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qqwweee / keras-yolo3

A Keras implementation of YOLOv3 (Tensorflow backend)
MIT License
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train.py #299

Open abhishekvarma23 opened 5 years ago

abhishekvarma23 commented 5 years ago

How to solve the list Index error while training the network.

Traceback (most recent call last): File "train.py", line 190, in _main() File "train.py", line 65, in _main callbacks=[logging, checkpoint]) File "/home/isemes/anaconda3/envs/tf-gpu/lib/python3.5/site-packages/keras/legacy/interfaces.py", line 91, in wrapper return func(*args, **kwargs) File "/home/isemes/anaconda3/envs/tf-gpu/lib/python3.5/site-packages/keras/engine/training.py", line 2192, in fit_generator generator_output = next(output_generator) File "/home/isemes/anaconda3/envs/tf-gpu/lib/python3.5/site-packages/keras/utils/data_utils.py", line 793, in get six.reraise(value.class, value, value.traceback) File "/home/isemes/anaconda3/envs/tf-gpu/lib/python3.5/site-packages/six.py", line 693, in reraise raise value File "/home/isemes/anaconda3/envs/tf-gpu/lib/python3.5/site-packages/keras/utils/data_utils.py", line 658, in _data_generator_task generator_output = next(self._generator) File "train.py", line 175, in data_generator image, box = get_random_data(annotation_lines[i], input_shape, random=True) File "/home/isemes/Music/keras-yolo3-master/yolo3/utils.py", line 39, in get_random_data image = Image.open(line[0]) IndexError: list index out of range

abhishekvarma23 commented 5 years ago

How to solve the list Index error while training the network.

Traceback (most recent call last): File "train.py", line 190, in _main() File "train.py", line 65, in _main callbacks=[logging, checkpoint]) File "/home/isemes/anaconda3/envs/tf-gpu/lib/python3.5/site-packages/keras/legacy/interfaces.py", line 91, in wrapper return func(*args, kwargs) File "/home/isemes/anaconda3/envs/tf-gpu/lib/python3.5/site-packages/keras/engine/training.py", line 2192, in fit_generator generator_output = next(output_generator) File "/home/isemes/anaconda3/envs/tf-gpu/lib/python3.5/site-packages/keras/utils/data_utils.py", line 793, in get six.reraise(value.class, value, value.traceback**) File "/home/isemes/anaconda3/envs/tf-gpu/lib/python3.5/site-packages/six.py", line 693, in reraise raise value File "/home/isemes/anaconda3/envs/tf-gpu/lib/python3.5/site-packages/keras/utils/data_utils.py", line 658, in _data_generator_task generator_output = next(self._generator) File "train.py", line 175, in data_generator image, box = get_random_data(annotation_lines[i], input_shape, random=True) File "/home/isemes/Music/keras-yolo3-master/yolo3/utils.py", line 39, in get_random_data image = Image.open(line[0]) IndexError: list index out of range

@qqwweee Please help me to solve the issue

Thanks in advance

AryaCao commented 5 years ago

what is in your train.txt? It seems to be that the train.txt line is wrong

abhishekvarma23 commented 5 years ago

what is in your train.txt? It seems to be that the train.txt line is wrong

###########Train.txt################################

Input data image size:1920*1080

C:\imgs1\vlcsnap-2018-07-21-18h42m15s301.png 180,485,462,741,0 1422,388,1675,625,1 C:\imgs1\vlcsnap-2018-07-23-16h37m17s162.png 175,201,462,474,0 84,808,384,1063,1 C:\imgs1\vlcsnap-2018-07-23-16h43m47s473.png 1377,699,1677,919,0 C:\imgs1\vlcsnap-2018-07-23-16h44m27s588.png 268,65,537,303,1 673,88,927,291,1 C:\imgs1\vlcsnap-2018-07-23-16h44m52s559.png 273,280,560,536,0 C:\imgs1\vlcsnap-2018-07-23-16h45m45s321.png 13,161,277,416,0 C:\imgs1\vlcsnap-2018-07-23-16h46m41s963.png 271,85,544,310,0 C:\imgs1\vlcsnap-2018-07-23-16h47m01s435.png 244,214,553,445,1 C:\imgs1\vlcsnap-2018-07-23-16h48m35s403.png 126,250,428,503,0 462,276,731,510,0 C:\imgs1\vlcsnap-2018-07-23-16h52m02s836.png 260,570,557,816,0 1404,400,1651,601,1 C:\imgs1\vlcsnap-2018-07-23-16h52m16s567.png 273,210,533,434,0 141,374,1677,605,1 C:\imgs1\vlcsnap-2018-07-23-17h39m19s389.png 276,185,554,421,1 1386,392,1668,612,1 C:\imgs1\vlcsnap-2018-07-23-17h39m39s510.png 385,199,656,412,0 1380,383,1677,625,1 C:\imgs1\vlcsnap-2018-07-23-17h39m54s920.png 366,681,684,943,0 1406,390,1688,632,1

#############Train File############################

annotation_path = ('train1.txt') log_dir = 'logs/000/' classes_path = 'model_data/classfile.txt' anchors_path = 'model_data/yolo_anchors.txt' class_names = get_classes(classes_path) num_classes = len(class_names) anchors = get_anchors(anchors_path)

input_shape = (416,416) # multiple of 32, hw

###############Error(Training Pattern) with 120 Images ###############################

Create YOLOv3 model with 9 anchors and 2 classes. Load weights model_data/yolo_weights.h5. Freeze the first 249 layers of total 252 layers. Train on 110 samples, val on 12 samples, with batch size 1. Epoch 1/50

1/110 [..............................] - ETA: 1:02:52 - loss: 6837.2021 2/110 [..............................] - ETA: 31:18 - loss: 6823.4150  3/110 [..............................] - ETA: 20:49 - loss: 6808.2749 4/110 [>.............................] - ETA: 15:33 - loss: 6795.0779 5/110 [>.............................] - ETA: 12:24 - loss: 6776.8220 6/110 [>.............................] - ETA: 10:18 - loss: 6758.4811 7/110 [>.............................] - ETA: 8:47 - loss: 6742.9335  8/110 [=>............................] - ETA: 7:39 - loss: 6723.7268 9/110 [=>............................] - ETA: 6:46 - loss: 6705.6183 10/110 [=>............................] - ETA: 6:03 - loss: 6687.0032 11/110 [==>...........................] - ETA: 5:29 - loss: 6667.8527 12/110 [==>...........................] - ETA: 5:00 - loss: 6648.6914 13/110 [==>...........................] - ETA: 4:36 - loss: 6629.6406 14/110 [==>...........................] - ETA: 4:14 - loss: 6611.4614 15/110 [===>..........................] - ETA: 3:56 - loss: 6592.5941 16/110 [===>..........................] - ETA: 3:40 - loss: 6573.6660 17/110 [===>..........................] - ETA: 3:26 - loss: 6555.0974 18/110 [===>..........................] - ETA: 3:14 - loss: 6536.2294 19/110 [====>.........................] - ETA: 3:02 - loss: 6517.4622 20/110 [====>.........................] - ETA: 2:52 - loss: 6498.8002 21/110 [====>.........................] - ETA: 2:43 - loss: 6480.1095 22/110 [=====>........................] - ETA: 2:35 - loss: 6463.1071 23/110 [=====>........................] - ETA: 2:27 - loss: 6444.5291 24/110 [=====>........................] - ETA: 2:20 - loss: 6425.9446 25/110 [=====>........................] - ETA: 2:14 - loss: 6407.5146 26/110 [======>.......................] - ETA: 2:08 - loss: 6389.1994 27/110 [======>.......................] - ETA: 2:03 - loss: 6370.9553 28/110 [======>.......................] - ETA: 1:58 - loss: 6353.2001 29/110 [======>.......................] - ETA: 1:53 - loss: 6334.9555 30/110 [=======>......................] - ETA: 1:49 - loss: 6316.9706 31/110 [=======>......................] - ETA: 1:45 - loss: 6298.9556 32/110 [=======>......................] - ETA: 1:41 - loss: 6281.1080 33/110 [========>.....................] - ETA: 1:37 - loss: 6263.1779 34/110 [========>.....................] - ETA: 1:34 - loss: 6245.3073 35/110 [========>.....................] - ETA: 1:30 - loss: 6227.5681 36/110 [========>.....................] - ETA: 1:27 - loss: 6209.8360 37/110 [=========>....................] - ETA: 1:24 - loss: 6192.2246 38/110 [=========>....................] - ETA: 1:22 - loss: 6174.7103 39/110 [=========>....................] - ETA: 1:19 - loss: 6158.0128 40/110 [=========>....................] - ETA: 1:16 - loss: 6140.5929 41/110 [==========>...................] - ETA: 1:14 - loss: 6123.1823 42/110 [==========>...................] - ETA: 1:12 - loss: 6105.9018 43/110 [==========>...................] - ETA: 1:09 - loss: 6088.9188 44/110 [===========>..................] - ETA: 1:07 - loss: 6072.4373 45/110 [===========>..................] - ETA: 1:05 - loss: 6055.4702 46/110 [===========>..................] - ETA: 1:03 - loss: 6038.4319 47/110 [===========>..................] - ETA: 1:01 - loss: 6021.5183 48/110 [============>.................] - ETA: 59s - loss: 6005.1967  49/110 [============>.................] - ETA: 58s - loss: 5988.3882 50/110 [============>.................] - ETA: 56s - loss: 5971.6597 51/110 [============>.................] - ETA: 55s - loss: 5955.0506 52/110 [=============>................] - ETA: 53s - loss: 5938.4933 53/110 [=============>................] - ETA: 51s - loss: 5921.9256 54/110 [=============>................] - ETA: 50s - loss: 5905.4772 Warning (from warnings module): File "C:\Users\Abhishek\AppData\Local\Programs\Python\Python36\lib\site-packages\keras\callbacks.py", line 122 % delta_t_median) UserWarning: Method on_batch_end() is slow compared to the batch update (0.182816). Check your callbacks.  55/110 [==============>...............] - ETA: 49s - loss: 5889.1740 Warning (from warnings module): File "C:\Users\Abhishek\AppData\Local\Programs\Python\Python36\lib\site-packages\keras\callbacks.py", line 122 % delta_t_median) UserWarning: Method on_batch_end() is slow compared to the batch update (0.172746). Check your callbacks.  56/110 [==============>...............] - ETA: 47s - loss: 5872.9922 57/110 [==============>...............] - ETA: 46s - loss: 5856.7600 58/110 [==============>...............] - ETA: 44s - loss: 5840.6051 Warning (from warnings module): File "C:\Users\Abhishek\AppData\Local\Programs\Python\Python36\lib\site-packages\keras\callbacks.py", line 122 % delta_t_median) UserWarning: Method on_batch_end() is slow compared to the batch update (0.163192). Check your callbacks.  59/110 [===============>..............] - ETA: 43s - loss: 5824.5102 60/110 [===============>..............] - ETA: 41s - loss: 5808.4763 61/110 [===============>..............] - ETA: 40s - loss: 5792.5592 62/110 [===============>..............] - ETA: 39s - loss: 5776.7299 63/110 [================>.............] - ETA: 38s - loss: 5760.9184 64/110 [================>.............] - ETA: 36s - loss: 5745.1704 65/110 [================>.............] - ETA: 35s - loss: 5729.4931 66/110 [=================>............] - ETA: 34s - loss: 5714.0763 67/110 [=================>............] - ETA: 33s - loss: 5698.5413 68/110 [=================>............] - ETA: 32s - loss: 5683.0661 69/110 [=================>............] - ETA: 31s - loss: 5667.6950 70/110 [==================>...........] - ETA: 30s - loss: 5652.3257 71/110 [==================>...........] - ETA: 29s - loss: 5637.1168 72/110 [==================>...........] - ETA: 28s - loss: 5621.9181Traceback (most recent call last): File "C:\Users\Abhishek\Documents\keras-yolo3-f4a9c40f4615cdbb774942507ecad3af5f05c990\train.py", line 190, in _main() File "C:\Users\Abhishek\Documents\keras-yolo3-f4a9c40f4615cdbb774942507ecad3af5f05c990\train.py", line 65, in _main callbacks=[logging, checkpoint]) File "C:\Users\Abhishek\AppData\Local\Programs\Python\Python36\lib\site-packages\keras\legacy\interfaces.py", line 91, in wrapper return func(*args, kwargs) File "C:\Users\Abhishek\AppData\Local\Programs\Python\Python36\lib\site-packages\keras\engine\training.py", line 1418, in fit_generator initial_epoch=initial_epoch) File "C:\Users\Abhishek\AppData\Local\Programs\Python\Python36\lib\site-packages\keras\engine\training_generator.py", line 181, in fit_generator generator_output = next(output_generator) File "C:\Users\Abhishek\AppData\Local\Programs\Python\Python36\lib\site-packages\keras\utils\data_utils.py", line 709, in get six.reraise(sys.exc_info()) File "C:\Users\Abhishek\AppData\Local\Programs\Python\Python36\lib\site-packages\six.py", line 693, in reraise raise value File "C:\Users\Abhishek\AppData\Local\Programs\Python\Python36\lib\site-packages\keras\utils\data_utils.py", line 685, in get inputs = self.queue.get(block=True).get() File "C:\Users\Abhishek\AppData\Local\Programs\Python\Python36\lib\multiprocessing\pool.py", line 644, in get raise self._value File "C:\Users\Abhishek\AppData\Local\Programs\Python\Python36\lib\multiprocessing\pool.py", line 119, in worker result = (True, func(args, kwds)) File "C:\Users\Abhishek\AppData\Local\Programs\Python\Python36\lib\site-packages\keras\utils\data_utils.py", line 626, in next_sample return six.next(_SHARED_SEQUENCES[uid]) File "C:\Users\Abhishek\Documents\keras-yolo3-f4a9c40f4615cdbb774942507ecad3af5f05c990\train.py", line 175, in data_generator image, box = get_random_data(annotation_lines[i], input_shape, random=True) File "C:\Users\Abhishek\Documents\keras-yolo3-f4a9c40f4615cdbb774942507ecad3af5f05c990\yolo3\utils.py", line 39, in get_random_data image = Image.open(line[0]) IndexError: list index out of range

@sunflowercao thanks for the reply The above two represents my train.py and train.txt file

Can you please check and help me about the issue

Thanks in advance

abhishekvarma23 commented 5 years ago

@AryaCao do i need to change to input shape (19201080) to (19201088) #multiple of 32 ?

AryaCao commented 5 years ago

the train.txt only contain the train_data_line like this: 2018-12-20 19-42-42 do you have contain the line:'Input data image size:1920*1080'? "line[0]:list index out of range:" , may be the line is empty, you should check your train.txt, delete the empty line

abhishekvarma23 commented 5 years ago

@AryaCao Thank you so much.

Saved extra lines in the train.txt. Solved the issue now.

sleepless-se commented 5 years ago

Hello! I have same issue.

Traceback (most recent call last):
  File "train.py", line 192, in <module>
    _main()
  File "train.py", line 33, in _main
    freeze_body=2, weights_path='model_data/yolo_weights.h5') # make sure you know what you freeze
  File "train.py", line 132, in create_model
    [*model_body.output, *y_true])
  File "/Users/main/.pyenv/versions/3.5.2/lib/python3.5/site-packages/keras/engine/topology.py", line 619, in __call__
    output = self.call(inputs, **kwargs)
  File "/Users/main/.pyenv/versions/3.5.2/lib/python3.5/site-packages/keras/layers/core.py", line 663, in call
    return self.function(inputs, **arguments)
  File "/Users/main/project/keras-yolo3/yolo3/model.py", line 366, in yolo_loss
    input_shape = K.cast(K.shape(yolo_outputs[0])[1:3] * 32, K.dtype(y_true[0]))
IndexError: list index out of range

But in my case train.txt is like this.

/Users/main/project/keras-yolo3/VOCdevkit/VOC2007/JPEGImages/a01%2520copy%252039.jpg 45,0,232,268,0 /Users/main/project/keras-yolo3/VOCdevkit/VOC2007/JPEGImages/a01%2520copy%252038.jpg 46,141,229,266,0 /Users/main/project/keras-yolo3/VOCdevkit/VOC2007/JPEGImages/a01%2520copy%252037.jpg 82,166,175,275,0 /Users/main/project/keras-yolo3/VOCdevkit/VOC2007/JPEGImages/a01%2520copy%252036.jpg 31,134,193,237,0 /Users/main/project/keras-yolo3/VOCdevkit/VOC2007/JPEGImages/a01%2520copy%252035.jpg 0,0,149,319,0 /Users/main/project/keras-yolo3/VOCdevkit/VOC2007/JPEGImages/a01%2520copy%252034.jpg 0,0,251,320,0 /Users/main/project/keras-yolo3/VOCdevkit/VOC2007/JPEGImages/a01%2520copy%252033.jpg 30,9,253,320,0

Is there any problem or another reason?

Thanks in advance.

sleepless-se commented 5 years ago

I found empty line of the file. Then I deleted and run train.py again. But I have still same error.

sleepless-se commented 5 years ago

I found my fault. I had rewrite anchor_path as anotetion_path. Sorry, It was easy mistake.

    annotation_path = 'train.txt'
    log_dir = 'logs/000/'
    classes_path = 'model_data/voc_classes.txt'
    anchors_path = 'model_data/yolo_anchors.txt' # as 'train.txt'(ERROR)
chaitanya-vardhan123 commented 4 years ago

How can i Solve this problem? Epoch 1/51 Traceback (most recent call last): File "Train_YOLO.py", line 217, in callbacks=[logging, checkpoint], File "C:\Users\AppData\Local\Continuum\anaconda3\lib\site-packages\kera s\legacy\interfaces.py", line 91, in wrapper return func(*args, **kwargs) File "C:\Users\AppData\Local\Continuum\anaconda3\lib\site-packages\kera s\engine\training.py", line 2192, in fit_generator generator_output = next(output_generator) File "C:\Users\AppData\Local\Continuum\anaconda3\lib\site-packages\kera s\utils\data_utils.py", line 793, in get six.reraise(value.class, value, value.traceback) File "C:\Users\AppData\Roaming\Python\Python37\site-packages\six.py", l ine 703, in reraise raise value File "C:\Users\AppData\Local\Continuum\anaconda3\lib\site-packages\kera s\utils\data_utils.py", line 658, in _data_generator_task generator_output = next(self._generator) File "D:\Notsaved\Downloads\TrainYourOwnYOLO-master\TrainYourOwnYOLO-ma ster\Utils\Train_Utils.py", line 194, in data_generator image, box = get_random_data(annotation_lines[i], input_shape, random=True) File "D:\Notsaved\Downloads\TrainYourOwnYOLO-master\TrainYourOwnYOLO-ma ster\2_Training\src\keras_yolo3\yolo3\utils.py", line 66, in get_random_data image = Image.open(line[0]) File "C:\Users\AppData\Local\Continuum\anaconda3\lib\site-packages\PIL\ Image.py", line 2809, in open fp = builtins.open(filename, "rb") FileNotFoundError: [Errno 2] No such file or directory: 'D:/Notsaved/naiduv/Down loads/TrainYourOwnYOLO/-master/'

wyjko commented 4 years ago

How can i Solve this problem? Epoch 1/51 Traceback (most recent call last): File "Train_YOLO.py", line 217, in callbacks=[logging, checkpoint], File "C:\Users\AppData\Local\Continuum\anaconda3\lib\site-packages\kera s\legacy\interfaces.py", line 91, in wrapper return func(*args, kwargs) File "C:\Users\AppData\Local\Continuum\anaconda3\lib\site-packages\kera s\engine\training.py", line 2192, in fit_generator generator_output = next(output_generator) File "C:\Users\AppData\Local\Continuum\anaconda3\lib\site-packages\kera s\utils\data_utils.py", line 793, in get six.reraise(value.class, value, value.traceback**) File "C:\Users\AppData\Roaming\Python\Python37\site-packages\six.py", l ine 703, in reraise raise value File "C:\Users\AppData\Local\Continuum\anaconda3\lib\site-packages\kera s\utils\data_utils.py", line 658, in _data_generator_task generator_output = next(self._generator) File "D:\Notsaved\Downloads\TrainYourOwnYOLO-master\TrainYourOwnYOLO-ma ster\Utils\Train_Utils.py", line 194, in data_generator image, box = get_random_data(annotation_lines[i], input_shape, random=True) File "D:\Notsaved\Downloads\TrainYourOwnYOLO-master\TrainYourOwnYOLO-ma ster\2_Training\src\keras_yolo3\yolo3\utils.py", line 66, in get_random_data image = Image.open(line[0]) File "C:\Users\AppData\Local\Continuum\anaconda3\lib\site-packages\PIL Image.py", line 2809, in open fp = builtins.open(filename, "rb") FileNotFoundError: [Errno 2] No such file or directory: 'D:/Notsaved/naiduv/Down loads/TrainYourOwnYOLO/-master/'

I have the same error ,can you solve it?

raffataldakka commented 4 years ago

I had the same error because I tried to merge tow train.txt files, so when i used voc_annotation.py to generate one train.txt file for all datasets the problem was solved.

chaitanya-vardhan123 commented 4 years ago

U need to work in ubuntu

On Wed, 3 Jun 2020, 12:57 raffataldakka, notifications@github.com wrote:

I had the same error because I tried to merge tow train.txt files, so when i used voc_annotation.py to generate one train.txt file for all datasets the problem was solved.

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jiangxinufo commented 3 years ago

(yolov3-tf2-cpu) N:\MachineLearning\TrainYourOwnYOLO\TrainYourOwnYOLO\2_Training>python Train_YOLO.py Using TensorFlow backend. Create YOLOv3 model with 9 anchors and 1 classes. Load weights N:\MachineLearning\TrainYourOwnYOLO\TrainYourOwnYOLO\2_Training\src\keras_yolo3\yolo.h5. Freeze the first 249 layers of total 252 layers. 8888888888888888888***98888888888888888888888888888888888 ['N:/MachineLearning/TrainYourOwnYOLO/', 'N:/MachineLearning/TrainYourOwnYOLO/', 'N:/MachineLearning/TrainYourOwnYOLO/', 'N:/MachineLearning/TrainYourOwnYOLO/', 'N:/MachineLearning/TrainYourOwnYOLO/', 'N:/MachineLearning/TrainYourOwnYO LO/', 'N:/MachineLearning/TrainYourOwnYOLO/', 'N:/MachineLearning/TrainYourOwnYOLO/', 'N:/MachineLearning/TrainYourOwnYOLO/', 'N:/MachineLearning/TrainYourOwnYOLO/', 'N:/MachineLearning/TrainYourOwnYOLO/', 'N:/MachineLearning/TrainYour OwnYOLO/', 'N:/MachineLearning/TrainYourOwnYOLO/', 'N:/MachineLearning/TrainYourOwnYOLO/', 'N:/MachineLearning/TrainYourOwnYOLO/', 'N:/MachineLearning/TrainYourOwnYOLO/', 'N:/MachineLearning/TrainYourOwnYOLO/', 'N:/MachineLearning/Trai nYourOwnYOLO/', 'N:/MachineLearning/TrainYourOwnYOLO/', 'N:/MachineLearning/TrainYourOwnYOLO/', 'N:/MachineLearning/TrainYourOwnYOLO/', 'N:/MachineLearning/TrainYourOwnYOLO/', 'N:/MachineLearning/TrainYourOwnYOLO/', 'N:/MachineLearning /TrainYourOwnYOLO/', 'N:/MachineLearning/TrainYourOwnYOLO/', 'N:/MachineLearning/TrainYourOwnYOLO/', 'N:/MachineLearning/TrainYourOwnYOLO/', 'N:/MachineLearning/TrainYourOwnYOLO/', 'N:/MachineLearning/TrainYourOwnYOLO/', 'N:/MachineLea rning/TrainYourOwnYOLO/', 'N:/MachineLearning/TrainYourOwnYOLO/', 'N:/MachineLearning/TrainYourOwnYOLO/', 'N:/MachineLearning/TrainYourOwnYOLO/', 'N:/MachineLearning/TrainYourOwnYOLO/', 'N:/MachineLearning/TrainYourOwnYOLO/', 'N:/Machi neLearning/TrainYourOwnYOLO/', 'N:/MachineLearning/TrainYourOwnYOLO/', 'N:/MachineLearning/TrainYourOwnYOLO/', 'N:/MachineLearning/TrainYourOwnYOLO/', 'N:/MachineLearning/TrainYourOwnYOLO/', 'N:/MachineLearning/TrainYourOwnYOLO/', 'N:/ MachineLearning/TrainYourOwnYOLO/', 'N:/MachineLearning/TrainYourOwnYOLO/', 'N:/MachineLearning/TrainYourOwnYOLO/', 'N:/MachineLearning/TrainYourOwnYOLO/', 'N:/MachineLearning/TrainYourOwnYOLO/', 'N:/MachineLearning/TrainYourOwnYOLO/', 'N:/MachineLearning/TrainYourOwnYOLO/', 'N:/MachineLearning/TrainYourOwnYOLO/', 'N:/MachineLearning/TrainYourOwnYOLO/', 'N:/MachineLearning/TrainYourOwnYOLO/', 'N:/MachineLearning/TrainYourOwnYOLO/', 'N:/MachineLearning/TrainYourOwnYO LO/', 'N:/MachineLearning/TrainYourOwnYOLO/', 'N:/MachineLearning/TrainYourOwnYOLO/', 'N:/MachineLearning/TrainYourOwnYOLO/', 'N:/MachineLearning/TrainYourOwnYOLO/', 'N:/MachineLearning/TrainYourOwnYOLO/', 'N:/MachineLearning/TrainYour OwnYOLO/', 'N:/MachineLearning/TrainYourOwnYOLO/', 'N:/MachineLearning/TrainYourOwnYOLO/', 'N:/MachineLearning/TrainYourOwnYOLO/', 'N:/MachineLearning/TrainYourOwnYOLO/', 'N:/MachineLearning/TrainYourOwnYOLO/', 'N:/MachineLearning/Trai nYourOwnYOLO/', 'N:/MachineLearning/TrainYourOwnYOLO/', 'N:/MachineLearning/TrainYourOwnYOLO/', 'N:/MachineLearning/TrainYourOwnYOLO/', 'N:/MachineLearning/TrainYourOwnYOLO/', 'N:/MachineLearning/TrainYourOwnYOLO/', 'N:/MachineLearning /TrainYourOwnYOLO/', 'N:/MachineLearning/TrainYourOwnYOLO/', 'N:/MachineLearning/TrainYourOwnYOLO/', 'N:/MachineLearning/TrainYourOwnYOLO/', 'N:/MachineLearning/TrainYourOwnYOLO/', 'N:/MachineLearning/TrainYourOwnYOLO/', 'N:/MachineLea rning/TrainYourOwnYOLO/', 'N:/MachineLearning/TrainYourOwnYOLO/', 'N:/MachineLearning/TrainYourOwnYOLO/', 'N:/MachineLearning/TrainYourOwnYOLO/', 'N:/MachineLearning/TrainYourOwnYOLO/', 'N:/MachineLearning/TrainYourOwnYOLO/', 'N:/Machi neLearning/TrainYourOwnYOLO/', 'N:/MachineLearning/TrainYourOwnYOLO/', 'N:/MachineLearning/TrainYourOwnYOLO/', 'N:/MachineLearning/TrainYourOwnYOLO/', 'N:/MachineLearning/TrainYourOwnYOLO/', 'N:/MachineLearning/TrainYourOwnYOLO/', 'N:/ MachineLearning/TrainYourOwnYOLO/', 'N:/MachineLearning/TrainYourOwnYOLO/', 'N:/MachineLearning/TrainYourOwnYOLO/', 'N:/MachineLearning/TrainYourOwnYOLO/', 'N:/MachineLearning/TrainYourOwnYOLO/', 'N:/MachineLearning/TrainYourOwnYOLO/', 'N:/MachineLearning/TrainYourOwnYOLO/', 'N:/MachineLearning/TrainYourOwnYOLO/', 'N:/MachineLearning/TrainYourOwnYOLO/', 'N:/MachineLearning/TrainYourOwnYOLO/', 'N:/MachineLearning/TrainYourOwnYOLO/', 'N:/MachineLearning/TrainYourOwnYO LO/'] Train on 90 samples, val on 10 samples, with batch size 32. Traceback (most recent call last): File "Train_YOLO.py", line 265, in callbacks=frozen_callbacks, File "C:\Users\JXHIT.conda\envs\yolov3-tf2-cpu\lib\site-packages\keras\legacy\interfaces.py", line 91, in wrapper return func(*args, kwargs) File "C:\Users\JXHIT.conda\envs\yolov3-tf2-cpu\lib\site-packages\keras\engine\training.py", line 1732, in fit_generator initial_epoch=initial_epoch) File "C:\Users\JXHIT.conda\envs\yolov3-tf2-cpu\lib\site-packages\keras\engine\training_generator.py", line 100, in fit_generator callbacks.set_model(callback_model) File "C:\Users\JXHIT.conda\envs\yolov3-tf2-cpu\lib\site-packages\keras\callbacks\callbacks.py", line 68, in set_model callback.set_model(model) File "C:\Users\JXHIT.conda\envs\yolov3-tf2-cpu\lib\site-packages\tensorflow_core\python\keras\callbacks.py", line 1532, in set_model self.log_dir, self.model._get_distribution_strategy()) # pylint: disable=protected-access AttributeError: 'Model' object has no attribute '_get_distribution_strategy'

help me! thank you!