b66acd1fc82ce746b837879efcf02a5f59f64eb0,helper/utilty.py,,compute_mse,#Any#Any#Any#,483

Before Change

	image1 = trim_image_as_file(image1)
	image2 = trim_image_as_file(image2)

	mse = 0.0
	for i in range(border_size, image1.shape[0] - border_size):
		for j in range(border_size, image1.shape[1] - border_size):
			for k in range(image1.shape[2]):
				error = image1[i, j, k] - image2[i, j, k]
				mse += error * error

	return mse / ((image1.shape[0] - 2 * border_size) * (image1.shape[1] - 2 * border_size) * image1.shape[2])


def print_filter_weights(tensor):
	print("Tensor[%s] shape=%s" % (tensor.name, str(tensor.get_shape())))

After Change

	image2 = trim_image_as_file(image2)

	shave = 6 + border_size
	diff = np.subtract(image1, image2)
	diff = diff[border_size:-border_size, border_size:-border_size, :]
	mse = np.mean(np.square(diff))

	return mse

def print_filter_weights(tensor):
	print("Tensor[%s] shape=%s" % (tensor.name, str(tensor.get_shape())))
	weight_value = tensor.eval()

Instances