Error in the code leading to bad performances

[MathiasGilson]

Hi,
I found that you resize images with opencv for the validation (see val_generator arguments)

Keras-ICNet/utils.py

Lines 61 to 63 in 987a6aa

	if self.resize_shape:
	image = cv2.resize(image, self.resize_shape)
	label = cv2.resize(label, self.resize_shape)

cv2.resize deforms the images and thus leads to bad learning

Instead I used the random crop function to always crop the image instead of deforming it
it's not and ideal fix but it leads to way better performances

change this line

Keras-ICNet/train

Line 48 in 987a6aa

val_generator = MapillaryGenerator(mode='validation', batch_size=opt.batch_size, crop_shape=None, resize_shape=(opt.image_width, opt.image_height))

to

val_generator = MapillaryGenerator(mode='validation', batch_size=opt.batch_size, crop_shape=(opt.image_width, opt.image_height))

and put this lines

Keras-ICNet/utils.py

Lines 91 to 92 in 987a6aa

	if self.crop_shape:
	image, label = _random_crop(image, label, self.crop_shape)

out of the if self.mode == 'training': condition
Now in each validation iteration the image will not be resized but randomly cropped