Filter

fiter.py

def filter_single_image(img_path, filter_cutoff, resize_to_shape=None):
    try:
        image = imagereader.image_read(img_path)

    except Exception:
        print(img_path + " is corrupted. Ignore it.")
        return None
    return filter_single_image_np(image,filter_cutoff,resize_to_shape)

def filter_single_image_np(image, filter_cutoff, resize_to_shape=None):
    cutoff_factor = 1.0
    if resize_to_shape is not None:
        if not isinstance(resize_to_shape, (list, tuple)):
            'Scale the short side to 1024'
            #         h              w
            ar = image.shape[0] / image.shape[1]
            if ar < 1:
                height = resize_to_shape
                width = int(resize_to_shape / ar)
            else:
                height = int(resize_to_shape * ar)
                width = resize_to_shape
            resize_to_shape = [height, width]

        cutoff_factor = image.shape[0] / resize_to_shape[0]
        from PIL import Image
        convert_to_array = Image.fromarray(image)
        resized = convert_to_array.resize((resize_to_shape[1], resize_to_shape[0]),
                                          resample=Image.BILINEAR)
        image = np.asarray(resized)

    mask_size_0 = next_power_of2(image.shape[0])
    mask_size_1 = next_power_of2(image.shape[1])
    filter_width = 2 * image.shape[1] * filter_cutoff * cutoff_factor
    mask = window(filter_width, (mask_size_0, mask_size_1))
    image_filtered = apply_fft_mask(image, mask)
    del image
    return image_filtered

def filter_single_image(img_path, filter_cutoff, resize_to_shape=None):
if isinstance(a, np.ndarray):
return filter_single_image_np(image,filter_cutoff,resize_to_shape)
try:
image = imagereader.image_read(img_path)

except Exception:
    print(img_path + " is corrupted. Ignore it.")
    return None
return filter_single_image_np(image,filter_cutoff,resize_to_shape)