Hi,
When I check the folder of my images by below code, there is no corrupted images.
but when I use a custom dataset and start to train the network this error happens during training (it does not stop the training and it will go on after that, but I do not know if it affect the parameters being trained and I wonder how I can handle this).
Thanks,
Epoch: 0
Corrupt JPEG data: 24 extraneous bytes before marker 0xd9
[===========================================================>…]  Step: 147ms | Tot: 11s720ms | Loss: 1.285 | Acc: 57.554% (640/111 12/12 2
[====================================================>…]  Step: 883ms | Tot: 4s311ms | Loss: 0.665 | Acc: 60.587% (289/47 5/5 5
Saving…
annotations = pd.read_csv(datapath, sep=’\t’)
root_dir=’/home/ubuntu/files’
for index in range(len(annotations)):
img_path = os.path.join(root_dir, annotations.loc[index, ‘image_path’])
try:
img = Image.open(img_path)
img.verify()
except:
print(‘Bad file:’, index) # print out the names of corrupt files