| import copy |
| import json |
| import os |
|
|
| import numpy as np |
| import cv2 |
| import pycocotools.mask as maskUtils |
| import random |
|
|
|
|
| def get_video_frames(video_path): |
| cap = cv2.VideoCapture(video_path) |
|
|
| if not cap.isOpened(): |
| print("Error: Cannot open video file.") |
| return |
|
|
| frames = [] |
|
|
| frame_id = 0 |
| while True: |
| ret, frame = cap.read() |
|
|
| if not ret: |
| break |
|
|
| frames.append(frame) |
|
|
| frame_id += 1 |
|
|
| cap.release() |
| return frames |
|
|
|
|
| def images_to_video(frames, video_name, fps=6): |
| height, width, layers = frames[0].shape |
|
|
| fourcc = cv2.VideoWriter_fourcc(*'mp4v') |
| video = cv2.VideoWriter(video_name, fourcc, fps, (width, height)) |
|
|
| for frame in frames: |
| video.write(frame) |
|
|
| |
| video.release() |
| return |
|
|
| def decode_masklet(masklet): |
| masks = [] |
| for _rle in masklet: |
| mask = maskUtils.decode(_rle) |
| |
| masks.append(mask) |
| |
| return masks |
|
|
| def draw_mask(image, mask): |
| obj_mask = mask * 255 |
| obj_mask = np.stack([obj_mask * 1, obj_mask * 0, obj_mask * 0], axis=2) |
| obj_mask = obj_mask * 0.5 + copy.deepcopy(image) * 0.5 |
| obj_mask = obj_mask.astype(np.uint8) |
| return obj_mask |
|
|
| def add_mask2images(frames, masklets): |
| show_videos = [] |
| for i_frames, (frame, masks) in enumerate(zip(frames, masklets)): |
| if i_frames == 0: |
| n_obj = masks.shape[-1] |
| for i_obj in range(n_obj): |
| show_videos.append([]) |
|
|
| n_obj = masks.shape[-1] |
| for i_obj in range(n_obj): |
| show_videos[i_obj].append(draw_mask(copy.deepcopy(frame), masks[:, :, i_obj])) |
| return show_videos |
|
|
|
|
| video_folder = '/mnt/bn/xiangtai-training-data-video/dataset/segmentation_datasets/sam_v_full' |
| video_save_path = './whole_pesudo_cap_visualization/demo.mp4' |
|
|
| caption_json_path = './whole_pesudo_cap/short_cap/' |
| cap_json_files = os.listdir(caption_json_path) |
| cap_json_paths = [os.path.join(caption_json_path, item) for item in cap_json_files] |
| caption_jsons = [] |
| for cap_json_path in cap_json_paths: |
| with open(cap_json_path, 'r') as f: |
| caption_jsons.extend(json.load(f)) |
|
|
|
|
| video_obj_cap_dict = {} |
| for cap_item in caption_jsons: |
| video_id = cap_item['video_id'] |
| obj_id = cap_item['obj_id'] |
| if video_id not in video_obj_cap_dict.keys(): |
| video_obj_cap_dict[video_id] = {} |
| video_obj_cap_dict[video_id].update({obj_id: cap_item}) |
|
|
| video_ids = list(video_obj_cap_dict.keys()) |
| random.shuffle(video_ids) |
| |
| for video_id in video_ids: |
| sub_folder = video_id[:7] |
| video_anno_file = f'{video_folder}/{sub_folder}/sav_train/{sub_folder}/{video_id}_manual.json' |
| video_path = f'{video_folder}/{sub_folder}/sav_train/{sub_folder}/{video_id}.mp4' |
| with open(video_anno_file, 'r') as f: |
| data = json.load(f) |
| frames = get_video_frames(video_path) |
| masklents = decode_masklet(data['masklet']) |
| frames = frames[::4] |
| assert len(frames) == len(masklents) |
| show_videos = add_mask2images(frames, masklents) |
|
|
| for i, show_video in enumerate(show_videos): |
| print(i, '---', video_obj_cap_dict[video_id].keys()) |
|
|
| i = f"{i}" |
| if i not in video_obj_cap_dict[video_id].keys(): |
| continue |
| |
| final_caption = video_obj_cap_dict[video_id][i]['formated'] |
| short_cap = video_obj_cap_dict[video_id][i]['short_cap'] |
| print('\n\n', final_caption, '\n\n') |
| with open(video_save_path.replace('demo.mp4', f'{video_id}_obj{i}.txt'), 'w', encoding='utf-8') as file: |
| file.write(final_caption + '\n\n' + short_cap) |
| video_save_path_ = video_save_path.replace('demo.mp4', f'{video_id}_obj{i}.mp4') |
| images_to_video(show_video, video_save_path_) |
|
|
|
|
