daveredrum / d3net Goto Github PK

Thanks for sharing this great work!

I am currently hitting an issue while running the evaluation for the pointgroup detector using the checkpoint file you shared.
python scripts/eval.py --folder <output_folder> --task detection

Output:
Traceback (most recent call last):
File "scripts/eval.py", line 522, in
model = init_model(cfg, dataset)
File "scripts/eval.py", line 121, in init_model
model.load_state_dict(checkpoint["state_dict"], strict=False)
File "/home/rajrup/miniconda3/envs/d3net-original/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1406, in load_state_dict
raise RuntimeError('Error(s) in loading state_dict for {}:\n\t{}'.format(
RuntimeError: Error(s) in loading state_dict for PipelineNet:
size mismatch for embeddings: copying a param with shape torch.Size([3441, 300]) from checkpoint, the shape in current model is torch.Size([3535, 300]).
size mismatch for speaker.caption.embeddings: copying a param with shape torch.Size([3441, 300]) from checkpoint, the shape in current model is torch.Size([3535, 300]).
size mismatch for speaker.caption.classifier.2.weight: copying a param with shape torch.Size([3441, 512]) from checkpoint, the shape in current model is torch.Size([3535, 512]).
size mismatch for speaker.caption.classifier.2.bias: copying a param with shape torch.Size([3441]) from checkpoint, the shape in current model is torch.Size([3535]).

The dimension of the tensors in checkpoint doesn't match the one required in the code. Before the model load step, the val splits, and the vocabulary loads fine. I might be missing something here. Can you please help me solve this issue?

Thanks!

It refers to scan2cap.

Besides, missing file conf/pointgroup-speaker-listener.yaml

hi @daveredrum

I'm getting the following error on executing the command below on colab terminal:

Command:
/content/D3Net/data/scannet# python prepare_scannet.py

Error:
data split: train
scene0000_00
Traceback (most recent call last):
File "prepare_scannet.py", line 222, in
process_all_scans(cfg)
File "prepare_scannet.py", line 205, in process_all_scans
process_one_scan(scan, cfg)
File "prepare_scannet.py", line 181, in process_one_scan
mesh, aligned_mesh, sem_labels, instance_ids, instance_bboxes, aligned_instance_bboxes = export(scan, cfg)
File "prepare_scannet.py", line 146, in export
mesh = read_mesh_file(mesh_file) #（num_verts, 9) xyz+rgb+normal
File "prepare_scannet.py", line 30, in read_mesh_file
mesh = scannet_utils.read_mesh_vertices_rgb_normal(mesh_file) #（num_verts, 9) xyz+rgb+normal
File "/content/D3Net/data/scannet/scannet_utils.py", line 119, in read_mesh_vertices_rgb_normal
assert(os.path.isfile(filename))
AssertionError

Is it possible that I'm doing something incorrectly in

I'm not entirely sure what is to be done here

Hi @daveredrum ,

I follow the instruction in README to train the PointGroup Detector, but the mAP@50 is around 32, which is quite low.

python scripts/train.py --config conf/pointgroup.yaml

I test the given checkpoint, and I can get the result of 50 mAP@50. So I guess there is something wrong with the given training hyper-parameters. Can you check it?

Thanks for your help.

Best

Hello,
I encountered an issue while trying to execute python scripts/train.py --config conf/pointgroup.yaml I got the error message TypeError: file must have 'read' and 'readline' attributes.

I could fix it by changing line 451 in lib/dataset/pipeline.py to:

with open(self.cfg["{}_PATH".format(self.name.upper())].glove_pickle, 'rb') as pickle_file:
                    glove = pickle.load(pickle_file)