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Regarding implementation of code in python about dehazing-pmhld-patch-map-based-hybrid-learning-dehazenet-for-single-image-haze-removal-tip-2020 HOT 1 OPEN

weitingchen83 avatar weitingchen83 commented on August 28, 2024
Regarding implementation of code in python

from dehazing-pmhld-patch-map-based-hybrid-learning-dehazenet-for-single-image-haze-removal-tip-2020.

Comments (1)

kumarballapavan avatar kumarballapavan commented on August 28, 2024

Finally I have installed CUDA, CUDNN and also implemented some of the projects. But in this project I face the issue as mentioned below:

TypeError: ('Keyword argument not understood:', 'data_format')

Full Description:

C:\Users\MY DELL\anaconda3\envs\cuda_pytorch\lib\site-packages\tensorflow\python\framework\dtypes.py:526: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
_np_qint8 = np.dtype([("qint8", np.int8, 1)])
C:\Users\MY DELL\anaconda3\envs\cuda_pytorch\lib\site-packages\tensorflow\python\framework\dtypes.py:527: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
_np_quint8 = np.dtype([("quint8", np.uint8, 1)])
C:\Users\MY DELL\anaconda3\envs\cuda_pytorch\lib\site-packages\tensorflow\python\framework\dtypes.py:528: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
_np_qint16 = np.dtype([("qint16", np.int16, 1)])
C:\Users\MY DELL\anaconda3\envs\cuda_pytorch\lib\site-packages\tensorflow\python\framework\dtypes.py:529: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
np_quint16 = np.dtype([("quint16", np.uint16, 1)])
C:\Users\MY DELL\anaconda3\envs\cuda_pytorch\lib\site-packages\tensorflow\python\framework\dtypes.py:530: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
np_qint32 = np.dtype([("qint32", np.int32, 1)])
C:\Users\MY DELL\anaconda3\envs\cuda_pytorch\lib\site-packages\tensorflow\python\framework\dtypes.py:535: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
np_resource = np.dtype([("resource", np.ubyte, 1)])
Using TensorFlow backend.
import end
import end
Read img from: ./testImg
Len of the file: 2
[||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||] 100.0% ...Loading data...
(0,) data shape
----------Build Model----------
import end
Build 10
(480, 640, 3) shape
WARNING:tensorflow:From C:\Users\MY DELL\anaconda3\envs\cuda_pytorch\lib\site-packages\tensorflow\python\framework\op_def_library.py:263: colocate_with (from tensorflow.python.framework.ops) is deprecated and will be removed in a future version.
Instructions for updating:
Colocations handled automatically by placer.
2022-05-14 18:09:01.757747: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2
C:\Users\MY DELL\anaconda3\envs\cuda_pytorch\lib\site-packages\keras\activations.py:115: UserWarning: Do not pass a layer instance (such as bound_relu) as the activation argument of another layer. Instead, advanced activation layers should be used just like any other layer in a model.
identifier=identifier.class.name))
WARNING:tensorflow:From C:\Users\MY DELL\anaconda3\envs\cuda_pytorch\lib\site-packages\keras\backend\tensorflow_backend.py:3138: calling dropout (from tensorflow.python.ops.nn_ops) with keep_prob is deprecated and will be removed in a future version.
Instructions for updating:
Please use rate instead of keep_prob. Rate should be set to rate = 1 - keep_prob.
Traceback (most recent call last):
File "./predict.py", line 109, in
modelRecoverCombine = model.build_combine_model()
File "D:\Study\NIT Research\Dehazing Matlab Codes\python\2020\J PMHLD\PMHLD\model\model.py", line 157, in build_combine_model
modelA = load_model('./modelParam/A.h5')
File "C:\Users\MY DELL\anaconda3\envs\cuda_pytorch\lib\site-packages\keras\models.py", line 243, in load_model
model = model_from_config(model_config, custom_objects=custom_objects)
File "C:\Users\MY DELL\anaconda3\envs\cuda_pytorch\lib\site-packages\keras\models.py", line 317, in model_from_config
return layer_module.deserialize(config, custom_objects=custom_objects)
File "C:\Users\MY DELL\anaconda3\envs\cuda_pytorch\lib\site-packages\keras\layers_init
.py", line 55, in deserialize
printable_module_name='layer')
File "C:\Users\MY DELL\anaconda3\envs\cuda_pytorch\lib\site-packages\keras\utils\generic_utils.py", line 144, in deserialize_keras_object
list(custom_objects.items())))
File "C:\Users\MY DELL\anaconda3\envs\cuda_pytorch\lib\site-packages\keras\engine\topology.py", line 2514, in from_config
process_layer(layer_data)
File "C:\Users\MY DELL\anaconda3\envs\cuda_pytorch\lib\site-packages\keras\engine\topology.py", line 2500, in process_layer
custom_objects=custom_objects)
File "C:\Users\MY DELL\anaconda3\envs\cuda_pytorch\lib\site-packages\keras\layers_init
.py", line 55, in deserialize
printable_module_name='layer')
File "C:\Users\MY DELL\anaconda3\envs\cuda_pytorch\lib\site-packages\keras\utils\generic_utils.py", line 146, in deserialize_keras_object
return cls.from_config(config['config'])
File "C:\Users\MY DELL\anaconda3\envs\cuda_pytorch\lib\site-packages\keras\engine\topology.py", line 1271, in from_config
return cls(**config)
File "C:\Users\MY DELL\anaconda3\envs\cuda_pytorch\lib\site-packages\keras\layers\core.py", line 483, in init
super(Flatten, self).init(**kwargs)
File "C:\Users\MY DELL\anaconda3\envs\cuda_pytorch\lib\site-packages\keras\engine\topology.py", line 293, in init
raise TypeError('Keyword argument not understood:', kwarg)
TypeError: ('Keyword argument not understood:', 'data_format')

from dehazing-pmhld-patch-map-based-hybrid-learning-dehazenet-for-single-image-haze-removal-tip-2020.

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