| import os | |
| import numpy as np | |
| import pandas as pd | |
| from pandarallel import pandarallel | |
| import tarfile | |
| from PIL import Image | |
| def is_video_file(path): | |
| video_extensions = ['.mp4', '.avi', '.mkv', '.mov', '.wmv', '.flv', '.mpeg', '.mpg'] | |
| ext = os.path.splitext(path)[1] | |
| return ext.lower() in video_extensions | |
| def is_path_valid(path): | |
| if os.path.isfile(path): | |
| if is_video_file(path): | |
| pass | |
| else: | |
| try: | |
| image = Image.open(path).convert('RGB') | |
| except Exception as e: | |
| print(e, path) | |
| return False | |
| else: | |
| dirname = os.path.dirname(path) | |
| basename = os.path.basename(path) | |
| if not dirname.endswith('.tar'): | |
| return False | |
| else: | |
| with tarfile.open(dirname) as tar: | |
| names = tar.getnames() | |
| if not basename in names: | |
| return False | |
| return True | |
| pandarallel.initialize(nb_workers=50, progress_bar=True) | |
| df = pd.read_csv("train_config_video_0912/part_1.csv") | |
| ret = df['path'].parallel_apply( | |
| is_path_valid | |
| ) | |
| df_ = df[ret] | |
| print('total:', len(df)) | |
| print('valid:', len(df_)) | |
| import ipdb | |
| ipdb.set_trace() | |