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"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Video Subtitle Remover - Google Colab\n",
"\n",
"This notebook allows you to run Video Subtitle Remover in Google Colab with free GPU access.\n",
"\n",
"**New in this version:**\n",
"- \ud83d\udcdd Subtitle extraction to SRT files with OCR\n",
"- \ud83e\udd16 Automatic model downloading from Hugging Face\n",
"- \u26a1 Improved performance\n",
"\n",
"**Requirements:**\n",
"- Google account\n",
"- Video file (upload to Google Drive or use sample)\n",
"\n",
"**Colab Environment:**\n",
"- Python: 3.10\n",
"- CUDA: 12.2 (Tesla T4 GPU)\n",
"- GPU Memory: 15GB\n",
"\n",
"**Recommended Algorithm:** STTN (fastest for Colab's limited runtime)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Step 1: Check GPU and Environment"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"# Check GPU availability\n",
"!nvidia-smi\n",
"\n",
"import torch\n",
"print(f\"Python version: 3.10\")\n",
"print(f\"PyTorch version: {torch.__version__}\")\n",
"print(f\"CUDA available: {torch.cuda.is_available()}\")\n",
"if torch.cuda.is_available():\n",
" print(f\"CUDA version: {torch.version.cuda}\")\n",
" print(f\"GPU: {torch.cuda.get_device_name(0)}\")\n",
" print(f\"GPU Memory: {torch.cuda.get_device_properties(0).total_memory / 1024**3:.1f} GB\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Step 2: Clone Repository"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": []
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"# Clone the repository\n",
"!git clone https://huggingface.co/Rasta02/dataku\n",
"%cd dataku"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Step 2.5: Verify Installation\n",
"\n",
"Quick check that the repository was cloned successfully."
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"# Verify the repository structure\n",
"import os\n",
"\n",
"repo_path = '/content/dataku'\n",
"if os.path.exists(repo_path):\n",
" print('\u2713 Repository cloned successfully')\n",
" print(f' Path: {repo_path}')\n",
"else:\n",
" print('\u274c Repository not found')\n",
" print(' Please run Step 2 first')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Step 3: Install Dependencies\n",
"\n",
"Colab already has many packages. We'll install missing ones."
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"# Install dependencies\n",
"# Note: Colab already has torch, torchvision, opencv-python, numpy, etc.\n",
"!pip install -q filesplit==3.0.2 albumentations scikit-image imgaug pyclipper lmdb\n",
"!pip install -q PyYAML omegaconf tqdm easydict scikit-learn pandas webdataset\n",
"!pip install -q protobuf av einops paddleocr paddle2onnx onnxruntime-gpu\n",
"\n",
"# Install PaddlePaddle GPU version (compatible with Colab)\n",
"!pip install -q paddlepaddle-gpu==2.6.2\n",
"\n",
"# Advanced Inpainting Models (Optional - only install if using these modes)\n",
"# Uncomment the line below to enable Stable Diffusion, DiffuEraser, E2FGVI\n",
"# !pip install -q diffusers transformers accelerate\n",
"\n",
"print(\"\u2713 Dependencies installed!\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Step 4: Mount Google Drive (Optional)\n",
"\n",
"Mount your Google Drive to access videos stored there."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"from google.colab import drive\n",
"drive.mount('/content/drive')\n",
"\n",
"# Your videos will be accessible at:\n",
"# /content/drive/MyDrive/your_video.mp4"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Step 5: Configure Settings\n",
"\n",
"Adjust these settings based on your needs:"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# === CONFIGURATION ===\n",
"\n",
"# Algorithm selection\n",
"# Options:\n",
"# 'STTN' - Fast, real-time video (recommended for Colab)\n",
"# 'LAMA' - High quality for images/animation\n",
"# 'PROPAINTER' - Best quality, very slow, high VRAM\n",
"# 'SD' - Stable Diffusion (NEW - requires extra install above)\n",
"# 'DIFFUERASER' - Specialized subtitle removal (Coming soon)\n",
"# 'E2FGVI' - Fast flow-guided (Coming soon)\n",
"ALGORITHM = 'STTN'\n",
"\n",
"# STTN Settings (recommended for Colab)\n",
"STTN_SKIP_DETECTION = True # Much faster, processes entire subtitle area\n",
"STTN_MAX_LOAD_NUM = 40 # Reduce if OOM (30-50 for T4 GPU)\n",
"STTN_NEIGHBOR_STRIDE = 5\n",
"STTN_REFERENCE_LENGTH = 10\n",
"\n",
"# LAMA Settings\n",
"LAMA_SUPER_FAST = False # Set True for faster but lower quality\n",
"\n",
"# ProPainter Settings (requires 16GB+ GPU, not recommended for Colab)\n",
"PROPAINTER_MAX_LOAD_NUM = 40 # Very low for T4 GPU\n",
"\n",
"# Stable Diffusion Settings (NEW)\n",
"SD_STEPS = 50 # More steps = better quality but slower\n",
"SD_GUIDANCE_SCALE = 7.5 # How much to follow the prompt\n",
"SD_PROMPT = \"natural scene, high quality\" # Text guidance\n",
"\n",
"# Video path (change this)\n",
"# Option 1: Use sample video\n",
"VIDEO_PATH = '/content/dataku/test/test.mp4'\n",
"\n",
"# Option 2: Use video from Google Drive (uncomment)\n",
"# VIDEO_PATH = '/content/drive/MyDrive/my_video.mp4'\n",
"\n",
"# Subtitle area (optional, in pixels: ymin, ymax, xmin, xmax)\n",
"# None = auto-detect subtitle area\n",
"SUBTITLE_AREA = None\n",
"\n",
"# Example: Bottom 20% of 1080p video\n",
"# SUBTITLE_AREA = (864, 1080, 0, 1920)\n",
"\n",
"print(f\"Configuration:\")\n",
"print(f\" Algorithm: {ALGORITHM}\")\n",
"print(f\" Video: {VIDEO_PATH}\")\n",
"print(f\" Subtitle area: {SUBTITLE_AREA or 'Auto-detect'}\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Step 6: Apply Configuration"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [],
"source": [
"# Modify config.py with our settings\n",
"import sys\n",
"sys.path.insert(0, '/content/dataku')\n",
"sys.path.insert(0, '/content/dataku/backend')\n",
"\n",
"from backend import config\n",
"from backend.config import InpaintMode\n",
"\n",
"# Apply algorithm selection\n",
"if ALGORITHM == 'STTN':\n",
" config.MODE = InpaintMode.STTN\n",
" config.STTN_SKIP_DETECTION = STTN_SKIP_DETECTION\n",
" config.STTN_MAX_LOAD_NUM = STTN_MAX_LOAD_NUM\n",
" config.STTN_NEIGHBOR_STRIDE = STTN_NEIGHBOR_STRIDE\n",
" config.STTN_REFERENCE_LENGTH = STTN_REFERENCE_LENGTH\n",
"elif ALGORITHM == 'LAMA':\n",
" config.MODE = InpaintMode.LAMA\n",
" config.LAMA_SUPER_FAST = LAMA_SUPER_FAST\n",
"elif ALGORITHM == 'PROPAINTER':\n",
" config.MODE = InpaintMode.PROPAINTER\n",
" config.PROPAINTER_MAX_LOAD_NUM = PROPAINTER_MAX_LOAD_NUM\n",
"elif ALGORITHM == 'SD':\n",
" config.MODE = InpaintMode.STABLE_DIFFUSION\n",
" config.SD_STEPS = SD_STEPS\n",
" config.SD_GUIDANCE_SCALE = SD_GUIDANCE_SCALE\n",
" config.SD_PROMPT = SD_PROMPT\n",
"elif ALGORITHM == 'DIFFUERASER':\n",
" config.MODE = InpaintMode.DIFFUERASER\n",
" print('\u26a0\ufe0f DiffuEraser not yet implemented, will fall back to LAMA')\n",
"elif ALGORITHM == 'E2FGVI':\n",
" config.MODE = InpaintMode.E2FGVI\n",
" print('\u26a0\ufe0f E2FGVI not yet implemented, will fall back to STTN')\n",
"\n",
"print(f\"\u2713 Configuration applied!\")\n",
"print(f\" Using device: {config.device}\")\n",
"print(f\" Mode: {config.MODE.value}\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Step 7: Process Video"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [],
"source": [
"import multiprocessing\n",
"from backend.main import SubtitleRemover\n",
"import os\n",
"\n",
"# Check if video exists\n",
"if not os.path.exists(VIDEO_PATH):\n",
" print(f\"\u274c Error: Video not found at {VIDEO_PATH}\")\n",
" print(\"Please upload your video or update VIDEO_PATH\")\n",
"else:\n",
" print(f\"Processing video: {VIDEO_PATH}\")\n",
" print(f\"This may take several minutes...\")\n",
" print(f\"\")\n",
" \n",
" # Set multiprocessing start method\n",
" try:\n",
" multiprocessing.set_start_method(\"spawn\")\n",
" except:\n",
" pass\n",
" \n",
" # Create SubtitleRemover instance\n",
" sr = SubtitleRemover(VIDEO_PATH, sub_area=SUBTITLE_AREA, gui_mode=False)\n",
" \n",
" # Run processing\n",
" sr.run()\n",
" \n",
" # Output location\n",
" output_path = sr.video_out_name\n",
" print(f\"\\n\u2713 Processing complete!\")\n",
" print(f\"Output saved to: {output_path}\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Step 8: Download Result\n",
"\n",
"Download the processed video to your computer."
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [],
"source": [
"from google.colab import files\n",
"import os\n",
"\n",
"# Get output filename\n",
"video_name = os.path.basename(VIDEO_PATH)\n",
"video_name_no_ext = os.path.splitext(video_name)[0]\n",
"output_file = f\"{video_name_no_ext}_no_sub.mp4\"\n",
"output_path = os.path.join(os.path.dirname(VIDEO_PATH), output_file)\n",
"\n",
"if os.path.exists(output_path):\n",
" print(f\"Downloading: {output_file}\")\n",
" files.download(output_path)\n",
"else:\n",
" print(f\"\u274c Output file not found: {output_path}\")\n",
" print(\"Check if processing completed successfully.\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Step 9: Save to Google Drive (Optional)\n",
"\n",
"Save the output video to Google Drive instead of downloading."
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [],
"source": [
"import shutil\n",
"import os\n",
"\n",
"# Destination in Google Drive\n",
"drive_output_path = '/content/drive/MyDrive/video_subtitle_remover_output/'\n",
"\n",
"# Create directory if it doesn't exist\n",
"os.makedirs(drive_output_path, exist_ok=True)\n",
"\n",
"# Copy output file\n",
"if os.path.exists(output_path):\n",
" dest_file = os.path.join(drive_output_path, output_file)\n",
" shutil.copy(output_path, dest_file)\n",
" print(f\"\u2713 Saved to Google Drive: {dest_file}\")\n",
"else:\n",
" print(f\"\u274c Output file not found\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Troubleshooting\n",
"\n",
"### Out of Memory (OOM)\n",
"```python\n",
"# Reduce batch size\n",
"STTN_MAX_LOAD_NUM = 30\n",
"# Or use LAMA\n",
"ALGORITHM = 'LAMA'\n",
"```\n",
"\n",
"### Processing too slow\n",
"```python\n",
"# Enable skip detection\n",
"STTN_SKIP_DETECTION = True\n",
"# Or use super fast mode\n",
"ALGORITHM = 'LAMA'\n",
"LAMA_SUPER_FAST = True\n",
"```\n",
"\n",
"### Subtitles not removed\n",
"```python\n",
"# Set manual subtitle area (bottom 20% of 1080p)\n",
"SUBTITLE_AREA = (864, 1080, 0, 1920)\n",
"```\n",
"\n",
"### GPU not detected\n",
"1. Runtime \u2192 Change runtime type \u2192 Hardware accelerator \u2192 GPU\n",
"2. Restart runtime\n",
"\n",
"### Session timeout\n",
"- Colab free tier has time limits\n",
"- Process smaller videos (<10 min)\n",
"- Or use Colab Pro for longer sessions"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Advanced: Batch Processing\n",
"\n",
"Process multiple videos from Google Drive:"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [],
"source": [
"import glob\n",
"import os\n",
"from backend.main import SubtitleRemover\n",
"\n",
"# Folder containing videos\n",
"video_folder = '/content/dataku/test/'\n",
"\n",
"# Find all MP4 files\n",
"video_files = glob.glob(os.path.join(video_folder, '*.mp4'))\n",
"\n",
"print(f\"Found {len(video_files)} videos to process\")\n",
"\n",
"for i, video_path in enumerate(video_files, 1):\n",
" print(f\"\\n[{i}/{len(video_files)}] Processing: {os.path.basename(video_path)}\")\n",
" \n",
" try:\n",
" sr = SubtitleRemover(video_path, sub_area=SUBTITLE_AREA, gui_mode=False)\n",
" sr.run()\n",
" print(f\"\u2713 Complete: {sr.video_out_name}\")\n",
" except Exception as e:\n",
" print(f\"\u274c Error: {e}\")\n",
" continue\n",
"\n",
"print(f\"\\n\u2713 Batch processing complete!\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Tips for Best Results\n",
"\n",
"1. **Use STTN with skip detection** - Fastest for Colab\n",
"2. **Keep videos under 10 minutes** - Avoid session timeout\n",
"3. **Set manual subtitle area** - For better accuracy\n",
"4. **Monitor GPU memory** - Use `!nvidia-smi` in separate cell\n",
"5. **Save to Drive frequently** - Avoid data loss on timeout\n",
"\n",
"## Performance Expectations (Colab T4 GPU)\n",
"\n",
"| Video Length | Algorithm | Time |\n",
"|--------------|-----------|------|\n",
"| 1 min 720p | STTN (skip) | ~30s |\n",
"| 5 min 720p | STTN (skip) | ~2min |\n",
"| 1 min 720p | LAMA | ~3min |\n",
"| 5 min 720p | LAMA | ~15min |\n",
"\n",
"ProPainter is not recommended for Colab due to memory limitations."
]
}
],
"metadata": {
"accelerator": "GPU",
"colab": {
"gpuType": "T4",
"provenance": []
},
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
}
},
"nbformat": 4,
"nbformat_minor": 0
} |