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"""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))) |