DeepLab v3 - how to process images with any size ratio. (h * w)
Deeplab v3 predicts only with default ratio 512 * 512. how to process images with different size ratio.
please look over the error:-
Traceback (most recent call last):
File "", line 35, in
predicted = model_dlv3.predict(img[np.newaxis, ...])
File
"/home/developer/anaconda2/envs/py36/lib/python3.6/site-packages/keras/engine/training.py",
line 1149, in predict
x, _, _ = self._standardize_user_data(x)
File
"/home/developer/anaconda2/envs/py36/lib/python3.6/site-packages/keras/engine/training.py",
line 751, in _standardize_user_data
exception_prefix='input')
File
"/home/developer/anaconda2/envs/py36/lib/python3.6/site-packages/keras/engine/training_utils.py",
line 138, in standardize_input_data
str(data_shape))
ValueError: Error when checking input: expected input_3 to have shape (512, 512, 3) but got array with shape (2448, 3264, 3)
python opencv keras deep-learning deeplab
edited Nov 23 '18 at 12:39
Mike Scotty
5,82552033
asked Nov 23 '18 at 12:38
Shyam KumarShyam Kumar
1
add a comment |
Deeplab v3 predicts only with default ratio 512 * 512. how to process images with different size ratio.
please look over the error:-
Traceback (most recent call last):
File "", line 35, in
predicted = model_dlv3.predict(img[np.newaxis, ...])
File
"/home/developer/anaconda2/envs/py36/lib/python3.6/site-packages/keras/engine/training.py",
line 1149, in predict
x, _, _ = self._standardize_user_data(x)
File
"/home/developer/anaconda2/envs/py36/lib/python3.6/site-packages/keras/engine/training.py",
line 751, in _standardize_user_data
exception_prefix='input')
File
"/home/developer/anaconda2/envs/py36/lib/python3.6/site-packages/keras/engine/training_utils.py",
line 138, in standardize_input_data
str(data_shape))
ValueError: Error when checking input: expected input_3 to have shape (512, 512, 3) but got array with shape (2448, 3264, 3)
python opencv keras deep-learning deeplab
edited Nov 23 '18 at 12:39
Mike Scotty
5,82552033
asked Nov 23 '18 at 12:38
Shyam KumarShyam Kumar
1
add a comment |
Deeplab v3 predicts only with default ratio 512 * 512. how to process images with different size ratio.
please look over the error:-
Traceback (most recent call last):
File "", line 35, in
predicted = model_dlv3.predict(img[np.newaxis, ...])
File
"/home/developer/anaconda2/envs/py36/lib/python3.6/site-packages/keras/engine/training.py",
line 1149, in predict
x, _, _ = self._standardize_user_data(x)
File
"/home/developer/anaconda2/envs/py36/lib/python3.6/site-packages/keras/engine/training.py",
line 751, in _standardize_user_data
exception_prefix='input')
File
"/home/developer/anaconda2/envs/py36/lib/python3.6/site-packages/keras/engine/training_utils.py",
line 138, in standardize_input_data
str(data_shape))
ValueError: Error when checking input: expected input_3 to have shape (512, 512, 3) but got array with shape (2448, 3264, 3)
python opencv keras deep-learning deeplab
edited Nov 23 '18 at 12:39
Mike Scotty
5,82552033
asked Nov 23 '18 at 12:38
Shyam KumarShyam Kumar
1
Deeplab v3 predicts only with default ratio 512 * 512. how to process images with different size ratio.
please look over the error:-
Traceback (most recent call last):
File "", line 35, in
predicted = model_dlv3.predict(img[np.newaxis, ...])
File
"/home/developer/anaconda2/envs/py36/lib/python3.6/site-packages/keras/engine/training.py",
line 1149, in predict
x, _, _ = self._standardize_user_data(x)
File
"/home/developer/anaconda2/envs/py36/lib/python3.6/site-packages/keras/engine/training.py",
line 751, in _standardize_user_data
exception_prefix='input')
File
"/home/developer/anaconda2/envs/py36/lib/python3.6/site-packages/keras/engine/training_utils.py",
line 138, in standardize_input_data
str(data_shape))
ValueError: Error when checking input: expected input_3 to have shape (512, 512, 3) but got array with shape (2448, 3264, 3)
python opencv keras deep-learning deeplab
python opencv keras deep-learning deeplab
edited Nov 23 '18 at 12:39
Mike Scotty
5,82552033
asked Nov 23 '18 at 12:38
Shyam KumarShyam Kumar
1
edited Nov 23 '18 at 12:39
Mike Scotty
5,82552033
asked Nov 23 '18 at 12:38
Shyam KumarShyam Kumar
1
edited Nov 23 '18 at 12:39
Mike Scotty
5,82552033
edited Nov 23 '18 at 12:39
Mike Scotty
5,82552033
edited Nov 23 '18 at 12:39
Mike Scotty
5,82552033
5,82552033
asked Nov 23 '18 at 12:38
Shyam KumarShyam Kumar
1
asked Nov 23 '18 at 12:38
Shyam KumarShyam Kumar
1
asked Nov 23 '18 at 12:38
Shyam KumarShyam Kumar
1
1
add a comment |
add a comment |
1 Answer
1
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oldest
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You can resize the images to 512*512 or turn images into a square using padding and then resize them into 512*512. Latter option is better since it won't change the shape of the objects inside the image. You can use different padding modes and see what gives the best result.
You can use opencv or scikit-image for resizing and padding
opencv documentation for padding: https://docs.opencv.org/2.4/modules/imgproc/doc/filtering.html?highlight=copymakeborder#copymakeborder
scikit-image documentation for padding : http://scikit-image.org/docs/dev/api/skimage.util.html#skimage.util.pad
answered Nov 23 '18 at 13:10
Mete Han KahramanMete Han Kahraman
41017
add a comment |
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1 Answer
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1 Answer
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active
oldest
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oldest
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oldest
votes
You can resize the images to 512*512 or turn images into a square using padding and then resize them into 512*512. Latter option is better since it won't change the shape of the objects inside the image. You can use different padding modes and see what gives the best result.
You can use opencv or scikit-image for resizing and padding
opencv documentation for padding: https://docs.opencv.org/2.4/modules/imgproc/doc/filtering.html?highlight=copymakeborder#copymakeborder
scikit-image documentation for padding : http://scikit-image.org/docs/dev/api/skimage.util.html#skimage.util.pad
answered Nov 23 '18 at 13:10
Mete Han KahramanMete Han Kahraman
41017
add a comment |
You can resize the images to 512*512 or turn images into a square using padding and then resize them into 512*512. Latter option is better since it won't change the shape of the objects inside the image. You can use different padding modes and see what gives the best result.
You can use opencv or scikit-image for resizing and padding
opencv documentation for padding: https://docs.opencv.org/2.4/modules/imgproc/doc/filtering.html?highlight=copymakeborder#copymakeborder
scikit-image documentation for padding : http://scikit-image.org/docs/dev/api/skimage.util.html#skimage.util.pad
answered Nov 23 '18 at 13:10
Mete Han KahramanMete Han Kahraman
41017
add a comment |
You can resize the images to 512*512 or turn images into a square using padding and then resize them into 512*512. Latter option is better since it won't change the shape of the objects inside the image. You can use different padding modes and see what gives the best result.
You can use opencv or scikit-image for resizing and padding
opencv documentation for padding: https://docs.opencv.org/2.4/modules/imgproc/doc/filtering.html?highlight=copymakeborder#copymakeborder
scikit-image documentation for padding : http://scikit-image.org/docs/dev/api/skimage.util.html#skimage.util.pad
answered Nov 23 '18 at 13:10
Mete Han KahramanMete Han Kahraman
41017
You can resize the images to 512*512 or turn images into a square using padding and then resize them into 512*512. Latter option is better since it won't change the shape of the objects inside the image. You can use different padding modes and see what gives the best result.
You can use opencv or scikit-image for resizing and padding
opencv documentation for padding: https://docs.opencv.org/2.4/modules/imgproc/doc/filtering.html?highlight=copymakeborder#copymakeborder
scikit-image documentation for padding : http://scikit-image.org/docs/dev/api/skimage.util.html#skimage.util.pad
answered Nov 23 '18 at 13:10
Mete Han KahramanMete Han Kahraman
41017
answered Nov 23 '18 at 13:10
Mete Han KahramanMete Han Kahraman
41017
answered Nov 23 '18 at 13:10
Mete Han KahramanMete Han Kahraman
41017
answered Nov 23 '18 at 13:10
Mete Han KahramanMete Han Kahraman
41017
41017
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