f45a368fe41452cf8b4f43f3cebffa4f1eb3c65f,keras_segmentation/data_utils/data_loader.py,,get_image_array,#,118

Before Change

    elif imgNorm == "sub_mean":
        img = cv2.resize(img, (width, height))
        img = img.astype(np.float32)
        img[:, :, 0] -= 103.939
        img[:, :, 1] -= 116.779
        img[:, :, 2] -= 123.68
        img = img[:, :, ::-1]
    elif imgNorm == "divide":
        img = cv2.resize(img, (width, height))

After Change

        means = [103.939, 116.779, 123.68]

        for i in range(min(img.shape[2], len(means))):
            img[:, :, i] -= means[i]

        img = img[:, :, ::-1]
    elif imgNorm == "divide":
        img = cv2.resize(img, (width, height))
        img = img.astype(np.float32)

Instances