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when I use SSD.ipynb or SSD_Train.ipynb, (keras-2.3.1 or 2.1.5 both failed)
model=model = SSD(input_shape, num_classes=NUM_CLASSES) always cause Error as below:
ValueError: A Concatenate layer requires inputs with matching shapes except for the concat axis. Got inputs shapes: [(None, 1917, 4), (None, 1917, 21), (None, 114432, 8)]
error is caused by merge of the 3 nets at line #186 of ssd300MobileNet.py
net['predictions'] = concatenate([net['mbox_loc'],net['mbox_conf'],net['mbox_priorbox']],axis=2,name='predictions')
how to fix the shape mismatch of these 3 nets ?
The text was updated successfully, but these errors were encountered:
rkuo2000
changed the title
ssd300MobileNet error
ssd300MobileNet layer concatenate error
Jan 10, 2020
The fix is to modify ssd_layers.py line #32 and #84 :
if K.image_dim_ordering() == 'tf': to if K.image_data_format() == 'channels_last':
Then it runs !
when I use SSD.ipynb or SSD_Train.ipynb, (keras-2.3.1 or 2.1.5 both failed)
model=model = SSD(input_shape, num_classes=NUM_CLASSES) always cause Error as below:
ValueError: A
Concatenate
layer requires inputs with matching shapes except for the concat axis. Got inputs shapes: [(None, 1917, 4), (None, 1917, 21), (None, 114432, 8)]error is caused by merge of the 3 nets at line #186 of ssd300MobileNet.py
net['predictions'] = concatenate([net['mbox_loc'],net['mbox_conf'],net['mbox_priorbox']],axis=2,name='predictions')
how to fix the shape mismatch of these 3 nets ?
The text was updated successfully, but these errors were encountered: