"""Cut video clips from downloaded videos.""" import os from os.path import join, exists from subprocess import call import time import numpy as np import pandas as pd from tqdm import tqdm # import shared.utils.io as io # import shared.utils.log as log def time_float_to_str(time_in_seconds): import datetime # Calculate hours, minutes, seconds, and milliseconds hours, remainder = divmod(time_in_seconds, 3600) minutes, seconds_with_ms = divmod(remainder, 60) seconds, milliseconds = divmod(int(seconds_with_ms * 1000), 1000) # Create a timedelta object time_delta = datetime.timedelta(hours=hours, minutes=minutes, seconds=seconds, milliseconds=milliseconds) # Format the time as HH:MM:SS.mmm formatted_time = str(time_delta) return formatted_time if __name__ == "__main__": import argparse parser = argparse.ArgumentParser() parser.add_argument( "--csv", type=str, required=True, help="Path to CSV file containing video IDs and timestamps", ) parser.add_argument( "--video_id_key", type=str, default="video_id", ) parser.add_argument( "--start_time_key", type=str, default="start_time", ) parser.add_argument( "--end_time_key", type=str, default="end_time", ) parser.add_argument( "--video_dir", type=str, required=True, help="Path to directory containing downloaded videos", ) parser.add_argument( "--cut_dir", type=str, required=True, help="Path to directory where cut videos will be saved", ) parser.add_argument( "--overwrite", action="store_true", help="Whether to overwrite existing cut videos", ) parser.add_argument( "--verbose", action="store_true", ) parser.add_argument( "--no_round_times", action="store_true", help="Whether to round start and end times to nearest second in filenames", ) args = parser.parse_args() # Make cut_dir os.makedirs(args.cut_dir, exist_ok=True) # Load csv assert os.path.exists(args.csv), f"CSV file {args.csv} does not exist." df = pd.read_csv(args.csv) print(">>> Loaded CSV file with shape", df.shape) assert {args.video_id_key, args.start_time_key, args.end_time_key}.issubset(df.columns), \ f"CSV file must contain columns {args.video_id_key}, {args.start_time_key}, and {args.end_time_key}." # Filter out videos that don't exist df["video_path"] = df[args.video_id_key].apply( lambda video_id: join(args.video_dir, f"{video_id}.mp4"), ) df["check_video"] = df["video_path"].apply(exists) df = df[df["check_video"]] del df["check_video"] print(">>> Found videos for", df.shape[0], "rows.") # Cut videos ext = "mp4" iterator = tqdm(range(len(df)), desc="Cutting clips") for i in iterator: row = df.iloc[i].to_dict() f = row["video_path"] v, s, e = row[args.video_id_key], row[args.start_time_key], row[args.end_time_key] s = float(s) e = float(e) if args.no_round_times: clip_filename = f"{v}_{s}_{e}.{ext}" else: clip_filename = f"{v}_{np.round(s, 1)}_{np.round(e, 1)}.{ext}" clip_filepath = join(args.cut_dir, clip_filename) os.makedirs(os.path.dirname(clip_filepath), exist_ok=True) if os.path.exists(clip_filepath) and not args.overwrite: continue # bring s in HH:MM:SS.mmm format with milliseconds s = time_float_to_str(s) e = time_float_to_str(e) # # bring s in HH:MM:SS. format # s = time.strftime("%H:%M:%S", time.gmtime(s)) # e = time.strftime("%H:%M:%S", time.gmtime(e)) # ffmpeg code # use ffmpeg to cut the clip + change spatial resolution to have max height command = f"ffmpeg -i {f} -ss {s} -to {e} -strict -2 -c:v libx264 "\ f"-pix_fmt yuv420p -c:a copy {clip_filepath} "\ f"-y -format {ext}" if not args.verbose: command += " -loglevel quiet" else: print(">>> Cutting clip", clip_filepath) call(command, shell=True) print(">>> Number of cut files:", len(os.listdir(args.cut_dir)))