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| import sys | |
| if sys.version_info[0] < 3 and sys.version_info[1] < 2: | |
| raise Exception("Must be using >= Python 3.2") | |
| from os import listdir, path | |
| if not path.isfile('data/face_detection/s3fd-619a316812.pth'): | |
| raise FileNotFoundError('Save the s3fd model to face_detection/detection/sfd/s3fd.pth before running this script!') | |
| import multiprocessing as mp | |
| from concurrent.futures import ThreadPoolExecutor, as_completed | |
| import numpy as np | |
| import argparse, os, traceback, subprocess | |
| import cv2 | |
| from tqdm import tqdm | |
| from glob import glob | |
| import audio | |
| from hparams import hparams as hp | |
| import face_detection | |
| def _progress(generated, to_generate): | |
| progress((generated, to_generate)) | |
| def preprocess_video_files(args): | |
| fa = [face_detection.FaceAlignment(face_detection.LandmarksType._2D, flip_input=False, device='cpu') for _ in range(args.ngpu)] | |
| template = 'ffmpeg -loglevel panic -y -i {} -strict -2 {}' | |
| def process_video_file(vfile, args, gpu_id): | |
| video_stream = cv2.VideoCapture(vfile) | |
| frames = [] | |
| while 1: | |
| still_reading, frame = video_stream.read() | |
| if not still_reading: | |
| video_stream.release() | |
| break | |
| frames.append(frame) | |
| vidname = os.path.basename(vfile).split('.')[0] | |
| dirname = vfile.split('/')[-2] | |
| fulldir = path.join(args.preprocessed_root, dirname, vidname) | |
| os.makedirs(fulldir, exist_ok=True) | |
| batches = [frames[i:i + args.batch_size] for i in range(0, len(frames), args.batch_size)] | |
| i = -1 | |
| for fb in tqdm(batches, desc='Processing Video Frames'): | |
| preds = fa[gpu_id].get_detections_for_batch(np.asarray(fb)) | |
| for j, f in enumerate(preds): | |
| i += 1 | |
| if f is None: | |
| continue | |
| x1, y1, x2, y2 = f | |
| cv2.imwrite(path.join(fulldir, '{}.jpg'.format(i)), fb[j][y1:y2, x1:x2]) | |
| _progress(i + 1, len(batches) * args.batch_size) | |
| def process_audio_file(vfile, args): | |
| vidname = os.path.basename(vfile).split('.')[0] | |
| dirname = vfile.split('/')[-2] | |
| fulldir = path.join(args.preprocessed_root, dirname, vidname) | |
| os.makedirs(fulldir, exist_ok=True) | |
| wavpath = path.join(fulldir, 'audio.wav') | |
| command = template.format(vfile, wavpath) | |
| subprocess.call(command, shell=True) | |
| _progress(1, 1) | |
| def mp_handler(job): | |
| vfile, args, gpu_id = job | |
| try: | |
| process_video_file(vfile, args, gpu_id) | |
| except KeyboardInterrupt: | |
| exit(0) | |
| except: | |
| traceback.print_exc() | |
| print('Started processing for {} with {} GPUs'.format(args.data_root, args.ngpu)) | |
| filelist = glob(path.join(args.data_root, '*.mp4')) | |
| jobs = [(vfile, args, i % args.ngpu) for i, vfile in enumerate(filelist)] | |
| p = ThreadPoolExecutor(args.ngpu) | |
| futures = [p.submit(mp_handler, j) for j in jobs] | |
| _ = [r.result() for r in tqdm(as_completed(futures), total=len(futures))] | |
| print('Dumping audios...') | |
| for vfile in tqdm(filelist): | |
| try: | |
| process_audio_file(vfile, args) | |
| _progress(1, 1) | |
| except KeyboardInterrupt: | |
| exit(0) | |
| except: | |
| traceback.print_exc() | |
| continue | |
| def main(args): | |
| print('Started processing for {} with {} GPUs'.format(args.data_root, args.ngpu)) | |
| filelist = glob(path.join(args.data_root, '*.mp4')) | |
| jobs = [(vfile, args, i % args.ngpu) for i, vfile in enumerate(filelist)] | |
| p = ThreadPoolExecutor(args.ngpu) | |
| futures = [p.submit(mp_handler, j) for j in jobs] | |
| _ = [r.result() for r in tqdm(as_completed(futures), total=len(futures))] | |
| _progress(1, 1) | |
| print('Dumping audios...') | |
| for vfile in tqdm(filelist, desc='Processing Audio Files'): | |
| try: | |
| process_audio_file(vfile, args) | |
| except KeyboardInterrupt: | |
| exit(0) | |
| except: | |
| traceback.print_exc() | |
| continue | |
| _progress(1, len(filelist)) | |
| if __name__ == '__main__': | |
| main(args) |