VTimeLLM/data/activitynet/videos/read.py

import json
import os
import shutil
import random
from pathlib import Path

# Load the datasets
train = json.load(open('/home/jisoo/demo/VidChain/VTimeLLM/data/activitynet/mdpo-train.json'))
val = json.load(open('/home/jisoo/demo/VidChain/VTimeLLM/data/activitynet/val_2.json'))

# Source directory where videos are already stored
source_dir = Path('/hub_data2/jisoo/data/ActivityNet/videos')

# Create directories if they don't exist
train_dir = Path('/home/jisoo/demo/VidChain/VTimeLLM/data/activitynet/videos/train')
val_dir = Path('/home/jisoo/demo/VidChain/VTimeLLM/data/activitynet/videos/val')
train_dir.mkdir(exist_ok=True)
val_dir.mkdir(exist_ok=True)

def copy_video(video_id, output_dir):
    """Copy a video from the source directory to the target directory"""
    # Look for mp4 files first, then other extensions
    possible_extensions = ['.mp4', '.mkv', '.avi', '.mov']
    
    for ext in possible_extensions:
        source_path = source_dir / f"{video_id}{ext}"
        if source_path.exists():
            output_path = output_dir / f"{video_id}.mp4"
            
            # Skip if file already exists
            if output_path.exists():
                print(f"Video {video_id} already exists in {output_dir}, skipping...")
                return True
            
            try:
                print(f"Copying {video_id} to {output_dir}...")
                shutil.copy2(source_path, output_path)
                print(f"Successfully copied {video_id}")
                return True
            except Exception as e:
                print(f"Error copying {video_id}: {e}")
                return False
    
    print(f"Video {video_id} not found in source directory")
    return False

def copy_sample_videos_from_list(video_ids, output_dir, num_samples=25):
    """Copy a sample of videos from a list of video IDs"""
    # Randomly sample videos
    if len(video_ids) > num_samples:
        sampled_ids = random.sample(video_ids, num_samples)
    else:
        sampled_ids = video_ids
    
    print(f"Copying {len(sampled_ids)} videos to {output_dir}...")
    
    successful_copies = 0
    for video_id in sampled_ids:
        if copy_video(video_id, output_dir):
            successful_copies += 1
    
    print(f"Successfully copied {successful_copies}/{len(sampled_ids)} videos")
    return successful_copies

# Set random seed for reproducibility
random.seed(42)

# Check if source directory exists
if not source_dir.exists():
    print(f"Error: Source directory {source_dir} does not exist!")
    exit(1)

print(f"Source directory: {source_dir}")
print(f"Train directory: {train_dir}")
print(f"Validation directory: {val_dir}")

# Get video IDs from train dataset (it has a 'vid' field with a list of video IDs)
train_video_ids = train['vid'] if 'vid' in train else []
print(f"Found {len(train_video_ids)} video IDs in train dataset")

# Get video IDs from validation dataset (it has video IDs as keys)
val_video_ids = list(val.keys())
print(f"Found {len(val_video_ids)} video IDs in validation dataset")

# Copy sample videos
# print("\n=== Copying Train Videos ===")
# train_success = copy_sample_videos_from_list(train_video_ids, train_dir, num_samples=100)

print("\n=== Copying Validation Videos ===")
val_success = copy_sample_videos_from_list(val_video_ids, val_dir, num_samples=50)

print(f"\n=== Summary ===")
# print(f"Train videos copied: {train_success}/100")
print(f"Validation videos copied: {val_success}/25")
# print(f"Total videos copied: {train_success + val_success}/125")

# List the copied files
# print(f"\n=== Copied Train Videos ===")
# train_files = list(train_dir.glob("*.mp4"))
# for file in train_files:
#     print(f"  {file.name}")

print(f"\n=== Copied Validation Videos ===")
val_files = list(val_dir.glob("*.mp4"))
for file in val_files:
    print(f"  {file.name}")

# Show some statistics
print(f"\n=== Statistics ===")
# print(f"Total train files: {len(train_files)}")
print(f"Total validation files: {len(val_files)}")

# # Check file sizes
# if train_files:
#     total_train_size = sum(f.stat().st_size for f in train_files)
#     print(f"Total train directory size: {total_train_size / (1024*1024):.2f} MB")

if val_files:
    total_val_size = sum(f.stat().st_size for f in val_files)
    print(f"Total validation directory size: {total_val_size / (1024*1024):.2f} MB")