# -----------------------------------------------------------------------------
# Copyright (c) 2025, NVIDIA CORPORATION. All rights reserved.
#
# NVIDIA CORPORATION and its licensors retain all intellectual property
# and proprietary rights in and to this software, related documentation
# and any modifications thereto. Any use, reproduction, disclosure or
# distribution of this software and related documentation without an express
# license agreement from NVIDIA CORPORATION is strictly prohibited.
# -----------------------------------------------------------------------------

import argparse
import ast
import csv
import json
import os
import shutil
import subprocess
from tqdm import tqdm


def get_vid_mapping(input_video_dir):
    """
    Create mapping from video ID to local file path.

    Args:
        input_video_dir: Directory containing downloaded videos organized in folders

    Returns:
        vid_mapping: Dictionary mapping video IDs to local file paths
    """
    print("mapping video id to local path")
    vid_mapping = {}
    folders = [x for x in os.listdir(input_video_dir) if os.path.isdir(f"{input_video_dir}/{x}")]
    for folder in sorted(folders):
        vids = [x for x in os.listdir(f"{input_video_dir}/{folder}") if x[-4:] == ".mp4"]
        for vid in tqdm(sorted(vids)):
            vid_path = f"{input_video_dir}/{folder}/{vid}"
            vid_json = f"{input_video_dir}/{folder}/{vid[:-4]}.json"
            # Extract video ID from URL in JSON metadata
            vid_name = json.load(open(vid_json))["url"].split("?v=")[-1]
            vid_mapping[vid_name] = vid_path
    return vid_mapping


def extract(url_list, input_video_dir, output_frame_parent, uid_mapping):
    """
    Extract frames from videos at 12 fps.

    Args:
        url_list: CSV file containing video URLs and timestamps
        input_video_dir: Directory containing downloaded videos
        output_frame_parent: Output directory for extracted frames
        uid_mapping: CSV file mapping timestamps to unique IDs
    """
    vid_mapping = get_vid_mapping(input_video_dir)

    with open(uid_mapping, "r") as file2:
        with open(url_list, "r") as file:
            csv_reader = csv.reader(file)
            csv_reader2 = csv.reader(file2)
            for i, (row, row2) in enumerate(tqdm(zip(csv_reader, csv_reader2))):
                # Skip header row and empty rows
                if i == 0 or len(row) == 0:
                    continue

                try:
                    full_vid_path = vid_mapping[row[0]]
                except KeyError:
                    if i % 10 == 0:
                        print("video not found, skipping", row[0])
                    continue

                print("extracting", row[0])
                for j, timestamps in enumerate(ast.literal_eval(row[2])):
                    uid = row2[j]
                    # Copy video with unique ID name
                    vid_parent = os.path.dirname(os.path.dirname(full_vid_path))
                    vid_uid_path = shutil.copyfile(full_vid_path, f"{vid_parent}/{uid}.mp4")
                    os.makedirs(f"{output_frame_parent}/{uid}", exist_ok=True)
                    # Extract frames using ffmpeg
                    cmd = f"nice -n 19 ffmpeg -i {vid_uid_path} -q:v 2 -vf fps=12 {output_frame_parent}/{uid}/%05d.jpg"

                    subprocess.run(cmd, shell=True, capture_output=True)


if __name__ == "__main__":
    parser = argparse.ArgumentParser()
    parser.add_argument("--url_list", type=str, help="path for url list")
    parser.add_argument("--input_video_dir", type=str, help="video directory")
    parser.add_argument("--output_frame_parent", type=str, help="parent for output frames")
    parser.add_argument("--uid_mapping", type=str, help="path for uid mapping")
    args = parser.parse_args()
    print("args", args)
    extract(args.url_list, args.input_video_dir, args.output_frame_parent, args.uid_mapping)