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ValueError: A Concatenate
layer should be called on a list of at least 1 input. Received: input_shape=[[(None, 480, 640, 1)], (None, 480, 640, 3)]
#4
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same issue |
I have same issue. |
I have the same issue, any one find a solution please?! |
please do you find a solution ? |
in model/model.py in build_combine_model function |
Command - python predict.py -dataroot testImg -datatype tif -predictpath output -batch_size 3
import end
Read img from: testImg
Len of the file: 3
[||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||] 100.0% ...Loading data...
(3, 480, 640, 3) data shape
2022-01-25 10:51:29.790963: W tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:39] Overriding allow_growth setting because the TF_FORCE_GPU_ALLOW_GROWTH environment variable is set. Original config value was 0.
Build TR
Traceback (most recent call last):
File "predict.py", line 95, in
modelRecoverCombine = model.model.build_combine_model()
File "/content/JSTASR-DesnowNet-ECCV-2020/model/model.py", line 181, in build_combine_model
TRinp=Concatenate(axis=3)([pmrc,inp])
File "/usr/local/lib/python3.7/dist-packages/keras/utils/traceback_utils.py", line 67, in error_handler
raise e.with_traceback(filtered_tb) from None
File "/usr/local/lib/python3.7/dist-packages/keras/layers/merge.py", line 499, in build
'A
Concatenate
layer should be called on a list of 'ValueError: A
Concatenate
layer should be called on a list of at least 1 input. Received: input_shape=[[(None, 480, 640, 1)], (None, 480, 640, 3)]Facing this issue when trying to use the pretrained model and running predict.py
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