Convert to AWNN online about maix_train

[diazGT94]

@JuanDavidBarrero You should put the name of the images that you'll use for training and for validation. For example I used a dataset of 600 images and the name of the image was a number. E.g 1.jpg, 2.jpg, ... , 600.jpg. Then with a python script I randomly distributed the numbers into train.txt and val.txt

[JuanDavidBarrero]

Could you help me? I don't know what to put in ImageSets/Main/train.txt and ImageSets/Main/val.txt, i leaved it empty but this error pops up

Loading the pretrained model ...
Loading the darknet_tiny ...
2021-12-01 20:10:26.889082: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libcudart.so.10.1
2021-12-01 20:10:27 - [DEBUG] - [MainProcess - MainThread] Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
2021-12-01 20:10:28 - [INFO] - [MainProcess - MainThread]  check dataset in train
Traceback (most recent call last):
  File "train.py", line 193, in <module>
    train.load_dataset(F"detectore/datasets/{dataset_name}", load_num_workers = 16)
  File "train.py", line 78, in load_dataset
    transform = SSDAugmentation(size=(self.input_shape[2], self.input_shape[1]), mean=(0.5, 0.5, 0.5), std=(128/255.0, 128/255.0, 128/255.0))
  File "/content/maix_train/pytorch/detector/dataset.py", line 104, in __init__
    if i % int(len(lines) * 0.05) == 0:
ZeroDivisionError: integer division or modulo by zero

[JuanDavidBarrero]

Thanks, it works !

[diazGT94]

@JuanDavidBarrero where you able to convert your trained model using the online converter tool?

[JuanDavidBarrero]

I tried but in the end got these results.

I don't know why this always throws me an error, And also when I run the example of yolo given by them with the number model, the maix dock II restarts

Have you been able to execute it?

[diazGT94]

@JuanDavidBarrero No because I can even upload my .zip folder to the converter. I mailed the sipeed guys couple of days ago regarding this issue and they told me they are working on an offline converter tool. May I ask what are the parameters of your model? How is the structure of the zip folder your trying to submit? Which pytorch version you used for train your model?

[JuanDavidBarrero]

@diazGT94 This is the structure in the zip file that I uploaded, in the images folder I put some of the validation images, not all of them, or the zip gets too heavy to upload

this is the .param file i worked with 224x224 images

7767517
28 28
Input            input0                   0 1 input0 0=224 1=224 =2=3
Convolution      Conv_0                   1 1 input0 148 0=32 1=3 11=3 2=1 12=1 3=1 13=1 4=1 14=1 15=1 16=1 5=1 6=864
ReLU             LeakyRelu_1              1 1 148 110 0=1.000000e-01
Convolution      Conv_2                   1 1 110 151 0=32 1=3 11=3 2=1 12=1 3=2 13=2 4=1 14=1 15=1 16=1 5=1 6=9216
ReLU             LeakyRelu_3              1 1 151 113 0=1.000000e-01
Convolution      Conv_4                   1 1 113 154 0=64 1=3 11=3 2=1 12=1 3=1 13=1 4=1 14=1 15=1 16=1 5=1 6=18432
ReLU             LeakyRelu_5              1 1 154 116 0=1.000000e-01
Convolution      Conv_6                   1 1 116 157 0=64 1=3 11=3 2=1 12=1 3=2 13=2 4=1 14=1 15=1 16=1 5=1 6=36864
ReLU             LeakyRelu_7              1 1 157 119 0=1.000000e-01
Convolution      Conv_8                   1 1 119 160 0=128 1=3 11=3 2=1 12=1 3=1 13=1 4=1 14=1 15=1 16=1 5=1 6=73728
ReLU             LeakyRelu_9              1 1 160 122 0=1.000000e-01
Convolution      Conv_10                  1 1 122 163 0=128 1=3 11=3 2=1 12=1 3=2 13=2 4=1 14=1 15=1 16=1 5=1 6=147456
ReLU             LeakyRelu_11             1 1 163 125 0=1.000000e-01
Convolution      Conv_12                  1 1 125 166 0=256 1=3 11=3 2=1 12=1 3=1 13=1 4=1 14=1 15=1 16=1 5=1 6=294912
ReLU             LeakyRelu_13             1 1 166 128 0=1.000000e-01
Convolution      Conv_14                  1 1 128 169 0=256 1=3 11=3 2=1 12=1 3=2 13=2 4=1 14=1 15=1 16=1 5=1 6=589824
ReLU             LeakyRelu_15             1 1 169 131 0=1.000000e-01
Convolution      Conv_16                  1 1 131 172 0=512 1=3 11=3 2=1 12=1 3=1 13=1 4=1 14=1 15=1 16=1 5=1 6=1179648
ReLU             LeakyRelu_17             1 1 172 134 0=1.000000e-01
Convolution      Conv_18                  1 1 134 175 0=512 1=3 11=3 2=1 12=1 3=2 13=2 4=1 14=1 15=1 16=1 5=1 6=2359296
ReLU             LeakyRelu_19             1 1 175 137 0=1.000000e-01
Convolution      Conv_20                  1 1 137 178 0=512 1=3 11=3 2=1 12=1 3=1 13=1 4=1 14=1 15=1 16=1 5=1 6=2359296
ReLU             LeakyRelu_21             1 1 178 140 0=1.000000e-01
Convolution      Conv_22                  1 1 140 181 0=512 1=3 11=3 2=1 12=1 3=1 13=1 4=1 14=1 15=1 16=1 5=1 6=2359296
ReLU             LeakyRelu_23             1 1 181 143 0=1.000000e-01
Convolution      Conv_24                  1 1 143 184 0=512 1=3 11=3 2=1 12=1 3=1 13=1 4=1 14=1 15=1 16=1 5=1 6=2359296
ReLU             LeakyRelu_25             1 1 184 146 0=1.000000e-01
Convolution      Conv_26                  1 1 146 output0 0=30 1=1 11=1 2=1 12=1 3=1 13=1 4=0 14=0 15=0 16=0 5=1 6=15360

finally this is the version of pytorch that i used

>>>import torch
>>>print(torch.__version__)
1.10.0+cu111