def copy_keyframes(project, _shots):
key_frames_file_names = [
image_filename(shot.keyframe.index) for shot in _shots
]
copy_keyframe = lambda file_name: copy2(
join(project.folder_path(Project.Folder.frames), file_name),
join(project.folder_path(Project.Folder.keyframes), file_name))
[copy_keyframe(file_name) for file_name in key_frames_file_names]
def run(project, shots, cluster_count): progress_bar = tqdm(total=len(shots), desc="colors") for shot in shots: filename = image_filename(shot.keyframe.index) image_path = path.join(project.folder_path(Project.Folder.keyframes), filename) shot.keyframe.colors = colors_from_image(image_path, cluster_count) progress_bar.update() progress_bar.close() return shots
def write_spatio_temporal_slices(project, shots):
progress_bar = tqdm(total=len(shots), desc="spatio temporal slices")
for shot in shots:
slices = calculate_patio_temporal_slice(
project.folder_path(Project.Folder.frames), shot)
vis = np.concatenate(slices, axis=1)
filename = image_filename(shot.id)
path = os.path.join(project.folder_path(Project.Folder.spatio),
filename)
cv2.imwrite(path, vis)
progress_bar.update()
progress_bar.close()
def calculate_patio_temporal_slice(base_path, shot):
cropped_images = []
for index in range(shot.start_index, shot.end_index):
filename = image_filename(index)
path = join(base_path, filename)
image = cv2.imread(path)
shape = image.shape
y = 0
x = shape[1] // 2
width = 1
height = shape[0]
cropped_image = image[y:y + height, x:x + width]
resize_image = cv2.resize(cropped_image, (cropped_image.shape[1], 50))
cropped_images.append(resize_image)
return cropped_images
def shot_to_keyframe_path(shot):
index = shot.keyframe.index
filename = utils.image_filename(index)
return path.join(project.folder_path(Project.Folder.keyframes),
filename)