def create_mean_image_file(file_paths, save_path):
frames, _ = load_state_files(file_paths)
mean_image = preprocess.compute_mean_image(frames) / 255.0
viewer.show_image(mean_image, title='mean_image')
mean_image = converter.hwc2chw(mean_image)
save_mean_image(save_path, mean_image)
return mean_image
def load_image(image_file):
print('loading images from: ', image_file)
image = cv2.imread(image_file)
image = cv2.resize(image, dsize=(64, 64))
image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
image = converter.hwc2chw(image) / 255.0
image = image.astype(np.float32)
assert np.all(0.0 <= image) and np.all(image <= 1.0)
return image
def preprocess_frames(frames):
preprocessed_frames = [converter.hwc2chw(frame) for frame in frames]
# for i in range(3):
# viewer.show_image(preprocessed_frames[0][i] + mean_image[0, :, :],
# 'preprocessed image. color channel -> {} (0: R, 1: G, 2: B) '.format(i))
assert preprocessed_frames[0].shape == (3, 210, 160)
return preprocessed_frames
def convert_to_grayscale(subtractor, filename):
image = cv2.imread(filename)
image = cv2.resize(image, dsize=(64, 64))
image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
image = converter.hwc2chw(image) / 255.0
image = image.astype(np.float32)
image = np.reshape(image, newshape=((1, ) + image.shape))
print('image shape: ', image.shape)
grayscale = subtractor(image)
return grayscale
def show_sample_subtraction(model, args):
image = cv2.imread(args.test_subtraction_image)
image = cv2.resize(image, dsize=(64, 64))
image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
image = converter.hwc2chw(image) / 255.0
image = image.astype(np.float32)
image = np.reshape(image, newshape=((1, ) + image.shape))
print('image shape: ', image.shape)
grayscale = model(image)
grayscale = np.reshape(grayscale.data, newshape=(64, 64))
print('grayscale shape: ', grayscale.shape)
viewer.show_image(grayscale, is_gray=True)
def load_images(images_dir):
print('loading images from: ', images_dir)
images = []
files = os.listdir(images_dir)
files.sort()
for file_name in files:
path = os.path.join(images_dir, file_name)
if os.path.isfile(path) and '.jpg' in path:
image = cv2.imread(path)
image = cv2.resize(image, dsize=(64, 64))
image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
image = converter.hwc2chw(image) / 255.0
image = image.astype(np.float32)
assert np.all(0.0 <= image) and np.all(image <= 1.0)
images.append(image)
return images
def test_hwc2chw(self):
image = np.ndarray(shape=(28, 28, 3), dtype=np.float32)
converted = converter.hwc2chw(image)
assert converted.shape == (3, 28, 28)