png
[0, 4, 2, 3, 1]
[[ 0. 2. 283.5 133.2 514.5 392.8 1870. ]
[ 0. 15. 38.4 233.8 337.6 370.2 1217. ]
[ 0. 5. 317.8 240.3 410.2 431.7 1192. ]
[ 0. 10. 95.6 306.8 280.4 487.2 844. ]
[ 0. 4. 372.4 250.9 473.6 363.1 630. ]]
im_segment: 0/5 2.584s 0.000s
/home/l00404262/pose-cnn/posecnn/output/images/vgg16_fcn_color_single_frame_2d_pose_add_lov_iter_160000/mat/000000.mat
003_cracker_box
[[ 0.6422991 0.11825264 0.75727683 0.08245494]
[ 0.2812132 0.8827622 -0.37636426 0.02077807]
[-0.71300143 0.45469466 0.53374314 1.022648 ]]

035_power_drill
[[-0.36496866 0.9297555 -0.04850226 -0.11761715]
[-0.22443092 -0.03730001 0.9737758 0.05707268]
[ 0.90356433 0.36628312 0.22227931 1.0038762 ]]

006_mustard_bottle
[[-0.27254885 -0.9612891 0.04050098 0.04041607]
[-0.52675986 0.11385927 -0.8423539 0.07496937]
[ 0.80513424 -0.2509169 -0.5374007 0.8451747 ]]

011_banana
[[ 0.7152798 -0.65476066 -0.24426067 -0.09588137]
[-0.47088557 -0.19330123 -0.86075634 0.11935466]
[ 0.5163735 0.73070043 -0.4465818 0.8183588 ]]

005_tomato_soup_can
[[-0.24271648 -0.96719044 0.07504287 0.09861922]
[-0.48978522 0.05540327 -0.870081 0.05884667]
[ 0.8373764 -0.24793784 -0.48716292 0.9562935 ]]

data/demo_images/000005-color.png
[3, 1, 2, 0, 4]
[[ 0. 15. 222.9 108.7 445.1 335.3 1785. ]
[ 0. 3. 188.6 304.3 373.4 451.7 1764. ]
[ 0. 12. 102.7 98.2 241.3 291.8 1745. ]
[ 0. 2. 87.8 26. 312.2 290. 1697. ]
[ 0. 19. 341.7 244.6 502.3 407.4 927. ]]
im_segment: 4/5 0.256s 0.000s
/home/l00404262/pose-cnn/posecnn/output/images/vgg16_fcn_color_single_frame_2d_pose_add_lov_iter_160000/mat/000004.mat
035_power_drill
[[-0.79307353 0.03152163 0.6083097 0.01757701]
[-0.2863282 -0.9007414 -0.3266206 -0.01614243]
[ 0.53763413 -0.4332104 0.7233798 0.89233726]]

004_sugar_box
[[-0.05908491 -0.15062854 0.9868232 -0.0249941 ]
[-0.88968515 0.45628068 0.01637772 0.10673593]
[-0.4527353 -0.8769943 -0.16097128 0.83356476]]

021_bleach_cleanser
[[-0.9080525 -0.4185388 -0.01629667 -0.12675728]
[-0.2248048 0.5198222 -0.8241648 -0.04160914]
[ 0.35341638 -0.7447215 -0.5661153 0.95910937]]

003_cracker_box
[[-0.27735838 0.9571752 0.08299295 -0.10655584]
[ 0.50783616 0.21938507 -0.83305013 -0.07851676]
[-0.8155824 -0.18890665 -0.54693645 1.0060583 ]]

051_large_clamp
[[ 0.98945546 -0.14415832 -0.01401017 0.09840345]
[-0.09128212 -0.54556674 -0.8330814 0.076396 ]
[ 0.11245212 0.8255758 -0.5529731 0.9629544 ]]

data/demo_images/000004-color.png
[2, 0, 1]
[[ 0. 11. 221. 75.9 463. 342.1 3526. ]
[ 0. 5. 332.8 249.9 447.2 428.1 1270. ]
[ 0. 6. 213.8 303.3 328.2 428.7 814. ]]
im_segment: 3/5 0.221s 0.000s
/home/l00404262/pose-cnn/posecnn/output/images/vgg16_fcn_color_single_frame_2d_pose_add_lov_iter_160000/mat/000003.mat
019_pitcher_base
[[ 0.57848835 0.8078584 0.11276557 0.02698041]
[ 0.57146865 -0.30274802 -0.7627366 -0.03002721]
[-0.58204365 0.5056762 -0.63680196 0.9920388 ]]

006_mustard_bottle
[[ 0.68264264 0.71917355 0.12957029 0.06465604]
[ 0.52466255 -0.3589347 -0.77194256 0.08196001]
[-0.50865334 0.5949416 -0.6223476 0.8956092 ]]

007_tuna_fish_can
[[-0.4215358 -0.5414055 0.7274529 -0.0353383 ]
[-0.90422386 0.31152016 -0.29212058 0.10487492]
[-0.06846057 -0.7809195 -0.6208687 0.8978541 ]]

data/demo_images/000002-color.png
[1, 3, 0, 2, 4]
[[0.000e+00 3.000e+00 1.825e+02 2.725e+02 3.475e+02 4.375e+02 1.573e+03]
[0.000e+00 1.200e+01 2.132e+02 8.910e+01 3.188e+02 2.629e+02 1.375e+03]
[0.000e+00 1.000e+00 2.912e+02 1.539e+02 4.188e+02 3.101e+02 1.304e+03]
[0.000e+00 4.000e+00 3.704e+02 2.414e+02 4.936e+02 3.646e+02 8.610e+02]
[0.000e+00 1.700e+01 6.320e+01 3.210e+02 2.128e+02 3.870e+02 4.470e+02]]
im_segment: 1/5 0.225s 0.000s
/home/l00404262/pose-cnn/posecnn/output/images/vgg16_fcn_color_single_frame_2d_pose_add_lov_iter_160000/mat/000001.mat
004_sugar_box
[[-0.15976454 0.9531169 -0.25698918 -0.04170658]
[-0.77241707 -0.2828072 -0.5686756 0.09874432]
[-0.6146927 0.10764863 0.7813864 0.9271626 ]]

021_bleach_cleanser
[[ 0.889594 -0.4554014 -0.0351006 -0.04652733]
[-0.19150709 -0.30211905 -0.93383586 -0.06462913]
[ 0.41466552 0.8374568 -0.3559759 1.0563438 ]]

002_master_chef_can
[[ 0.73876274 -0.6727802 0.03995484 0.0403282 ]
[-0.30980563 -0.39164263 -0.8663928 -0.00893156]
[ 0.59854 0.6276805 -0.49776208 1.0239959 ]]

005_tomato_soup_can
[[-0.4866409 -0.3669129 -0.792815 0.09678001]
[ 0.76156765 -0.62281054 -0.1792256 0.05013151]
[-0.42801332 -0.69100076 0.582514 0.86749095]]

037_scissors
[[ 0.21864083 0.9612652 -0.16782571 -0.14670825]
[ 0.4488678 0.05363503 0.89198714 0.09441528]
[ 0.8664375 -0.2703564 -0.4197542 0.89438194]]

data/demo_images/000003-color.png
[2, 1, 0]
[[ 0. 13. 298.5 244.1 551.5 483.9 2656. ]
[ 0. 9. 136.8 211.6 295.2 374.4 1019. ]
[ 0. 4. 174. 302.8 284. 439.2 971. ]]
im_segment: 2/5 0.230s 0.000s
/home/l00404262/pose-cnn/posecnn/output/images/vgg16_fcn_color_single_frame_2d_pose_add_lov_iter_160000/mat/000002.mat
024_bowl
[[ 0.94938517 0.29547584 0.10659184 0.08527517]
[ 0.22814123 -0.41536832 -0.8805798 0.09334073]
[-0.21591519 0.8603274 -0.46175474 0.81213427]]

010_potted_meat_can
[[-0.96951807 0.24496381 0.00523676 -0.08112083]
[ 0.15087484 0.61370015 -0.7749896 0.04320456]
[-0.19305821 -0.7505764 -0.6319522 0.8922638 ]]

005_tomato_soup_can
[[-0.1556726 -0.98779947 -0.00426031 -0.06283883]
[-0.71000516 0.11489002 -0.69476104 0.09696867]
[ 0.6867741 -0.10513044 -0.7192279 0.7981611 ]]

42.40user 6.38system 0:12.40elapsed 393%CPU (0avgtext+0avgdata 3729156maxresident)k
0inputs+64outputs (0major+956187minor)pagefaults 0swaps

Running the demo.sh: "Error in `python': free(): invalid next size (fast)"

Hi all, I got the following error when I tried to run the demo.sh:

Error in `python': free(): invalid next size (fast)

Has anyone encountered the same problem / What could be the solution?
Here's the full output:

/local/data/PoseCNN$ ./experiments/scripts/demo.sh 0
+ set -e
+ export PYTHONUNBUFFERED=True
+ PYTHONUNBUFFERED=True
+ export CUDA_VISIBLE_DEVICES=0
+ CUDA_VISIBLE_DEVICES=0
+ ./tools/demo.py --gpu 0 --network vgg16_convs --model data/demo_models/vgg16_fcn_color_single_frame_2d_pose_add_lov_iter_80000.ckpt --imdb lov_keyframe --cfg experiments/cfgs/lov_color_2d.yml
registered Poly3
registered Poly3
registered Linear
registered Linear
shapenet_scene_train
shapenet_scene_val
shapenet_single_train
shapenet_single_val
gmu_scene_train
gmu_scene_val
rgbd_scene_train
rgbd_scene_val
rgbd_scene_trainval
lov_train
lov_val
lov_keyframe
lov_trainval
lov_debug
lov_train_few
lov_val_few
lov_single_002_master_chef_can_train
lov_single_003_cracker_box_train
lov_single_004_sugar_box_train
lov_single_005_tomato_soup_can_train
lov_single_006_mustard_bottle_train
lov_single_007_tuna_fish_can_train
lov_single_008_pudding_box_train
lov_single_009_gelatin_box_train
lov_single_010_potted_meat_can_train
lov_single_011_banana_train
lov_single_019_pitcher_base_train
lov_single_021_bleach_cleanser_train
lov_single_024_bowl_train
lov_single_025_mug_train
lov_single_035_power_drill_train
lov_single_036_wood_block_train
lov_single_037_scissors_train
lov_single_040_large_marker_train
lov_single_051_large_clamp_train
lov_single_052_extra_large_clamp_train
lov_single_061_foam_brick_train
ycb_trainval
yumi_train
linemod_ape_train
linemod_ape_test
linemod_ape_train_few
linemod_ape_test_few
linemod_benchvise_train
linemod_benchvise_test
linemod_benchvise_train_few
linemod_benchvise_test_few
linemod_bowl_train
linemod_bowl_test
linemod_bowl_train_few
linemod_bowl_test_few
linemod_camera_train
linemod_camera_test
linemod_camera_train_few
linemod_camera_test_few
linemod_can_train
linemod_can_test
linemod_can_train_few
linemod_can_test_few
linemod_cat_train
linemod_cat_test
linemod_cat_train_few
linemod_cat_test_few
linemod_cup_train
linemod_cup_test
linemod_cup_train_few
linemod_cup_test_few
linemod_driller_train
linemod_driller_test
linemod_driller_train_few
linemod_driller_test_few
linemod_duck_train
linemod_duck_test
linemod_duck_train_few
linemod_duck_test_few
linemod_eggbox_train
linemod_eggbox_test
linemod_eggbox_train_few
linemod_eggbox_test_few
linemod_glue_train
linemod_glue_test
linemod_glue_train_few
linemod_glue_test_few
linemod_holepuncher_train
linemod_holepuncher_test
linemod_holepuncher_train_few
linemod_holepuncher_test_few
linemod_iron_train
linemod_iron_test
linemod_iron_train_few
linemod_iron_test_few
linemod_lamp_train
linemod_lamp_test
linemod_lamp_train_few
linemod_lamp_test_few
linemod_phone_train
linemod_phone_test
linemod_phone_train_few
linemod_phone_test_few
Called with args:
Namespace(background_name=None, cad_name=None, cfg_file='experiments/cfgs/lov_color_2d.yml', gpu_id=0, imdb_name='lov_keyframe', kfusion=False, model='data/demo_models/vgg16_fcn_color_single_frame_2d_pose_add_lov_iter_80000.ckpt', network_name='vgg16_convs', pose_name=None, pretrained_model=None, rig_name=None, wait=True)
Using config:
{'ANCHOR_RATIOS': [0.5, 1, 2],
 'ANCHOR_SCALES': [8, 16, 32],
 'BACKGROUND': '',
 'CAD': '',
 'EPS': 1e-14,
 'EXP_DIR': 'lov',
 'FEATURE_STRIDE': 16,
 'FLIP_X': False,
 'GPU_ID': 0,
 'INPUT': 'COLOR',
 'NETWORK': 'VGG16',
 'PIXEL_MEANS': array([[[102.9801, 115.9465, 122.7717]]]),
 'POSE': '',
 'RIG': '',
 'RNG_SEED': 3,
 'ROOT_DIR': '/local/data/PoseCNN',
 'TEST': {'BBOX_REG': True,
          'GAN': False,
          'GRID_SIZE': 256,
          'NMS': 0.3,
          'POSE_REFINE': False,
          'POSE_REG': True,
          'RANSAC': False,
          'RPN_NMS_THRESH': 0.7,
          'RPN_POST_NMS_TOP_N': 300,
          'RPN_PRE_NMS_TOP_N': 6000,
          'SCALES_BASE': [1.0],
          'SEGMENTATION': True,
          'SINGLE_FRAME': True,
          'SYNTHETIC': False,
          'VERTEX_REG_2D': True,
          'VERTEX_REG_3D': False,
          'VISUALIZE': True},
 'TRAIN': {'ADAPT': False,
           'ADAPT_NUM': 400,
           'ADAPT_RATIO': 1,
           'ADAPT_ROOT': '',
           'ADAPT_WEIGHT': 0.1,
           'ADD_NOISE': False,
           'BATCH_SIZE': 128,
           'BBOX_INSIDE_WEIGHTS': [1.0, 1.0, 1.0, 1.0],
           'BBOX_NORMALIZE_MEANS': [0.0, 0.0, 0.0, 0.0],
           'BBOX_NORMALIZE_STDS': [0.1, 0.1, 0.2, 0.2],
           'BBOX_NORMALIZE_TARGETS': True,
           'BBOX_NORMALIZE_TARGETS_PRECOMPUTED': True,
           'BG_THRESH_HI': 0.5,
           'BG_THRESH_LO': 0.1,
           'CHROMATIC': True,
           'DISPLAY': 20,
           'FG_FRACTION': 0.25,
           'FG_THRESH': 0.5,
           'GAMMA': 0.1,
           'GAN': False,
           'GRID_SIZE': 256,
           'HAS_RPN': True,
           'IMS_PER_BATCH': 2,
           'LEARNING_RATE': 0.001,
           'MATCHING': False,
           'MOMENTUM': 0.9,
           'NUM_CLASSES': 22,
           'NUM_STEPS': 5,
           'NUM_UNITS': 64,
           'OPTIMIZER': 'MOMENTUM',
           'POSE_REG': True,
           'POSE_W': 1.0,
           'RPN_BATCHSIZE': 256,
           'RPN_BBOX_INSIDE_WEIGHTS': [1.0, 1.0, 1.0, 1.0],
           'RPN_CLOBBER_POSITIVES': False,
           'RPN_FG_FRACTION': 0.5,
           'RPN_NEGATIVE_OVERLAP': 0.3,
           'RPN_NMS_THRESH': 0.7,
           'RPN_POSITIVE_OVERLAP': 0.7,
           'RPN_POSITIVE_WEIGHT': -1.0,
           'RPN_POST_NMS_TOP_N': 2000,
           'RPN_PRE_NMS_TOP_N': 12000,
           'SCALES_BASE': [1.0],
           'SEGMENTATION': True,
           'SINGLE_FRAME': True,
           'SNAPSHOT_INFIX': 'lov',
           'SNAPSHOT_ITERS': 10000,
           'SNAPSHOT_PREFIX': 'vgg16_fcn_color_single_frame_2d_pose_add',
           'STEPSIZE': 60000,
           'SYNITER': 0,
           'SYNNUM': 80000,
           'SYNROOT': 'data/LOV/data_syn/',
           'SYNTHESIZE': True,
           'SYN_HEIGHT': 480,
           'SYN_ONLINE': False,
           'SYN_RATIO': 10,
           'SYN_WIDTH': 640,
           'TRAINABLE': True,
           'USE_FLIPPED': False,
           'USE_GT': False,
           'VERTEX_REG_2D': True,
           'VERTEX_REG_3D': False,
           'VERTEX_W': 1.0,
           'VISUALIZE': False,
           'WEIGHT_REG': 0.0001},
 'USE_GPU_NMS': True}
/local/data/PoseCNN/tools/../lib/datasets/../../data/LOV/models/002_master_chef_can/points.xyz
/local/data/PoseCNN/tools/../lib/datasets/../../data/LOV/models/003_cracker_box/points.xyz
/local/data/PoseCNN/tools/../lib/datasets/../../data/LOV/models/004_sugar_box/points.xyz
/local/data/PoseCNN/tools/../lib/datasets/../../data/LOV/models/005_tomato_soup_can/points.xyz
/local/data/PoseCNN/tools/../lib/datasets/../../data/LOV/models/006_mustard_bottle/points.xyz
/local/data/PoseCNN/tools/../lib/datasets/../../data/LOV/models/007_tuna_fish_can/points.xyz
/local/data/PoseCNN/tools/../lib/datasets/../../data/LOV/models/008_pudding_box/points.xyz
/local/data/PoseCNN/tools/../lib/datasets/../../data/LOV/models/009_gelatin_box/points.xyz
/local/data/PoseCNN/tools/../lib/datasets/../../data/LOV/models/010_potted_meat_can/points.xyz
/local/data/PoseCNN/tools/../lib/datasets/../../data/LOV/models/011_banana/points.xyz
/local/data/PoseCNN/tools/../lib/datasets/../../data/LOV/models/019_pitcher_base/points.xyz
/local/data/PoseCNN/tools/../lib/datasets/../../data/LOV/models/021_bleach_cleanser/points.xyz
/local/data/PoseCNN/tools/../lib/datasets/../../data/LOV/models/024_bowl/points.xyz
/local/data/PoseCNN/tools/../lib/datasets/../../data/LOV/models/025_mug/points.xyz
/local/data/PoseCNN/tools/../lib/datasets/../../data/LOV/models/035_power_drill/points.xyz
/local/data/PoseCNN/tools/../lib/datasets/../../data/LOV/models/036_wood_block/points.xyz
/local/data/PoseCNN/tools/../lib/datasets/../../data/LOV/models/037_scissors/points.xyz
/local/data/PoseCNN/tools/../lib/datasets/../../data/LOV/models/040_large_marker/points.xyz
/local/data/PoseCNN/tools/../lib/datasets/../../data/LOV/models/051_large_clamp/points.xyz
/local/data/PoseCNN/tools/../lib/datasets/../../data/LOV/models/052_extra_large_clamp/points.xyz
/local/data/PoseCNN/tools/../lib/datasets/../../data/LOV/models/061_foam_brick/points.xyz
data/demo_images/000001-color.png
data/demo_images/000001-depth.png
data/demo_images/000002-color.png
data/demo_images/000002-depth.png
data/demo_images/000003-color.png
data/demo_images/000003-depth.png
data/demo_images/000004-color.png
data/demo_images/000004-depth.png
data/demo_images/000005-color.png
data/demo_images/000005-depth.png
{'intrinsic_matrix': array([[1.066778e+03, 0.000000e+00, 3.129869e+02],
       [0.000000e+00, 1.067487e+03, 2.413109e+02],
       [0.000000e+00, 0.000000e+00, 1.000000e+00]]), 'factor_depth': 10000.0}
/gpu:0
/usr/local/lib/python2.7/dist-packages/h5py/__init__.py:36: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.
  from ._conv import register_converters as _register_converters
/local/data/PoseCNN/tools/../lib/backprojecting_layer/backprojecting.so
*** Error in `python': free(): invalid next size (fast): 0x0000000003654470 ***
======= Backtrace: =========
/lib/x86_64-linux-gnu/libc.so.6(+0x777e5)[0x7f93684207e5]
/lib/x86_64-linux-gnu/libc.so.6(+0x8037a)[0x7f936842937a]
/lib/x86_64-linux-gnu/libc.so.6(cfree+0x4c)[0x7f936842d53c]
/usr/local/lib/python2.7/dist-packages/tensorflow/libtensorflow_framework.so(+0x351d1f)[0x7f92838c9d1f]
/lib64/ld-linux-x86-64.so.2(+0x106ba)[0x7f93689a06ba]
/lib64/ld-linux-x86-64.so.2(+0x107cb)[0x7f93689a07cb]
/lib64/ld-linux-x86-64.so.2(+0x158e2)[0x7f93689a58e2]
/lib64/ld-linux-x86-64.so.2(+0x10564)[0x7f93689a0564]
/lib64/ld-linux-x86-64.so.2(+0x14da9)[0x7f93689a4da9]
/lib/x86_64-linux-gnu/libdl.so.2(+0xf09)[0x7f93681a5f09]
/lib64/ld-linux-x86-64.so.2(+0x10564)[0x7f93689a0564]
/lib/x86_64-linux-gnu/libdl.so.2(+0x1571)[0x7f93681a6571]
/lib/x86_64-linux-gnu/libdl.so.2(dlopen+0x31)[0x7f93681a5fa1]
/usr/local/lib/python2.7/dist-packages/tensorflow/python/_pywrap_tensorflow_internal.so(_ZN10tensorflow8internal11LoadLibraryEPKcPPv+0x1a)[0x7f92b8cd638a]
/usr/local/lib/python2.7/dist-packages/tensorflow/python/_pywrap_tensorflow_internal.so(+0x3731617)[0x7f92b8cd5617]
/usr/local/lib/python2.7/dist-packages/tensorflow/python/_pywrap_tensorflow_internal.so(_ZN10tensorflow11LoadLibraryEPKcPPvPPKvPm+0x603)[0x7f92b8ba1f33]
/usr/local/lib/python2.7/dist-packages/tensorflow/python/_pywrap_tensorflow_internal.so(TF_LoadLibrary+0x37)[0x7f92b6875147]
/usr/local/lib/python2.7/dist-packages/tensorflow/python/_pywrap_tensorflow_internal.so(+0x10f9eda)[0x7f92b669deda]
python(PyEval_EvalFrameEx+0x5ca)[0x4bc3fa]
python(PyEval_EvalCodeEx+0x306)[0x4b9ab6]
python(PyEval_EvalFrameEx+0x603f)[0x4c1e6f]
python(PyEval_EvalCodeEx+0x306)[0x4b9ab6]
python(PyEval_EvalCode+0x16)[0x4b97a6]
python(PyImport_ExecCodeModuleEx+0xbf)[0x4b96df]
python[0x4b2b06]
python[0x4a4ae1]
python(PyImport_ImportModuleLevel+0x8d3)[0x4a4513]
python[0x4a59e4]
python(PyObject_Call+0x3e)[0x4a577e]
python(PyEval_CallObjectWithKeywords+0x30)[0x4c5e10]
python(PyEval_EvalFrameEx+0x28a7)[0x4be6d7]
python(PyEval_EvalCodeEx+0x306)[0x4b9ab6]
python(PyEval_EvalCode+0x16)[0x4b97a6]
python(PyImport_ExecCodeModuleEx+0xbf)[0x4b96df]
python[0x4b2b06]
python[0x4a4ae1]
python(PyImport_ImportModuleLevel+0x8d3)[0x4a4513]
python[0x4a59e4]
python(PyObject_Call+0x3e)[0x4a577e]
python(PyEval_CallObjectWithKeywords+0x30)[0x4c5e10]
python(PyEval_EvalFrameEx+0x28a7)[0x4be6d7]
python(PyEval_EvalCodeEx+0x306)[0x4b9ab6]
python(PyEval_EvalCode+0x16)[0x4b97a6]
python(PyImport_ExecCodeModuleEx+0xbf)[0x4b96df]
python[0x4b2b06]
python[0x4a4ae1]
python(PyImport_ImportModuleLevel+0x689)[0x4a42c9]
python[0x4a59e4]
python(PyObject_Call+0x3e)[0x4a577e]
python(PyEval_CallObjectWithKeywords+0x30)[0x4c5e10]
python(PyEval_EvalFrameEx+0x28a7)[0x4be6d7]
python(PyEval_EvalCodeEx+0x306)[0x4b9ab6]
python(PyEval_EvalCode+0x16)[0x4b97a6]
python(PyImport_ExecCodeModuleEx+0xbf)[0x4b96df]
python[0x4b2b06]
python[0x4b402c]
python[0x4a4ae1]
python(PyImport_ImportModuleLevel+0x689)[0x4a42c9]
python[0x4a59e4]
python(PyObject_Call+0x3e)[0x4a577e]
python(PyEval_CallObjectWithKeywords+0x30)[0x4c5e10]
python(PyEval_EvalFrameEx+0x28a7)[0x4be6d7]
python(PyEval_EvalCodeEx+0x306)[0x4b9ab6]
======= Memory map: ========
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00955000-00978000 rw-p 00000000 00:00 0 
0146b000-0427c000 rw-p 00000000 00:00 0                                  [heap]
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7f9368bb7000-7f9368bb8000 rw-p 00000000 00:00 0 
7ffdf4c85000-7ffdf4ca6000 rwxp 00000000 00:00 0                          [stack]
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ffffffffff600000-ffffffffff601000 r-xp 00000000 00:00 0                  [vsyscall]
./experiments/scripts/demo.sh: line 13: 31681 Aborted                 (core dumped) ./tools/demo.py --gpu 0 --network vgg16_convs --model data/demo_models/vgg16_fcn_color_single_frame_2d_pose_add_lov_iter_80000.ckpt --imdb lov_keyframe --cfg experiments/cfgs/lov_color_2d.yml

When loading gradient_reversal_layer.so SyntaxError: invalid syntax happens?

I'm trying to run the demo and this I get following stack trace:

Traceback (most recent call last):
  File "./tools/demo.py", line 118, in <module>
    from networks.factory import get_network
  File "/home/<username>/external_libraries_and_code/PoseCNN/tools/../lib/networks/__init__.py", line 8, in <module>
    from .vgg16 import vgg16
  File "/home/<username>/external_libraries_and_code/PoseCNN/tools/../lib/networks/vgg16.py", line 2, in <module>
    from networks.network import Network
  File "/home/<username>/external_libraries_and_code/PoseCNN/tools/../lib/networks/network.py", line 23, in <module>
    import gradient_reversal_layer.gradient_reversal_op as gradient_reversal_op
  File "/home/<username>/external_libraries_and_code/PoseCNN/tools/../lib/gradient_reversal_layer/gradient_reversal_op.py", line 6, in <module>
    _gradient_reversal_module = tf.load_op_library(filename)
  File "/home/<username>/tf/source_tf/local/lib/python2.7/site-packages/tensorflow/python/framework/load_library.py", line 73, in load_op_library
    exec(wrappers, module.__dict__)
  File "<string>", line 58
    "lambda", lambda)
                    ^
SyntaxError: invalid syntax

Any idea why this might be happening? It might have to do with the tf version, what tf version did you use, I tried 1.10.0-rc1

ImportError: libsynthesizer.so: undefined symbol: _ZN2df11backprojectIfNS

Hello,
When I ran the script:
./experiments/scripts/demo.sh $GPU_ID
I got an error as follows:

+ set -e
+ export PYTHONUNBUFFERED=True
+ PYTHONUNBUFFERED=True
+ export CUDA_VISIBLE_DEVICES=
+ CUDA_VISIBLE_DEVICES=
+ ./tools/demo.py --gpu 0 --network vgg16_convs --model data/demo_models/vgg16_fcn_color_single_frame_2d_pose_add_lov_iter_80000.ckpt --imdb lov_keyframe --cfg experiments/cfgs/lov_color_2d.yml
Traceback (most recent call last):
  File "./tools/demo.py", line 13, in <module>
    from fcn.test import test_net_images
  File "/home/ubuntu/PoseCNN/tools/../lib/fcn/test.py", line 27, in <module>
    from synthesize import synthesizer
ImportError: /home/ubuntu/PoseCNN/lib/synthesize/build/libsynthesizer.so: undefined symbol: _ZN2df11backprojectIfNS_16Poly3CameraModelEEEvRKNS_6TensorILj2ET_LNS_9ResidencyE1ELb0EEERNS2_ILj2EN5Eigen6MatrixIS3_Li3ELi1ELi2ELi3ELi1EEELS4_1ELb0EEERT0_IS3_E

When I ran
c++filt _ZN2df11backprojectIfNS_16Poly3CameraModelEEEvRKNS_6TensorILj2ET_LNS_9ResidencyE1ELb0EEERNS2_ILj2EN5Eigen6MatrixIS3_Li3ELi1ELi2ELi3ELi1EEELS4_1ELb0EEERT0_IS3_E
I got the following results:
void df::backproject<float, df::Poly3CameraModel>(df::Tensor<2u, float, (df::Residency)1, false> const&, df::Tensor<2u, Eigen::Matrix<float, 3, 1, 2, 3, 1>, (df::Residency)1, false>&, df::Poly3CameraModel<float>&)
How to solve the problem? Thank you very much for your help.

Here is my system information:

Python version: anaconda python 2.7.14
Ubuntu version: 16.04
Tensorflow version: 1.2.1, installed in conda environment
CUDA version: 8.0

In order to describe the problem which I meeted more clearly, I added some messages from the terminal before the step ./experiments/scripts/demo.sh $GPU_ID as follows:

When I went to the second step by running:

cd $ROOT/lib
sh make.sh

I got the following result:

/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/Eigen/src/Core/MathFunctions.h(1265): warning: calling a constexpr __host__ function("real") from a __host__ __device__ function("abs") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/Eigen/src/Core/MathFunctions.h(1265): warning: calling a constexpr __host__ function("imag") from a __host__ __device__ function("abs") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/Eigen/src/Core/MathFunctions.h(1265): warning: calling a constexpr __host__ function from a __host__ __device__ function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/Eigen/src/Core/MathFunctions.h(1265): warning: calling a constexpr __host__ function from a __host__ __device__ function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/Eigen/src/Core/MathFunctions.h(1270): warning: calling a constexpr __host__ function("real") from a __host__ __device__ function("abs") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/Eigen/src/Core/MathFunctions.h(1270): warning: calling a constexpr __host__ function("imag") from a __host__ __device__ function("abs") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/Eigen/src/Core/MathFunctions.h(1270): warning: calling a constexpr __host__ function from a __host__ __device__ function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/Eigen/src/Core/MathFunctions.h(1270): warning: calling a constexpr __host__ function from a __host__ __device__ function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/src/Tensor/TensorRandom.h(133): warning: calling a constexpr __host__ function from a __host__ __device__ function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/src/Tensor/TensorRandom.h(138): warning: calling a constexpr __host__ function from a __host__ __device__ function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/src/Tensor/TensorRandom.h(208): warning: calling a constexpr __host__ function from a __host__ __device__ function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/src/Tensor/TensorRandom.h(213): warning: calling a constexpr __host__ function from a __host__ __device__ function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/google/protobuf/arena_impl.h(52): warning: integer conversion resulted in a change of sign
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/google/protobuf/arena_impl.h(147): warning: integer conversion resulted in a change of sign
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/google/protobuf/arena_impl.h(52): warning: integer conversion resulted in a change of sign
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/google/protobuf/arena_impl.h(147): warning: integer conversion resulted in a change of sign
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/google/protobuf/generated_message_reflection.h(689): warning: variable "unused" was set but never used
 
average_distance_loss
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/Eigen/src/Core/MathFunctions.h(1265): warning: calling a constexpr __host__ function("real") from a __host__ __device__ function("abs") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/Eigen/src/Core/MathFunctions.h(1265): warning: calling a constexpr __host__ function("imag") from a __host__ __device__ function("abs") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/Eigen/src/Core/MathFunctions.h(1265): warning: calling a constexpr __host__ function from a __host__ __device__ function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/Eigen/src/Core/MathFunctions.h(1265): warning: calling a constexpr __host__ function from a __host__ __device__ function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/Eigen/src/Core/MathFunctions.h(1270): warning: calling a constexpr __host__ function("real") from a __host__ __device__ function("abs") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/Eigen/src/Core/MathFunctions.h(1270): warning: calling a constexpr __host__ function("imag") from a __host__ __device__ function("abs") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/Eigen/src/Core/MathFunctions.h(1270): warning: calling a constexpr __host__ function from a __host__ __device__ function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/Eigen/src/Core/MathFunctions.h(1270): warning: calling a constexpr __host__ function from a __host__ __device__ function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/src/Tensor/TensorRandom.h(133): warning: calling a constexpr __host__ function from a __host__ __device__ function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/src/Tensor/TensorRandom.h(138): warning: calling a constexpr __host__ function from a __host__ __device__ function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/src/Tensor/TensorRandom.h(208): warning: calling a constexpr __host__ function from a __host__ __device__ function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/src/Tensor/TensorRandom.h(213): warning: calling a constexpr __host__ function from a __host__ __device__ function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/google/protobuf/arena_impl.h(52): warning: integer conversion resulted in a change of sign
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/google/protobuf/arena_impl.h(147): warning: integer conversion resulted in a change of sign
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/google/protobuf/arena_impl.h(52): warning: integer conversion resulted in a change of sign
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/google/protobuf/arena_impl.h(147): warning: integer conversion resulted in a change of sign
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/google/protobuf/generated_message_reflection.h(689): warning: variable "unused" was set but never used
 
hough_voting_gpu_layer
hough_voting_layer
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/MathFunctions.h(1265): warning: calling a constexpr __host__ function("real") from a __host__ __device__ function("abs") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/MathFunctions.h(1265): warning: calling a constexpr __host__ function("imag") from a __host__ __device__ function("abs") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/MathFunctions.h(1265): warning: calling a constexpr __host__ function from a __host__ __device__ function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/MathFunctions.h(1265): warning: calling a constexpr __host__ function from a __host__ __device__ function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/MathFunctions.h(1270): warning: calling a constexpr __host__ function("real") from a __host__ __device__ function("abs") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/MathFunctions.h(1270): warning: calling a constexpr __host__ function("imag") from a __host__ __device__ function("abs") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/MathFunctions.h(1270): warning: calling a constexpr __host__ function from a __host__ __device__ function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/MathFunctions.h(1270): warning: calling a constexpr __host__ function from a __host__ __device__ function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/src/Tensor/TensorRandom.h(133): warning: calling a constexpr __host__ function from a __host__ __device__ function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/src/Tensor/TensorRandom.h(138): warning: calling a constexpr __host__ function from a __host__ __device__ function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/src/Tensor/TensorRandom.h(208): warning: calling a constexpr __host__ function from a __host__ __device__ function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/src/Tensor/TensorRandom.h(213): warning: calling a constexpr __host__ function from a __host__ __device__ function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
roi_pooling_layer
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/MathFunctions.h(1265): warning: calling a constexpr __host__ function("real") from a __host__ __device__ function("abs") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/MathFunctions.h(1265): warning: calling a constexpr __host__ function("imag") from a __host__ __device__ function("abs") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/MathFunctions.h(1265): warning: calling a constexpr __host__ function from a __host__ __device__ function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/MathFunctions.h(1265): warning: calling a constexpr __host__ function from a __host__ __device__ function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/MathFunctions.h(1270): warning: calling a constexpr __host__ function("real") from a __host__ __device__ function("abs") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/MathFunctions.h(1270): warning: calling a constexpr __host__ function("imag") from a __host__ __device__ function("abs") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/MathFunctions.h(1270): warning: calling a constexpr __host__ function from a __host__ __device__ function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/MathFunctions.h(1270): warning: calling a constexpr __host__ function from a __host__ __device__ function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/src/Tensor/TensorRandom.h(133): warning: calling a constexpr __host__ function from a __host__ __device__ function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/src/Tensor/TensorRandom.h(138): warning: calling a constexpr __host__ function from a __host__ __device__ function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/src/Tensor/TensorRandom.h(208): warning: calling a constexpr __host__ function from a __host__ __device__ function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/src/Tensor/TensorRandom.h(213): warning: calling a constexpr __host__ function from a __host__ __device__ function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
build triplet loss
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/MathFunctions.h(1265): warning: calling a constexpr __host__ function("real") from a __host__ __device__ function("abs") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/MathFunctions.h(1265): warning: calling a constexpr __host__ function("imag") from a __host__ __device__ function("abs") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/MathFunctions.h(1265): warning: calling a constexpr __host__ function from a __host__ __device__ function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/MathFunctions.h(1265): warning: calling a constexpr __host__ function from a __host__ __device__ function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/MathFunctions.h(1270): warning: calling a constexpr __host__ function("real") from a __host__ __device__ function("abs") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/MathFunctions.h(1270): warning: calling a constexpr __host__ function("imag") from a __host__ __device__ function("abs") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/MathFunctions.h(1270): warning: calling a constexpr __host__ function from a __host__ __device__ function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/MathFunctions.h(1270): warning: calling a constexpr __host__ function from a __host__ __device__ function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/src/Tensor/TensorRandom.h(133): warning: calling a constexpr __host__ function from a __host__ __device__ function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/src/Tensor/TensorRandom.h(138): warning: calling a constexpr __host__ function from a __host__ __device__ function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/src/Tensor/TensorRandom.h(208): warning: calling a constexpr __host__ function from a __host__ __device__ function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/src/Tensor/TensorRandom.h(213): warning: calling a constexpr __host__ function from a __host__ __device__ function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
build lifted structured loss
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/MathFunctions.h(1265): warning: calling a constexpr __host__ function("real") from a __host__ __device__ function("abs") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/MathFunctions.h(1265): warning: calling a constexpr __host__ function("imag") from a __host__ __device__ function("abs") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/MathFunctions.h(1265): warning: calling a constexpr __host__ function from a __host__ __device__ function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/MathFunctions.h(1265): warning: calling a constexpr __host__ function from a __host__ __device__ function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/MathFunctions.h(1270): warning: calling a constexpr __host__ function("real") from a __host__ __device__ function("abs") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/MathFunctions.h(1270): warning: calling a constexpr __host__ function("imag") from a __host__ __device__ function("abs") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/MathFunctions.h(1270): warning: calling a constexpr __host__ function from a __host__ __device__ function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/MathFunctions.h(1270): warning: calling a constexpr __host__ function from a __host__ __device__ function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/src/Tensor/TensorRandom.h(133): warning: calling a constexpr __host__ function from a __host__ __device__ function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/src/Tensor/TensorRandom.h(138): warning: calling a constexpr __host__ function from a __host__ __device__ function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/src/Tensor/TensorRandom.h(208): warning: calling a constexpr __host__ function from a __host__ __device__ function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/src/Tensor/TensorRandom.h(213): warning: calling a constexpr __host__ function from a __host__ __device__ function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
build computing flow layer
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/MathFunctions.h(1265): warning: calling a constexpr __host__ function("real") from a __host__ __device__ function("abs") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/MathFunctions.h(1265): warning: calling a constexpr __host__ function("imag") from a __host__ __device__ function("abs") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/MathFunctions.h(1265): warning: calling a constexpr __host__ function from a __host__ __device__ function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/MathFunctions.h(1265): warning: calling a constexpr __host__ function from a __host__ __device__ function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/MathFunctions.h(1270): warning: calling a constexpr __host__ function("real") from a __host__ __device__ function("abs") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/MathFunctions.h(1270): warning: calling a constexpr __host__ function("imag") from a __host__ __device__ function("abs") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/MathFunctions.h(1270): warning: calling a constexpr __host__ function from a __host__ __device__ function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/MathFunctions.h(1270): warning: calling a constexpr __host__ function from a __host__ __device__ function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/src/Tensor/TensorRandom.h(133): warning: calling a constexpr __host__ function from a __host__ __device__ function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/src/Tensor/TensorRandom.h(138): warning: calling a constexpr __host__ function from a __host__ __device__ function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/src/Tensor/TensorRandom.h(208): warning: calling a constexpr __host__ function from a __host__ __device__ function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/src/Tensor/TensorRandom.h(213): warning: calling a constexpr __host__ function from a __host__ __device__ function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
build backprojecting layer
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/MathFunctions.h(1265): warning: calling a constexpr __host__ function("real") from a __host__ __device__ function("abs") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/MathFunctions.h(1265): warning: calling a constexpr __host__ function("imag") from a __host__ __device__ function("abs") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/MathFunctions.h(1265): warning: calling a constexpr __host__ function from a __host__ __device__ function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/MathFunctions.h(1265): warning: calling a constexpr __host__ function from a __host__ __device__ function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/MathFunctions.h(1270): warning: calling a constexpr __host__ function("real") from a __host__ __device__ function("abs") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/MathFunctions.h(1270): warning: calling a constexpr __host__ function("imag") from a __host__ __device__ function("abs") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/MathFunctions.h(1270): warning: calling a constexpr __host__ function from a __host__ __device__ function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/MathFunctions.h(1270): warning: calling a constexpr __host__ function from a __host__ __device__ function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/src/Tensor/TensorRandom.h(133): warning: calling a constexpr __host__ function from a __host__ __device__ function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/src/Tensor/TensorRandom.h(138): warning: calling a constexpr __host__ function from a __host__ __device__ function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/src/Tensor/TensorRandom.h(208): warning: calling a constexpr __host__ function from a __host__ __device__ function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/src/Tensor/TensorRandom.h(213): warning: calling a constexpr __host__ function from a __host__ __device__ function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
build projecting layer
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/MathFunctions.h(1265): warning: calling a constexpr __host__ function("real") from a __host__ __device__ function("abs") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/MathFunctions.h(1265): warning: calling a constexpr __host__ function("imag") from a __host__ __device__ function("abs") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/MathFunctions.h(1265): warning: calling a constexpr __host__ function from a __host__ __device__ function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/MathFunctions.h(1265): warning: calling a constexpr __host__ function from a __host__ __device__ function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/MathFunctions.h(1270): warning: calling a constexpr __host__ function("real") from a __host__ __device__ function("abs") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/MathFunctions.h(1270): warning: calling a constexpr __host__ function("imag") from a __host__ __device__ function("abs") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/MathFunctions.h(1270): warning: calling a constexpr __host__ function from a __host__ __device__ function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/MathFunctions.h(1270): warning: calling a constexpr __host__ function from a __host__ __device__ function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/src/Tensor/TensorRandom.h(133): warning: calling a constexpr __host__ function from a __host__ __device__ function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/src/Tensor/TensorRandom.h(138): warning: calling a constexpr __host__ function from a __host__ __device__ function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/src/Tensor/TensorRandom.h(208): warning: calling a constexpr __host__ function from a __host__ __device__ function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/src/Tensor/TensorRandom.h(213): warning: calling a constexpr __host__ function from a __host__ __device__ function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
 
build computing label layer

Despite some warnings, I chose to continue the fourth step:

cd $ROOT/lib/synthesize
mkdir build
cd build
cmake ..
make

When running cmake .., I got the following result:

cmake: /home/ubuntu/anaconda2/lib/libcurl.so.4: no version information available (required by cmake)
-- The C compiler identification is GNU 5.4.0
-- The CXX compiler identification is GNU 5.4.0
-- Check for working C compiler: /usr/bin/cc
-- Check for working C compiler: /usr/bin/cc -- works
-- Detecting C compiler ABI info
-- Detecting C compiler ABI info - done
-- Detecting C compile features
-- Detecting C compile features - done
-- Check for working CXX compiler: /usr/bin/c++
-- Check for working CXX compiler: /usr/bin/c++ -- works
-- Detecting CXX compiler ABI info
-- Detecting CXX compiler ABI info - done
-- Detecting CXX compile features
-- Detecting CXX compile features - done
-- Found Nlopt: /usr/lib/x86_64-linux-gnu/libnlopt.so  
-- Looking for pthread.h
-- Looking for pthread.h - found
-- Looking for pthread_create
-- Looking for pthread_create - not found
-- Looking for pthread_create in pthreads
-- Looking for pthread_create in pthreads - not found
-- Looking for pthread_create in pthread
-- Looking for pthread_create in pthread - found
-- Found Threads: TRUE  
-- Found CUDA: /usr/local/cuda (found version "8.0") 
-- Found PkgConfig: /usr/bin/pkg-config (found version "0.29.1") 
-- Checking for module 'eigen3'
--   Found eigen3, version 3.2.92
-- Found Eigen: /usr/include/eigen3  
-- Eigen found (include: /usr/include/eigen3, version: 3.2.92)
-- Boost version: 1.58.0
-- Found the following Boost libraries:
--   system
--   filesystem
--   thread
--   date_time
--   iostreams
--   serialization
--   chrono
--   atomic
--   regex
-- Checking for module 'flann'
--   Found flann, version 1.8.4
-- Found FLANN: /usr/lib/x86_64-linux-gnu/libflann_cpp.so  
-- FLANN found (include: /usr/include, lib: optimized;/usr/lib/x86_64-linux-gnu/libflann_cpp.so;debug;/usr/lib/x86_64-linux-gnu/libflann_cpp.so)
-- FLANN found (include: /usr/include, lib: optimized;/usr/lib/x86_64-linux-gnu/libflann_cpp.so;debug;/usr/lib/x86_64-linux-gnu/libflann_cpp.so)
-- Found Qhull: /usr/lib/x86_64-linux-gnu/libqhull.so  
-- QHULL found (include: /usr/include, lib: optimized;/usr/lib/x86_64-linux-gnu/libqhull.so;debug;/usr/lib/x86_64-linux-gnu/libqhull.so)
-- Checking for module 'libusb-1.0'
--   Found libusb-1.0, version 1.0.22
-- Found USB_10: /usr/local/lib/libusb-1.0.so  
-- Found OpenNI: /usr/lib/libOpenNI.so  
-- OpenNI found (include: /usr/include/ni, lib: /usr/lib/libOpenNI.so)
-- Found OpenNI2: /usr/lib/libOpenNI2.so  
-- OpenNI2 found (include: /usr/include/openni2, lib: /usr/lib/libOpenNI2.so)
** WARNING ** io features related to pcap will be disabled
** WARNING ** io features related to png will be disabled
-- Found libusb-1.0: /usr/local/include  
** WARNING ** io features related to libusb-1.0 will be disabled
-- OpenNI found (include: /usr/include/ni, lib: /usr/lib/libOpenNI.so)
-- OpenNI2 found (include: /usr/include/openni2, lib: /usr/lib/libOpenNI2.so)
-- looking for PCL_COMMON
-- Found PCL_COMMON: /usr/local/lib/libpcl_common.so  
-- looking for PCL_KDTREE
-- Found PCL_KDTREE: /usr/local/lib/libpcl_kdtree.so  
-- looking for PCL_OCTREE
-- Found PCL_OCTREE: /usr/local/lib/libpcl_octree.so  
-- looking for PCL_SEARCH
-- Found PCL_SEARCH: /usr/local/lib/libpcl_search.so  
-- looking for PCL_SURFACE
-- Found PCL_SURFACE: /usr/local/lib/libpcl_surface.so  
-- looking for PCL_GEOMETRY
-- Found PCL_GEOMETRY: /usr/local/include/pcl-1.8  
-- looking for PCL_IO
-- Found PCL_IO: /usr/local/lib/libpcl_io.so  
-- looking for PCL_SAMPLE_CONSENSUS
-- Found PCL_SAMPLE_CONSENSUS: /usr/local/lib/libpcl_sample_consensus.so  
-- looking for PCL_FILTERS
-- Found PCL_FILTERS: /usr/local/lib/libpcl_filters.so  
-- looking for PCL_2D
-- Found PCL_2D: /usr/local/include/pcl-1.8  
-- looking for PCL_FEATURES
-- Found PCL_FEATURES: /usr/local/lib/libpcl_features.so  
-- looking for PCL_VISUALIZATION
-- Found PCL_VISUALIZATION: /usr/local/lib/libpcl_visualization.so  
-- looking for PCL_TRACKING
-- Found PCL_TRACKING: /usr/local/lib/libpcl_tracking.so  
-- looking for PCL_OUTOFCORE
-- Found PCL_OUTOFCORE: /usr/local/lib/libpcl_outofcore.so  
-- looking for PCL_ML
-- Found PCL_ML: /usr/local/lib/libpcl_ml.so  
-- looking for PCL_SEGMENTATION
-- Found PCL_SEGMENTATION: /usr/local/lib/libpcl_segmentation.so  
-- looking for PCL_PEOPLE
-- Found PCL_PEOPLE: /usr/local/lib/libpcl_people.so  
-- looking for PCL_STEREO
-- Found PCL_STEREO: /usr/local/lib/libpcl_stereo.so  
-- looking for PCL_REGISTRATION
-- Found PCL_REGISTRATION: /usr/local/lib/libpcl_registration.so  
-- looking for PCL_RECOGNITION
-- Found PCL_RECOGNITION: /usr/local/lib/libpcl_recognition.so  
-- looking for PCL_KEYPOINTS
-- Found PCL_KEYPOINTS: /usr/local/lib/libpcl_keypoints.so  
-- Found PCL: /usr/lib/x86_64-linux-gnu/libboost_system.so;/usr/lib/x86_64-linux-gnu/libboost_filesystem.so;/usr/lib/x86_64-linux-gnu/libboost_thread.so;/usr/lib/x86_64-linux-gnu/libboost_date_time.so;/usr/lib/x86_64-linux-gnu/libboost_iostreams.so;/usr/lib/x86_64-linux-gnu/libboost_serialization.so;/usr/lib/x86_64-linux-gnu/libboost_chrono.so;/usr/lib/x86_64-linux-gnu/libboost_atomic.so;/usr/lib/x86_64-linux-gnu/libboost_regex.so;/usr/lib/x86_64-linux-gnu/libpthread.so;optimized;/usr/local/lib/libpcl_common.so;debug;/usr/local/lib/libpcl_common.so;optimized;/usr/lib/x86_64-linux-gnu/libflann_cpp.so;debug;/usr/lib/x86_64-linux-gnu/libflann_cpp.so;optimized;/usr/local/lib/libpcl_kdtree.so;debug;/usr/local/lib/libpcl_kdtree.so;optimized;/usr/local/lib/libpcl_octree.so;debug;/usr/local/lib/libpcl_octree.so;optimized;/usr/local/lib/libpcl_search.so;debug;/usr/local/lib/libpcl_search.so;optimized;/usr/lib/x86_64-linux-gnu/libqhull.so;debug;/usr/lib/x86_64-linux-gnu/libqhull.so;optimized;/usr/local/lib/libpcl_surface.so;debug;/usr/local/lib/libpcl_surface.so;/usr/lib/libOpenNI.so;/usr/lib/libOpenNI2.so;vtkCommon;vtkFiltering;vtkImaging;vtkGraphics;vtkGenericFiltering;vtkIO;vtkRendering;vtkVolumeRendering;vtkHybrid;vtkWidgets;vtkParallel;vtkInfovis;vtkGeovis;vtkViews;vtkCharts;optimized;/usr/local/lib/libpcl_io.so;debug;/usr/local/lib/libpcl_io.so;optimized;/usr/local/lib/libpcl_sample_consensus.so;debug;/usr/local/lib/libpcl_sample_consensus.so;optimized;/usr/local/lib/libpcl_filters.so;debug;/usr/local/lib/libpcl_filters.so;optimized;/usr/local/lib/libpcl_features.so;debug;/usr/local/lib/libpcl_features.so;optimized;/usr/local/lib/libpcl_visualization.so;debug;/usr/local/lib/libpcl_visualization.so;optimized;/usr/local/lib/libpcl_tracking.so;debug;/usr/local/lib/libpcl_tracking.so;optimized;/usr/local/lib/libpcl_outofcore.so;debug;/usr/local/lib/libpcl_outofcore.so;optimized;/usr/local/lib/libpcl_ml.so;debug;/usr/local/lib/libpcl_ml.so;optimized;/usr/local/lib/libpcl_segmentation.so;debug;/usr/local/lib/libpcl_segmentation.so;optimized;/usr/local/lib/libpcl_people.so;debug;/usr/local/lib/libpcl_people.so;optimized;/usr/local/lib/libpcl_stereo.so;debug;/usr/local/lib/libpcl_stereo.so;optimized;/usr/local/lib/libpcl_registration.so;debug;/usr/local/lib/libpcl_registration.so;optimized;/usr/local/lib/libpcl_recognition.so;debug;/usr/local/lib/libpcl_recognition.so;optimized;/usr/local/lib/libpcl_keypoints.so;debug;/usr/local/lib/libpcl_keypoints.so;/usr/lib/x86_64-linux-gnu/libboost_system.so;/usr/lib/x86_64-linux-gnu/libboost_filesystem.so;/usr/lib/x86_64-linux-gnu/libboost_thread.so;/usr/lib/x86_64-linux-gnu/libboost_date_time.so;/usr/lib/x86_64-linux-gnu/libboost_iostreams.so;/usr/lib/x86_64-linux-gnu/libboost_serialization.so;/usr/lib/x86_64-linux-gnu/libboost_chrono.so;/usr/lib/x86_64-linux-gnu/libboost_atomic.so;/usr/lib/x86_64-linux-gnu/libboost_regex.so;/usr/lib/x86_64-linux-gnu/libpthread.so;optimized;/usr/lib/x86_64-linux-gnu/libqhull.so;debug;/usr/lib/x86_64-linux-gnu/libqhull.so;/usr/lib/libOpenNI.so;/usr/lib/libOpenNI2.so;optimized;/usr/lib/x86_64-linux-gnu/libflann_cpp.so;debug;/usr/lib/x86_64-linux-gnu/libflann_cpp.so;vtkCommon;vtkFiltering;vtkImaging;vtkGraphics;vtkGenericFiltering;vtkIO;vtkRendering;vtkVolumeRendering;vtkHybrid;vtkWidgets;vtkParallel;vtkInfovis;vtkGeovis;vtkViews;vtkCharts  
-- Checking for module 'OpenEXR'
--   Found OpenEXR, version 2.2.0
-- Try OpenMP C flag = [-fopenmp]
-- Performing Test OpenMP_FLAG_DETECTED
-- Performing Test OpenMP_FLAG_DETECTED - Success
-- Try OpenMP CXX flag = [-fopenmp]
-- Performing Test OpenMP_FLAG_DETECTED
-- Performing Test OpenMP_FLAG_DETECTED - Success
-- Found OpenMP: -fopenmp  
-- xFusion root: /home/ubuntu/PoseCNN/lib/kinect_fusion
-- pangolin: /usr/local/lib/cmake/Pangolin/../../../include;/usr/include;/usr/include;/usr/include;/usr/include/eigen3
-- Configuring done
CMake Warning at /usr/share/cmake-3.5/Modules/FindCUDA.cmake:1649 (add_library):
  Cannot generate a safe runtime search path for target synthesizer because
  files in some directories may conflict with libraries in implicit
  directories:
 
    runtime library [libz.so.1] in /usr/lib/x86_64-linux-gnu may be hidden by files in:
      /home/ubuntu/anaconda2/lib
    runtime library [libtiff.so.5] in /usr/lib/x86_64-linux-gnu may be hidden by files in:
      /home/ubuntu/anaconda2/lib
 
  Some of these libraries may not be found correctly.
Call Stack (most recent call first):
  CMakeLists.txt:74 (cuda_add_library)
 
 
-- Generating done
-- Build files have been written to: /home/ubuntu/PoseCNN/lib/synthesize/build

When running make,I got the following result:

/usr/bin/cmake: /home/ubuntu/anaconda2/lib/libcurl.so.4: no version information available (required by /usr/bin/cmake)
/usr/bin/cmake: /home/ubuntu/anaconda2/lib/libcurl.so.4: no version information available (required by /usr/bin/cmake)
/usr/bin/cmake: /home/ubuntu/anaconda2/lib/libcurl.so.4: no version information available (required by /usr/bin/cmake)
Scanning dependencies of target synthesizer
/usr/bin/cmake: /home/ubuntu/anaconda2/lib/libcurl.so.4: no version information available (required by /usr/bin/cmake)
[ 25%] Building CXX object CMakeFiles/synthesizer.dir/synthesize.cpp.o
In file included from /home/ubuntu/PoseCNN/lib/synthesize/synthesize.hpp:49:0,
                 from /home/ubuntu/PoseCNN/lib/synthesize/synthesize.cpp:1:
/home/ubuntu/PoseCNN/lib/synthesize/types.h: In function \u2018cv::Mat jp::float2double(cv::Mat&)\u2019:
/home/ubuntu/PoseCNN/lib/synthesize/types.h:159:24: warning: comparison between signed and unsigned integer expressions [-Wsign-compare]
  for(unsigned i = 0; i < fmat.cols; i++)
                        ^
/home/ubuntu/PoseCNN/lib/synthesize/types.h:160:24: warning: comparison between signed and unsigned integer expressions [-Wsign-compare]
  for(unsigned j = 0; j < fmat.rows; j++)
                        ^
/home/ubuntu/PoseCNN/lib/synthesize/types.h: In function \u2018cv::Mat jp::double2float(cv::Mat&)\u2019:
/home/ubuntu/PoseCNN/lib/synthesize/types.h:176:24: warning: comparison between signed and unsigned integer expressions [-Wsign-compare]
  for(unsigned i = 0; i < dmat.cols; i++)
                        ^
/home/ubuntu/PoseCNN/lib/synthesize/types.h:177:24: warning: comparison between signed and unsigned integer expressions [-Wsign-compare]
  for(unsigned j = 0; j < dmat.rows; j++)
                        ^
In file included from /home/ubuntu/PoseCNN/lib/synthesize/synthesize.hpp:50:0,
                 from /home/ubuntu/PoseCNN/lib/synthesize/synthesize.cpp:1:
/home/ubuntu/PoseCNN/lib/synthesize/ransac.h: In constructor \u2018TransHyp::TransHyp(jp::id_t, jp::cv_trans_t)\u2019:
/home/ubuntu/PoseCNN/lib/synthesize/ransac.h:44:17: warning: \u2018TransHyp::pose\u2019 will be initialized after [-Wreorder]
  jp::cv_trans_t pose; // the actual transformation
                 ^
/home/ubuntu/PoseCNN/lib/synthesize/ransac.h:43:11: warning:   \u2018jp::id_t TransHyp::objID\u2019 [-Wreorder]
  jp::id_t objID; // ID of the object this hypothesis belongs to
           ^
In file included from /home/ubuntu/PoseCNN/lib/synthesize/synthesize.hpp:50:0,
                 from /home/ubuntu/PoseCNN/lib/synthesize/synthesize.cpp:1:
/home/ubuntu/PoseCNN/lib/synthesize/ransac.h:40:2: warning:   when initialized here [-Wreorder]
  TransHyp(jp::id_t objID, jp::cv_trans_t pose) : pose(pose), objID(objID), inli
  ^
In file included from /home/ubuntu/PoseCNN/lib/synthesize/synthesize.hpp:50:0,
                 from /home/ubuntu/PoseCNN/lib/synthesize/synthesize.cpp:1:
/home/ubuntu/PoseCNN/lib/synthesize/ransac.h:59:6: warning: \u2018TransHyp::inliers\u2019 will be initialized after [-Wreorder]
  int inliers; // how many of them were inliers
      ^
/home/ubuntu/PoseCNN/lib/synthesize/ransac.h:56:6: warning:   \u2018int TransHyp::maxPixels\u2019 [-Wreorder]
  int maxPixels; // how many pixels should be maximally drawn to score this hyp
      ^
In file included from /home/ubuntu/PoseCNN/lib/synthesize/synthesize.hpp:50:0,
                 from /home/ubuntu/PoseCNN/lib/synthesize/synthesize.cpp:1:
/home/ubuntu/PoseCNN/lib/synthesize/ransac.h:40:2: warning:   when initialized here [-Wreorder]
  TransHyp(jp::id_t objID, jp::cv_trans_t pose) : pose(pose), objID(objID), inli
  ^
In file included from /home/ubuntu/PoseCNN/lib/synthesize/synthesize.hpp:50:0,
                 from /home/ubuntu/PoseCNN/lib/synthesize/synthesize.cpp:1:
/home/ubuntu/PoseCNN/lib/synthesize/ransac.h:62:6: warning: \u2018TransHyp::refSteps\u2019 will be initialized after [-Wreorder]
  int refSteps; // how many iterations has this hyp been refined?
      ^
/home/ubuntu/PoseCNN/lib/synthesize/ransac.h:60:8: warning:   \u2018float TransHyp::likelihood\u2019 [-Wreorder]
  float likelihood; // likelihood of this hypothesis (optimization using uncerta
        ^
In file included from /home/ubuntu/PoseCNN/lib/synthesize/synthesize.hpp:50:0,
                 from /home/ubuntu/PoseCNN/lib/synthesize/synthesize.cpp:1:
/home/ubuntu/PoseCNN/lib/synthesize/ransac.h:40:2: warning:   when initialized here [-Wreorder]
  TransHyp(jp::id_t objID, jp::cv_trans_t pose) : pose(pose), objID(objID), inli
  ^
In file included from /home/ubuntu/PoseCNN/lib/synthesize/synthesize.hpp:50:0,
                 from /home/ubuntu/PoseCNN/lib/synthesize/synthesize.cpp:1:
/home/ubuntu/PoseCNN/lib/synthesize/ransac.h: In constructor \u2018TransHyp::TransHyp(jp::id_t, cv::Point2d)\u2019:
/home/ubuntu/PoseCNN/lib/synthesize/ransac.h:46:21: warning: \u2018TransHyp::center\u2019 will be initialized after [-Wreorder]
         cv::Point2d center; // object center
                     ^
/home/ubuntu/PoseCNN/lib/synthesize/ransac.h:43:11: warning:   \u2018jp::id_t TransHyp::objID\u2019 [-Wreorder]
  jp::id_t objID; // ID of the object this hypothesis belongs to
           ^
/home/ubuntu/PoseCNN/lib/synthesize/ransac.h:41:9: warning:   when initialized here [-Wreorder]
         TransHyp(jp::id_t objID, cv::Point2d center) : center(center), objID(ob
         ^
/home/ubuntu/PoseCNN/lib/synthesize/ransac.h:59:6: warning: \u2018TransHyp::inliers\u2019 will be initialized after [-Wreorder]
  int inliers; // how many of them were inliers
      ^
/home/ubuntu/PoseCNN/lib/synthesize/ransac.h:56:6: warning:   \u2018int TransHyp::maxPixels\u2019 [-Wreorder]
  int maxPixels; // how many pixels should be maximally drawn to score this hyp
      ^
/home/ubuntu/PoseCNN/lib/synthesize/ransac.h:41:9: warning:   when initialized here [-Wreorder]
         TransHyp(jp::id_t objID, cv::Point2d center) : center(center), objID(ob
         ^
/home/ubuntu/PoseCNN/lib/synthesize/ransac.h:62:6: warning: \u2018TransHyp::refSteps\u2019 will be initialized after [-Wreorder]
  int refSteps; // how many iterations has this hyp been refined?
      ^
/home/ubuntu/PoseCNN/lib/synthesize/ransac.h:60:8: warning:   \u2018float TransHyp::likelihood\u2019 [-Wreorder]
  float likelihood; // likelihood of this hypothesis (optimization using uncerta
        ^
/home/ubuntu/PoseCNN/lib/synthesize/ransac.h:41:9: warning:   when initialized here [-Wreorder]
         TransHyp(jp::id_t objID, cv::Point2d center) : center(center), objID(ob
         ^
In file included from /home/ubuntu/PoseCNN/lib/synthesize/synthesize.hpp:52:0,
                 from /home/ubuntu/PoseCNN/lib/synthesize/synthesize.cpp:1:
/home/ubuntu/PoseCNN/lib/synthesize/detection.h: In function \u2018cv::Rect getBB2D(int, int, const std::vector<cv::Point3_<float> >&, const cv::Mat&, const jp_trans_t&)\u2019:
/home/ubuntu/PoseCNN/lib/synthesize/detection.h:130:23: warning: comparison between signed and unsigned integer expressions [-Wsign-compare]
     for (int i = 0; i < bb3D.size(); i++)
                       ^
/home/ubuntu/PoseCNN/lib/synthesize/synthesize.cpp: In member function \u2018aiMesh* Synthesizer::loadTexturedMesh(std::__cxx11::string, std::__cxx11::string&)\u2019:
/home/ubuntu/PoseCNN/lib/synthesize/synthesize.cpp:209:23: warning: comparison between signed and unsigned integer expressions [-Wsign-compare]
     for (int i = 0; i < scene->mNumMaterials; ++i) 
                       ^
/home/ubuntu/PoseCNN/lib/synthesize/synthesize.cpp: In member function \u2018void Synthesizer::render(int, int, float, float, float, float, float, float, unsigned char*, float*, float*, float*, float*, float*, float*, float*, float)\u2019:
/home/ubuntu/PoseCNN/lib/synthesize/synthesize.cpp:501:31: warning: narrowing conversion of \u2018drand(-1.0e+0, 1.0e+0, -1)\u2019 from \u2018double\u2019 to \u2018GLfloat {aka float}\u2019 inside { } [-Wnarrowing]
   GLfloat lightpos0[] = {drand(-1, 1), drand(-1, 1), drand(0.2, 5), 1.};
                               ^
/home/ubuntu/PoseCNN/lib/synthesize/synthesize.cpp:501:45: warning: narrowing conversion of \u2018drand(-1.0e+0, 1.0e+0, -1)\u2019 from \u2018double\u2019 to \u2018GLfloat {aka float}\u2019 inside { } [-Wnarrowing]
   GLfloat lightpos0[] = {drand(-1, 1), drand(-1, 1), drand(0.2, 5), 1.};
                                             ^
/home/ubuntu/PoseCNN/lib/synthesize/synthesize.cpp:501:59: warning: narrowing conversion of \u2018drand(2.0000000000000001e-1, 5.0e+0, -1)\u2019 from \u2018double\u2019 to \u2018GLfloat {aka float}\u2019 inside { } [-Wnarrowing]
   GLfloat lightpos0[] = {drand(-1, 1), drand(-1, 1), drand(0.2, 5), 1.};
                                                           ^
/home/ubuntu/PoseCNN/lib/synthesize/synthesize.cpp: In member function \u2018void Synthesizer::render_one(int, int, int, float, float, float, float, float, float, unsigned char*, float*, float*, float*, float*, float*)\u2019:
/home/ubuntu/PoseCNN/lib/synthesize/synthesize.cpp:775:31: warning: narrowing conversion of \u2018drand(-1.0e+0, 1.0e+0, -1)\u2019 from \u2018double\u2019 to \u2018GLfloat {aka float}\u2019 inside { } [-Wnarrowing]
   GLfloat lightpos0[] = {drand(-1, 1), drand(-1, 1), drand(0.2, 5), 1.};
                               ^
/home/ubuntu/PoseCNN/lib/synthesize/synthesize.cpp:775:45: warning: narrowing conversion of \u2018drand(-1.0e+0, 1.0e+0, -1)\u2019 from \u2018double\u2019 to \u2018GLfloat {aka float}\u2019 inside { } [-Wnarrowing]
   GLfloat lightpos0[] = {drand(-1, 1), drand(-1, 1), drand(0.2, 5), 1.};
                                             ^
/home/ubuntu/PoseCNN/lib/synthesize/synthesize.cpp:775:59: warning: narrowing conversion of \u2018drand(2.0000000000000001e-1, 5.0e+0, -1)\u2019 from \u2018double\u2019 to \u2018GLfloat {aka float}\u2019 inside { } [-Wnarrowing]
   GLfloat lightpos0[] = {drand(-1, 1), drand(-1, 1), drand(0.2, 5), 1.};
                                                           ^
/home/ubuntu/PoseCNN/lib/synthesize/synthesize.cpp:688:10: warning: variable \u2018pose\u2019 set but not used [-Wunused-but-set-variable]
   float* pose = poses_[class_id] + seed * 7;
          ^
/home/ubuntu/PoseCNN/lib/synthesize/synthesize.cpp: In member function \u2018void Synthesizer::getLabels(const int*, std::vector<std::vector<int> >&, std::vector<int>&, int, int, int, int)\u2019:
/home/ubuntu/PoseCNN/lib/synthesize/synthesize.cpp:911:26: warning: comparison between signed and unsigned integer expressions [-Wsign-compare]
     if (labels[i].size() > minArea)
                          ^
/home/ubuntu/PoseCNN/lib/synthesize/synthesize.cpp: In member function \u2018std::vector<TransHyp*> Synthesizer::getWorkingQueue(std::map<short unsigned int, std::vector<TransHyp> >&, int)\u2019:
/home/ubuntu/PoseCNN/lib/synthesize/synthesize.cpp:1035:20: warning: comparison between signed and unsigned integer expressions [-Wsign-compare]
   for(int h = 0; h < it->second.size(); h++)
                    ^
/home/ubuntu/PoseCNN/lib/synthesize/synthesize.cpp: In member function \u2018void Synthesizer::countInliers2D(TransHyp&, const cv::Mat&, const std::vector<std::vector<int> >&, const float*, const float*, float, int, int, int)\u2019:
/home/ubuntu/PoseCNN/lib/synthesize/synthesize.cpp:1080:33: warning: comparison between signed and unsigned integer expressions [-Wsign-compare]
   for(unsigned ptIdx = 0; ptIdx < maxPt;)
                                 ^
/home/ubuntu/PoseCNN/lib/synthesize/synthesize.cpp: In member function \u2018void Synthesizer::countInliers3D(TransHyp&, const std::vector<std::vector<int> >&, const float*, const float*, const img_coord_t&, float, int, int, int)\u2019:
/home/ubuntu/PoseCNN/lib/synthesize/synthesize.cpp:1140:33: warning: comparison between signed and unsigned integer expressions [-Wsign-compare]
   for(unsigned ptIdx = 0; ptIdx < maxPt;)
                                 ^
/home/ubuntu/PoseCNN/lib/synthesize/synthesize.cpp: In member function \u2018void Synthesizer::filterInliers2D(TransHyp&, int)\u2019:
/home/ubuntu/PoseCNN/lib/synthesize/synthesize.cpp:1178:29: warning: comparison between signed and unsigned integer expressions [-Wsign-compare]
   if(hyp.inlierPts2D.size() < maxInliers) return; // maximum number not reached
                             ^
/home/ubuntu/PoseCNN/lib/synthesize/synthesize.cpp:1183:25: warning: comparison between signed and unsigned integer expressions [-Wsign-compare]
   for(unsigned i = 0; i < maxInliers; i++)
                         ^
/home/ubuntu/PoseCNN/lib/synthesize/synthesize.cpp: In member function \u2018void Synthesizer::filterInliers3D(TransHyp&, int)\u2019:
/home/ubuntu/PoseCNN/lib/synthesize/synthesize.cpp:1195:27: warning: comparison between signed and unsigned integer expressions [-Wsign-compare]
   if(hyp.inlierPts.size() < maxInliers) return; // maximum number not reached, 
                           ^
/home/ubuntu/PoseCNN/lib/synthesize/synthesize.cpp:1200:25: warning: comparison between signed and unsigned integer expressions [-Wsign-compare]
   for(unsigned i = 0; i < maxInliers; i++)
                         ^
/home/ubuntu/PoseCNN/lib/synthesize/synthesize.cpp: In member function \u2018void Synthesizer::updateHyp2D(TransHyp&, const cv::Mat&, int, int, const std::vector<cv::Point3_<float> >&, int)\u2019:
/home/ubuntu/PoseCNN/lib/synthesize/synthesize.cpp:1218:21: warning: comparison between signed and unsigned integer expressions [-Wsign-compare]
   for (int i = 0; i < hyp.inlierPts2D.size(); i++)
                     ^
/home/ubuntu/PoseCNN/lib/synthesize/synthesize.cpp: In function \u2018double optEnergy2D(const std::vector<double>&, std::vector<double>&, void*)\u2019:
/home/ubuntu/PoseCNN/lib/synthesize/synthesize.cpp:1331:21: warning: comparison between signed and unsigned integer expressions [-Wsign-compare]
   for (int i = 0; i < dataForOpt->hyp->inlierPts2D.size(); i++)
                     ^
/home/ubuntu/PoseCNN/lib/synthesize/synthesize.cpp:1336:22: warning: comparison between signed and unsigned integer expressions [-Wsign-compare]
   for(int pt = 0; pt < dataForOpt->hyp->inlierPts2D.size(); pt++) // iterate ov
                      ^
/home/ubuntu/PoseCNN/lib/synthesize/synthesize.cpp: In function \u2018double optEnergy3D(const std::vector<double>&, std::vector<double>&, void*)\u2019:
/home/ubuntu/PoseCNN/lib/synthesize/synthesize.cpp:1371:22: warning: comparison between signed and unsigned integer expressions [-Wsign-compare]
   for(int pt = 0; pt < dataForOpt->hyp->inlierPts.size(); pt++) // iterate over
                      ^
/home/ubuntu/PoseCNN/lib/synthesize/synthesize.cpp: In member function \u2018double Synthesizer::refineWithOpt(TransHyp&, cv::Mat&, int, int)\u2019:
/home/ubuntu/PoseCNN/lib/synthesize/synthesize.cpp:1440:17: warning: unused variable \u2018result\u2019 [-Wunused-variable]
   nlopt::result result = opt.optimize(vec, energy);
                 ^
/home/ubuntu/PoseCNN/lib/synthesize/synthesize.cpp: In member function \u2018void Synthesizer::estimatePose2D(const int*, const float*, const float*, int, int, int, float, float, float, float, float*)\u2019:
/home/ubuntu/PoseCNN/lib/synthesize/synthesize.cpp:1499:27: warning: comparison between signed and unsigned integer expressions [-Wsign-compare]
   for(unsigned h = 0; h < ransacIterations; h++)
                           ^
/home/ubuntu/PoseCNN/lib/synthesize/synthesize.cpp:1500:25: warning: comparison between signed and unsigned integer expressions [-Wsign-compare]
   for(unsigned i = 0; i < maxIterations; i++)
                         ^
/home/ubuntu/PoseCNN/lib/synthesize/synthesize.cpp:1595:42: warning: comparison between signed and unsigned integer expressions [-Wsign-compare]
     for(int h = 0; h < workingQueue.size(); h++)
                                          ^
/home/ubuntu/PoseCNN/lib/synthesize/synthesize.cpp:1613:42: warning: comparison between signed and unsigned integer expressions [-Wsign-compare]
     for(int h = 0; h < workingQueue.size(); h++)
                                          ^
/home/ubuntu/PoseCNN/lib/synthesize/synthesize.cpp:1623:20: warning: comparison between signed and unsigned integer expressions [-Wsign-compare]
   for(int h = 0; h < it->second.size(); h++)
                    ^
/home/ubuntu/PoseCNN/lib/synthesize/synthesize.cpp: In member function \u2018void Synthesizer::estimatePose3D(const int*, unsigned char*, const float*, const float*, int, int, int, float, float, float, float, float, float*)\u2019:
/home/ubuntu/PoseCNN/lib/synthesize/synthesize.cpp:1699:27: warning: comparison between signed and unsigned integer expressions [-Wsign-compare]
   for(unsigned h = 0; h < ransacIterations; h++)
                           ^
/home/ubuntu/PoseCNN/lib/synthesize/synthesize.cpp:1700:25: warning: comparison between signed and unsigned integer expressions [-Wsign-compare]
   for(unsigned i = 0; i < maxIterations; i++)
                         ^
/home/ubuntu/PoseCNN/lib/synthesize/synthesize.cpp:1794:42: warning: comparison between signed and unsigned integer expressions [-Wsign-compare]
     for(int h = 0; h < workingQueue.size(); h++)
                                          ^
/home/ubuntu/PoseCNN/lib/synthesize/synthesize.cpp:1812:42: warning: comparison between signed and unsigned integer expressions [-Wsign-compare]
     for(int h = 0; h < workingQueue.size(); h++)
                                          ^
/home/ubuntu/PoseCNN/lib/synthesize/synthesize.cpp:1822:20: warning: comparison between signed and unsigned integer expressions [-Wsign-compare]
   for(int h = 0; h < it->second.size(); h++)
                    ^
/home/ubuntu/PoseCNN/lib/synthesize/synthesize.cpp: In member function \u2018void Synthesizer::refinePose(int, int, int, float, float, const int*, DataForOpt, df::Poly3CameraModel<float>, Sophus::SE3f&, int, float, int)\u2019:
/home/ubuntu/PoseCNN/lib/synthesize/synthesize.cpp:1898:13: warning: unused variable \u2018energy\u2019 [-Wunused-variable]
       float energy = poseWithOpt(vec, data, iterations);
             ^
/home/ubuntu/PoseCNN/lib/synthesize/synthesize.cpp: In member function \u2018void Synthesizer::solveICP(const int*, unsigned char*, int, int, float, float, float, float, float, float, float, int, int, const float*, const float*, float*, float*, float)\u2019:
/home/ubuntu/PoseCNN/lib/synthesize/synthesize.cpp:2040:23: warning: comparison between signed and unsigned integer expressions [-Wsign-compare]
     for (int j = 0; j < label_indexes_.size(); j++)
                       ^
/home/ubuntu/PoseCNN/lib/synthesize/synthesize.cpp:2149:23: warning: comparison between signed and unsigned integer expressions [-Wsign-compare]
     for (int j = 0; j < hyps.size(); j++)
                       ^
/home/ubuntu/PoseCNN/lib/synthesize/synthesize.cpp:2174:25: warning: comparison between signed and unsigned integer expressions [-Wsign-compare]
       for (int j = 0; j < hyps.size(); j++)
                         ^
/home/ubuntu/PoseCNN/lib/synthesize/synthesize.cpp:2179:47: warning: comparison between signed and unsigned integer expressions [-Wsign-compare]
         for (int k = 0; k < model_points.size(); k++)
                                               ^
/home/ubuntu/PoseCNN/lib/synthesize/synthesize.cpp: In member function \u2018void Synthesizer::visualizePose(int, int, float, float, float, float, float, float, const float*, float*, int, int)\u2019:
/home/ubuntu/PoseCNN/lib/synthesize/synthesize.cpp:2276:9: warning: unused variable \u2018threshold\u2019 [-Wunused-variable]
   float threshold = 0.1;
         ^
/home/ubuntu/PoseCNN/lib/synthesize/synthesize.cpp: In function \u2018double optEnergy(const std::vector<double>&, std::vector<double>&, void*)\u2019:
/home/ubuntu/PoseCNN/lib/synthesize/synthesize.cpp:2362:21: warning: comparison between signed and unsigned integer expressions [-Wsign-compare]
   for (int i = 0; i < dataForOpt->label_indexes->size(); i++)
                     ^
/home/ubuntu/PoseCNN/lib/synthesize/synthesize.cpp:2355:7: warning: unused variable \u2018height\u2019 [-Wunused-variable]
   int height = dataForOpt->height;
       ^
/home/ubuntu/PoseCNN/lib/synthesize/synthesize.cpp:2356:7: warning: unused variable \u2018objID\u2019 [-Wunused-variable]
   int objID = dataForOpt->objID;
       ^
/home/ubuntu/PoseCNN/lib/synthesize/synthesize.cpp:2357:14: warning: unused variable \u2018labelmap\u2019 [-Wunused-variable]
   const int* labelmap = dataForOpt->labelmap;
              ^
/home/ubuntu/PoseCNN/lib/synthesize/synthesize.cpp: In member function \u2018double Synthesizer::poseWithOpt(std::vector<double>&, DataForOpt, int)\u2019:
/home/ubuntu/PoseCNN/lib/synthesize/synthesize.cpp:2431:17: warning: unused variable \u2018result\u2019 [-Wunused-variable]
   nlopt::result result = opt.optimize(vec, energy);
                 ^
In file included from /home/ubuntu/PoseCNN/lib/synthesize/synthesize.hpp:41:0,
                 from /home/ubuntu/PoseCNN/lib/synthesize/synthesize.cpp:1:
/home/ubuntu/PoseCNN/lib/kinect_fusion/include/df/prediction/glRender.h: In instantiation of \u2018void df::GLRenderer<RenderType>::render(const std::vector<std::vector<pangolin::GlBuffer*> >&, const std::vector<pangolin::GlBuffer*>&, const std::vector<Eigen::Matrix<float, 4, 4> >&, GLenum) [with RenderType = df::CanonicalVertRenderType; GLenum = unsigned int]\u2019:
/home/ubuntu/PoseCNN/lib/synthesize/synthesize.cpp:435:68:   required from here
/home/ubuntu/PoseCNN/lib/kinect_fusion/include/df/prediction/glRender.h:274:23: warning: comparison between signed and unsigned integer expressions [-Wsign-compare]
     for (int m = 0; m < vertexAttributeBuffers.size(); ++m) {
                       ^
/home/ubuntu/PoseCNN/lib/synthesize/synthesize.cpp: In member function \u2018void Synthesizer::loadPoses(std::__cxx11::string)\u2019:
/home/ubuntu/PoseCNN/lib/synthesize/synthesize.cpp:130:33: warning: ignoring return value of \u2018int fscanf(FILE*, const char*, ...)\u2019, declared with attribute warn_unused_result [-Wunused-result]
       fscanf(fp, "%f", pose + i);
                                 ^
/usr/bin/cmake: /home/ubuntu/anaconda2/lib/libcurl.so.4: no version information available (required by /usr/bin/cmake)
[ 50%] Building CXX object CMakeFiles/synthesizer.dir/thread_rand.cpp.o
/usr/bin/cmake: /home/ubuntu/anaconda2/lib/libcurl.so.4: no version information available (required by /usr/bin/cmake)
[ 75%] Building CXX object CMakeFiles/synthesizer.dir/Hypothesis.cpp.o
In file included from /home/ubuntu/PoseCNN/lib/synthesize/Hypothesis.h:34:0,
                 from /home/ubuntu/PoseCNN/lib/synthesize/Hypothesis.cpp:28:
/home/ubuntu/PoseCNN/lib/synthesize/types.h: In function \u2018cv::Mat jp::float2double(cv::Mat&)\u2019:
/home/ubuntu/PoseCNN/lib/synthesize/types.h:159:24: warning: comparison between signed and unsigned integer expressions [-Wsign-compare]
  for(unsigned i = 0; i < fmat.cols; i++)
                        ^
/home/ubuntu/PoseCNN/lib/synthesize/types.h:160:24: warning: comparison between signed and unsigned integer expressions [-Wsign-compare]
  for(unsigned j = 0; j < fmat.rows; j++)
                        ^
/home/ubuntu/PoseCNN/lib/synthesize/types.h: In function \u2018cv::Mat jp::double2float(cv::Mat&)\u2019:
/home/ubuntu/PoseCNN/lib/synthesize/types.h:176:24: warning: comparison between signed and unsigned integer expressions [-Wsign-compare]
  for(unsigned i = 0; i < dmat.cols; i++)
                        ^
/home/ubuntu/PoseCNN/lib/synthesize/types.h:177:24: warning: comparison between signed and unsigned integer expressions [-Wsign-compare]
  for(unsigned j = 0; j < dmat.rows; j++)
                        ^
/usr/bin/cmake: /home/ubuntu/anaconda2/lib/libcurl.so.4: no version information available (required by /usr/bin/cmake)
[100%] Linking CXX shared library libsynthesizer.so
/usr/bin/cmake: /home/ubuntu/anaconda2/lib/libcurl.so.4: no version information available (required by /usr/bin/cmake)
/usr/bin/cmake: /home/ubuntu/anaconda2/lib/libcurl.so.4: no version information available (required by /usr/bin/cmake)
[100%] Built target synthesizer
/usr/bin/cmake: /home/ubuntu/anaconda2/lib/libcurl.so.4: no version information available (required by /usr/bin/cmake)

Then I ran the following code:

cd $ROOT/lib
python setup.py build_ext --inplace

I got the following results:

cythoning normals/gpu_normals.pyx to normals/gpu_normals.cpp
building 'normals.gpu_normals' extension
/usr/local/cuda/bin/nvcc -I/home/ubuntu/anaconda2/lib/python2.7/site-packages/numpy/core/include -I/usr/local/cuda/include -I/usr/local/include/eigen3 -I/home/ubuntu/anaconda2/include/python2.7 -c normals/compute_normals.cu -o build/temp.linux-x86_64-2.7/normals/compute_normals.o -arch=sm_35 --ptxas-options=-v -c --compiler-options '-fPIC'
ptxas info    : 0 bytes gmem
ptxas info    : Compiling entry function '_Z17computeNmapKernelPfS_ii' for 'sm_35'
ptxas info    : Function properties for _Z17computeNmapKernelPfS_ii
    0 bytes stack frame, 0 bytes spill stores, 0 bytes spill loads
ptxas info    : Used 20 registers, 344 bytes cmem[0], 8 bytes cmem[2]
ptxas info    : Compiling entry function '_Z17computeVmapKernelPfS_fffffii' for 'sm_35'
ptxas info    : Function properties for _Z17computeVmapKernelPfS_fffffii
    0 bytes stack frame, 0 bytes spill stores, 0 bytes spill loads
ptxas info    : Used 8 registers, 364 bytes cmem[0]
gcc -pthread -B /home/ubuntu/anaconda2/compiler_compat -Wl,--sysroot=/ -fno-strict-aliasing -g -O2 -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -fPIC -I/home/ubuntu/anaconda2/lib/python2.7/site-packages/numpy/core/include -I/usr/local/cuda/include -I/usr/local/include/eigen3 -I/home/ubuntu/anaconda2/include/python2.7 -c normals/gpu_normals.cpp -o build/temp.linux-x86_64-2.7/normals/gpu_normals.o -Wno-unused-function
cc1plus: warning: command line option \u2018-Wstrict-prototypes\u2019 is valid for C/ObjC but not for C++
In file included from /home/ubuntu/anaconda2/lib/python2.7/site-packages/numpy/core/include/numpy/ndarraytypes.h:1809:0,
                 from /home/ubuntu/anaconda2/lib/python2.7/site-packages/numpy/core/include/numpy/ndarrayobject.h:18,
                 from /home/ubuntu/anaconda2/lib/python2.7/site-packages/numpy/core/include/numpy/arrayobject.h:4,
                 from normals/gpu_normals.cpp:499:
/home/ubuntu/anaconda2/lib/python2.7/site-packages/numpy/core/include/numpy/npy_1_7_deprecated_api.h:15:2: warning: #warning "Using deprecated NumPy API, disable it by " "#defining NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION" [-Wcpp]
 #warning "Using deprecated NumPy API, disable it by " \
  ^
g++ -pthread -shared -B /home/ubuntu/anaconda2/compiler_compat -L/home/ubuntu/anaconda2/lib -Wl,-rpath=/home/ubuntu/anaconda2/lib -Wl,--no-as-needed -Wl,--sysroot=/ build/temp.linux-x86_64-2.7/normals/compute_normals.o build/temp.linux-x86_64-2.7/normals/gpu_normals.o -L/usr/local/cuda/lib64 -L/home/ubuntu/anaconda2/lib -Wl,-R/usr/local/cuda/lib64 -lcudart -lpython2.7 -o /home/ubuntu/PoseCNN/lib/normals/gpu_normals.so
cythoning utils/bbox.pyx to utils/bbox.c
building 'utils.cython_bbox' extension
gcc -pthread -B /home/ubuntu/anaconda2/compiler_compat -Wl,--sysroot=/ -fno-strict-aliasing -g -O2 -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -fPIC -I/home/ubuntu/anaconda2/lib/python2.7/site-packages/numpy/core/include -I/home/ubuntu/anaconda2/include/python2.7 -c utils/bbox.c -o build/temp.linux-x86_64-2.7/utils/bbox.o -Wno-cpp -Wno-unused-function
gcc -pthread -shared -B /home/ubuntu/anaconda2/compiler_compat -L/home/ubuntu/anaconda2/lib -Wl,-rpath=/home/ubuntu/anaconda2/lib -Wl,--no-as-needed -Wl,--sysroot=/ build/temp.linux-x86_64-2.7/utils/bbox.o -L/home/ubuntu/anaconda2/lib -lpython2.7 -o /home/ubuntu/PoseCNN/lib/utils/cython_bbox.so
cythoning nms/cpu_nms.pyx to nms/cpu_nms.c
building 'nms.cpu_nms' extension
gcc -pthread -B /home/ubuntu/anaconda2/compiler_compat -Wl,--sysroot=/ -fno-strict-aliasing -g -O2 -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -fPIC -I/home/ubuntu/anaconda2/lib/python2.7/site-packages/numpy/core/include -I/home/ubuntu/anaconda2/include/python2.7 -c nms/cpu_nms.c -o build/temp.linux-x86_64-2.7/nms/cpu_nms.o -Wno-cpp -Wno-unused-function
gcc -pthread -shared -B /home/ubuntu/anaconda2/compiler_compat -L/home/ubuntu/anaconda2/lib -Wl,-rpath=/home/ubuntu/anaconda2/lib -Wl,--no-as-needed -Wl,--sysroot=/ build/temp.linux-x86_64-2.7/nms/cpu_nms.o -L/home/ubuntu/anaconda2/lib -lpython2.7 -o /home/ubuntu/PoseCNN/lib/nms/cpu_nms.so
cythoning nms/gpu_nms.pyx to nms/gpu_nms.cpp
building 'nms.gpu_nms' extension
/usr/local/cuda/bin/nvcc -I/home/ubuntu/anaconda2/lib/python2.7/site-packages/numpy/core/include -I/usr/local/cuda/include -I/home/ubuntu/anaconda2/include/python2.7 -c nms/nms_kernel.cu -o build/temp.linux-x86_64-2.7/nms/nms_kernel.o -arch=sm_52 --ptxas-options=-v -c --compiler-options '-fPIC'
ptxas info    : 0 bytes gmem
ptxas info    : Compiling entry function '_Z10nms_kernelifPKfPy' for 'sm_52'
ptxas info    : Function properties for _Z10nms_kernelifPKfPy
    0 bytes stack frame, 0 bytes spill stores, 0 bytes spill loads
ptxas info    : Used 22 registers, 1280 bytes smem, 344 bytes cmem[0], 12 bytes cmem[2]
gcc -pthread -B /home/ubuntu/anaconda2/compiler_compat -Wl,--sysroot=/ -fno-strict-aliasing -g -O2 -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -fPIC -I/home/ubuntu/anaconda2/lib/python2.7/site-packages/numpy/core/include -I/usr/local/cuda/include -I/home/ubuntu/anaconda2/include/python2.7 -c nms/gpu_nms.cpp -o build/temp.linux-x86_64-2.7/nms/gpu_nms.o -Wno-unused-function
cc1plus: warning: command line option \u2018-Wstrict-prototypes\u2019 is valid for C/ObjC but not for C++
In file included from /home/ubuntu/anaconda2/lib/python2.7/site-packages/numpy/core/include/numpy/ndarraytypes.h:1809:0,
                 from /home/ubuntu/anaconda2/lib/python2.7/site-packages/numpy/core/include/numpy/ndarrayobject.h:18,
                 from /home/ubuntu/anaconda2/lib/python2.7/site-packages/numpy/core/include/numpy/arrayobject.h:4,
                 from nms/gpu_nms.cpp:499:
/home/ubuntu/anaconda2/lib/python2.7/site-packages/numpy/core/include/numpy/npy_1_7_deprecated_api.h:15:2: warning: #warning "Using deprecated NumPy API, disable it by " "#defining NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION" [-Wcpp]
 #warning "Using deprecated NumPy API, disable it by " \
  ^
g++ -pthread -shared -B /home/ubuntu/anaconda2/compiler_compat -L/home/ubuntu/anaconda2/lib -Wl,-rpath=/home/ubuntu/anaconda2/lib -Wl,--no-as-needed -Wl,--sysroot=/ build/temp.linux-x86_64-2.7/nms/nms_kernel.o build/temp.linux-x86_64-2.7/nms/gpu_nms.o -L/usr/local/cuda/lib64 -L/home/ubuntu/anaconda2/lib -Wl,-R/usr/local/cuda/lib64 -lcudart -lpython2.7 -o /home/ubuntu/PoseCNN/lib/nms/gpu_nms.so
cythoning synthesize/synthesizer.pyx to synthesize/synthesizer.cpp
building 'synthesize.synthesizer' extension
gcc -pthread -B /home/ubuntu/anaconda2/compiler_compat -Wl,--sysroot=/ -fno-strict-aliasing -g -O2 -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -fPIC -I/home/ubuntu/anaconda2/include/python2.7 -c synthesize/synthesizer.cpp -o build/temp.linux-x86_64-2.7/synthesize/synthesizer.o -Wno-unused-function
cc1plus: warning: command line option \u2018-Wstrict-prototypes\u2019 is valid for C/ObjC but not for C++
In file included from /usr/include/numpy/ndarraytypes.h:1777:0,
                 from /usr/include/numpy/ndarrayobject.h:18,
                 from /usr/include/numpy/arrayobject.h:4,
                 from synthesize/synthesizer.cpp:504:
/usr/include/numpy/npy_1_7_deprecated_api.h:15:2: warning: #warning "Using deprecated NumPy API, disable it by " "#defining NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION" [-Wcpp]
 #warning "Using deprecated NumPy API, disable it by " \
  ^
g++ -pthread -shared -B /home/ubuntu/anaconda2/compiler_compat -L/home/ubuntu/anaconda2/lib -Wl,-rpath=/home/ubuntu/anaconda2/lib -Wl,--no-as-needed -Wl,--sysroot=/ build/temp.linux-x86_64-2.7/synthesize/synthesizer.o synthesize/build/libsynthesizer.so -L/home/ubuntu/anaconda2/lib -lpython2.7 -o /home/ubuntu/PoseCNN/lib/synthesize/synthesizer.so

implementation problems

Hi Yu Xiang,

Thanks for providing the code for your paper. I met some problems when run the commands that you provided.

when i run the following:
Shell cd $ROOT/lib/synthesize mkdir build cd build cmake .. make
There were some problems, it said 'can't fine the #include <df/camera/camera.h>'
how can i find all the df files?

Thanks.

Segmentation Fault

Hi,
While running ./experiments/scripts/demo.sh $GPU_ID, I almost always get these errors and warnings :

2018-07-06 13:14:14.755317: E tensorflow/stream_executor/cuda/cuda_driver.cc:406] failed call to cuInit: CUDA_ERROR_NO_DEVICE
2018-07-06 13:14:14.755381: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:158] retrieving CUDA diagnostic information for host: thomas-HP-Pavilion-15-Notebook-PC
2018-07-06 13:14:14.755404: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:165] hostname: thomas-HP-Pavilion-15-Notebook-PC
2018-07-06 13:14:14.755490: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:189] libcuda reported version is: 384.130.0
2018-07-06 13:14:14.755530: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:369] driver version file contents: """NVRM version: NVIDIA UNIX x86_64 Kernel Module  384.130  Wed Mar 21 03:37:26 PDT 2018 GCC version:  gcc version 5.4.0 20160609 (Ubuntu 5.4.0-6ubuntu1~16.04.10) """
2018-07-06 13:14:14.755558: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:193] kernel reported version is: 384.130.0
2018-07-06 13:14:14.755572: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:300] kernel version seems to match DSO: 384.130.0
Loading model weights from data/demo_models/vgg16_fcn_color_single_frame_2d_pose_add_lov_iter_160000.ckpt
data/demo_images/000002-color.png
./experiments/scripts/demo.sh: line 18: 16203 Segmentation fault      (core dumped) ./tools/demo.py --gpu 0 --network vgg16_convs --model data/demo_models/vgg16_fcn_color_single_frame_2d_pose_add_lov_iter_160000.ckpt --imdb lov_keyframe --cfg experiments/cfgs/lov_color_2d.yml --rig data/LOV/camera.json --cad data/LOV/models.txt --pose data/LOV/poses.txt --background data/cache/backgrounds.pk

`
The segmentation fault error doesn't happen every time but still often happen. Has anyone encountered this ? Is the memory allocation warning linked to the segmentation fault ? Do I have not enough RAM on my computer ?

My current setting is :
Ubuntu 16.04 with Memory : 5.8
Cuda 8.0 with cuDNN 7
Tensorflow 1.8
GPU : NVIDIA GEFORCE 840M

Demo tries to use vgg16_conv, but only defines vgg16

Hello, after a lot of version conflicts I managed to compile :-)

Running demo.sh fails with "KeyError: 'Unknown network: vgg16_conv'" though.
I can understand this since with __C.TRAIN.SINGLE_FRAME = False in fcn/config.py
networks/factory.py only defines vgg16.

So from my understanding demo.sh can not work as it is checked in right now.

A simple change from --network vgg16_conf to vgg16 does not help and fails with other errors.
Thanks for any help towards a working demo.

implementation problem

hi, i have two questions for asking
1, when i do ./experiments/scripts/demo.sh, i just run this script and it happens an error like below
"AssertionError: Data path does not exist: ../../data/LOV/data". i hope to know whether i need to download the YCB-Video dataset when run this demo.sh.
2, The size of the YCB-Video dataset is two large, about 256G, and not easy to save on disk. can you give a small one, or separate the dataset to a small set.
Appreciate your reply!

KeyError: 'Unknown network: vgg16_convs'

I get the following error when I run ./experiments/scripts/lov_color_2d_train.sh 0

Traceback (most recent call last):
  File "./tools/train_net.py", line 328, in <module>
    network = get_network(args.network_name)
  File "/home/nivedithak/Downloads/PoseCNN-master/tools/../lib/networks/factory.py", line 50, in get_network
    raise KeyError('Unknown network: {}'.format(name))
KeyError: 'Unknown network: vgg16_convs'

I am not sure what is causing this considering the vgg16_convs file exists and is one of the imported networks.

Demo dependencies missing - ImportError: cannot import name gpu_normals

I am trying to run ./experiments/scripts/demo.sh 0

I have installed following till now:-

pip install opencv-contrib-python==3.4.1.15
conda install scipy
sudo apt-get install python3-setuptools
pip install cython
pip install -U pip setuptools
pip install transforms3d

I am currently stuck with ImportError: cannot import name gpu_normals. Please could you suggest which library this is?

Ofcourse, would help others if you add these dependencies to readme with versions as well.

ImportError: No module named libsynthesizer

When I tried to run the training demo
./experiments/scripts/lov_color_2d_train.sh $GPU_ID
there was the following error:

File "./tools/train_net.py", line 303, in <module>
    import libsynthesizer
ImportError: No module named libsynthesizer

So I tried to compile setup.py
python setup.py build_ext --inplace
but it failed because of missing synthesizer.hpp:

synthesize/synthesizer.cpp:588:27: fatal error: synthesizer.hpp: No such file or directory
compilation terminated.

(There's only synthesize.hpp in $ROOT/lib/synthesize/ but no synthesizer.hpp)

Is the synthesizer.hpp missing / could you please add the file to the github repository?
Or is there another solution to this problem?
Thanks for help.

versions of libraries

Hi,

You used so many third-party libraries and softwares in your code. If you have time, could you please list out the versions of these libraries or softwares? Then at least we will not be confused by the combination of different versions. Thanks very much.

False/hard annotations with occluded objects

I am currently looking at the YCB-video dataset and noticed that there might be occlusions that are "too hard":
e.g. the sugar box in the image below

Is there a flag for hard occlusions in the dataset?
Were these annotations used to train poseCNN?

Thank you.

cudaCheckError() failed compute outputs: too many resources requested for launch

I get this error while trying to run ./experiments/scripts/demo.sh 0 :

2018-07-06 12:51:54.564555: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:892] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2018-07-06 12:51:54.565020: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1030] Found device 0 with properties: 
name: GeForce 840M major: 5 minor: 0 memoryClockRate(GHz): 1.124
pciBusID: 0000:0a:00.0
totalMemory: 1.96GiB freeMemory: 1.73GiB
2018-07-06 12:51:54.565060: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1120] Creating TensorFlow device (/device:GPU:0) -> (device: 0, name: GeForce 840M, pci bus id: 0000:0a:00.0, compute capability: 5.0)
Loading model weights from data/demo_models/vgg16_fcn_color_single_frame_2d_pose_add_lov_iter_160000.ckpt
data/demo_images/000003-color.png
2018-07-06 12:51:56.557339: W tensorflow/core/common_runtime/bfc_allocator.cc:217] Allocator (GPU_0_bfc) ran out of memory trying to allocate 2.76GiB. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory is available.
2018-07-06 12:51:56.736688: W tensorflow/core/common_runtime/bfc_allocator.cc:217] Allocator (GPU_0_bfc) ran out of memory trying to allocate 675.00MiB. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory is available.
2018-07-06 12:51:56.956865: W tensorflow/core/common_runtime/bfc_allocator.cc:217] Allocator (GPU_0_bfc) ran out of memory trying to allocate 1.98GiB. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory is available.
2018-07-06 12:51:57.085750: W tensorflow/core/common_runtime/bfc_allocator.cc:217] Allocator (GPU_0_bfc) ran out of memory trying to allocate 337.50MiB. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory is available.
2018-07-06 12:51:57.158900: W tensorflow/core/common_runtime/bfc_allocator.cc:217] Allocator (GPU_0_bfc) ran out of memory trying to allocate 2.64GiB. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory is available.
2018-07-06 12:51:57.328548: W tensorflow/core/common_runtime/bfc_allocator.cc:217] Allocator (GPU_0_bfc) ran out of memory trying to allocate 1017.00MiB. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory is available.
2018-07-06 12:51:57.572087: W tensorflow/core/common_runtime/bfc_allocator.cc:217] Allocator (GPU_0_bfc) ran out of memory trying to allocate 1.33GiB. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory is available.
2018-07-06 12:51:57.769324: W tensorflow/core/common_runtime/bfc_allocator.cc:217] Allocator (GPU_0_bfc) ran out of memory trying to allocate 524.25MiB. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory is available.
2018-07-06 12:51:58.011584: W tensorflow/core/common_runtime/bfc_allocator.cc:217] Allocator (GPU_0_bfc) ran out of memory trying to allocate 711.00MiB. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory is available.
cudaCheckError() failed compute outputs: too many resources requested for launch

I guess that this is due to the fact that my GPU card doesn't have enough memory. Is there a way to avoid this error without changing my GPU card ?

How to use test_ros_bag.sh with a custom rosbag?

Could you provide a small example how you used this script? Right now the repository is missing 011_banana_train.txt(I get an assertion error when running test_ros_bag.sh) and I'm unsure what should be in it. I tried to run the file with the same settings like the demo just adding my bag, but then tensorflow segfaults.

the format of the YCB-Video dataset

I can't access the YCB-Video dataset because of the limited internet in China.
Now I want to know the format of the dataset, so that I can make my own dataset. Thank you very much!

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