Epoch 1/100
13097/13097 [==============================] - 5262s 402ms/step - loss: 2.8854 - acc: 0.8722 - iou: 0.2555 - val_loss: 5.3026 - val_acc: 0.9111 - val_iou: 0.2434
Epoch 00001: saving model to seg_hrnet-01-5.3026-0.9111-0.2434.hdf5
Epoch 2/100
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InvalidArgumentError: Inputs to operation loss/Classification_loss/logistic_loss/Select of type Select must have the same size and shape. Input 0: [2,1,512,512] != input 1: [1,1,512,512]
Problem: a mismatch occurs batch dimensions, the causes, the picture / batchsize not divisible.
My situation here is batch = 2, so the final picture does not divide the remaining one, cause this error.
That is, to change it batch_generater, in its interior, if detection of the index exceeded the number of pictures, take it from the beginning.
My sample code is as follows:
# 获取batch data
def batch_generator(train_images_paths, batch_size, flag):
while 1:
for i in range(0, len(train_images_paths), batch_size):
idx_start = 0 if (i + batch_size) > len(train_images_paths) else i
idx_end = idx_start + batch_size
if flag == 'train':
images, slic_seg, gts = read_train_img(train_images_paths[idx_start: idx_end])
else:
images, slic_seg, gts = read_test_img(train_images_paths[idx_start: idx_end])
yield ([images, slic_seg], [gts])
