Example of semantic segmentation in Keras

Last update: Mar 23, 2022

Related tags

Deep Learning deep-learning proof-of-concept keras segmentation convolutional-neural-networks toy-project

Overview

keras-semantic-segmentation-example

Example of semantic segmentation in Keras

Single class example:

Generated data: random ellipse with random color on random color background and with random noise added.

Result: 1st images is input image, 2nd image is ground truth mask, 3rd image is probability, 4th image is probability thresholded at 0.5.

Multi-class example:

Generated data: first class is random ellipse with random color and second class is random rectangle with random color on random color background and with random noise added.

Result: 1st images is input image, 2nd image is ground truth mask, 3rd image is probability, 4th image is probability thresholded at 0.5.

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Comments

Failures if image width != height

In binary_crossentropy_example.py if I change the dimensions of the image so that the width and height are not the same, as in:

IMAGE_W = 126
IMAGE_H = 124

then I get the error:

Epoch 1/100000
Traceback (most recent call last):
File "binary_crossentropy_example.py", line 187, in <module>  train()
File "binary_crossentropy_example.py", line 182, in train callbacks=callbacks)
File "C:\Python3.6\lib\site-packages\keras\legacy\interfaces.py", line 91, in wrapper
return func(*args, **kwargs)
File "C:\Python3.6\lib\site-packages\keras\engine\training.py", line 2230, in fit_generator
class_weight=class_weight)
File "C:\Python3.6\lib\site-packages\keras\engine\training.py", line 1877, in train_on_batch
class_weight=class_weight)
File "C:\Python3.6\lib\site-packages\keras\engine\training.py", line 1480, in _standardize_user_data
exception_prefix='target')
File "C:\Python3.6\lib\site-packages\keras\engine\training.py", line 123, in _standardize_input_data
str(data_shape))
ValueError: Error when checking target: expected activation_1 to have shape (9216, 1) but got array 
with shape (15624, 1)

On Windows 10 Keras 2.1.6 tensorflow 1.8.0

opened by jaybo 3

Reshaping the mask

Sorry for the interruption, but I don't understand why the mask is reshaped in binary_crossentropy_example.py, line 106:

mask_list= mask_list.reshape(batch_size,IMAGE_H*IMAGE_W,NUMBER_OF_CLASSES)

but the image_list is not similarly reshaped. The code works perfectly as is, but I'm just trying to understand why the above line isn't:

mask_list= mask_list.reshape(batch_size,IMAGE_H,IMAGE_W,NUMBER_OF_CLASSES)

opened by jaybo 1

Example of semantic segmentation in Keras

Related tags

Overview

keras-semantic-segmentation-example

Single class example:

Multi-class example:

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Comments

Failures if image width != height

Reshaping the mask

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