bulk-bg-remover

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bulk-bg-remover

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Remove bulk image background for free using python in Google Colabs

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bulk_bg_remover.py
README.md

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# Bulk Background Remover for Google Drive

A simple Python script that removes backgrounds from all images in your Google Drive folder using AI. Perfect for batch processing product photos, portraits, or any images where you need transparent backgrounds.

## Features

- **Bulk Processing**: Process all images in a Google Drive folder at once
- **AI-Powered**: Uses advanced AI models (rembg) for accurate background removal
- **Transparent PNGs**: Outputs high-quality PNG files with transparent backgrounds
- **Smart Resume**: Skips already-processed images if you run it multiple times
- **Google Colab Ready**: Runs entirely in Google Colab - no local setup required
- **Progress Tracking**: Shows real-time progress with a progress bar

## Supported Image Formats

- JPEG/JPG
- PNG
- BMP
- WebP
- TIFF

## How to Use

### Step 1: Prepare Your Images

1. Upload all your images to a Google Drive folder
2. Get the folder link by right-clicking the folder → "Share" → "Copy link"
   - Example: `https://drive.google.com/drive/folders/1NnSIpOyJzZtM6e2iVqArwwWj3QPBOj3Z`

### Step 2: Open Google Colab

1. Go to [Google Colab](https://colab.research.google.com/)
2. Create a new notebook: **File → New notebook**

### Step 3: Copy the Script

1. Download the `bulk_bg_remover.py` file from this repository
2. Open it and copy all the code
3. Paste it into a new cell in your Google Colab notebook

### Step 4: Configure the Script

Find the **CONFIGURATION** section at the top of the script and edit these values:

```python
# 📁 STEP 1: Replace with YOUR Google Drive folder link
FOLDER_LINK_OR_ID = "PASTE_YOUR_GOOGLE_DRIVE_FOLDER_LINK_HERE"

# 📂 STEP 2: Choose output folder name suffix (optional)
OUTPUT_SUFFIX = "_no_bg"

# 🤖 STEP 3: Choose AI model (optional)
MODEL_NAME = "u2net"
```

**Required:**
- Replace `"PASTE_YOUR_GOOGLE_DRIVE_FOLDER_LINK_HERE"` with your actual Google Drive folder link

**Optional:**
- `OUTPUT_SUFFIX`: The suffix added to your output folder name (default: `_no_bg`)
- `MODEL_NAME`: Choose between:
  - `"u2net"` - Best quality (recommended)
  - `"u2netp"` - Faster but slightly lower quality
  - `"isnet-general-use"` - Alternative model

### Step 5: Run the Script

1. Click the **Play button** (▶️) next to the cell
2. **Grant permissions** when prompted:
   - Allow Google Colab to access your Google Drive
   - Allow Google Colab to access Google Drive API
3. Wait for the script to complete

### Step 6: Get Your Results

- The script creates a new folder with the suffix `_no_bg` (or your custom suffix)
- This folder will be in the **same location** as your original folder
- All processed images will be saved as transparent PNGs
- A link to the output folder will be displayed when processing completes

## Example Configuration

If your folder link is:
```
https://drive.google.com/drive/folders/1NnSIpOyJzZtM6e2iVqArwwWj3QPBOj3Z
```

Your configuration should look like:
```python
FOLDER_LINK_OR_ID = "https://drive.google.com/drive/folders/1NnSIpOyJzZtM6e2iVqArwwWj3QPBOj3Z"
OUTPUT_SUFFIX = "_no_bg"
MODEL_NAME = "u2net"
```

If your original folder is named "ProductPhotos", the output folder will be named "ProductPhotos_no_bg".

## What the Script Does

1. **Installs Dependencies**: Automatically installs all required Python packages
2. **Mounts Google Drive**: Connects to your Google Drive (requires permission)
3. **Locates Images**: Finds all image files in your specified folder
4. **Removes Backgrounds**: Uses AI to remove backgrounds from each image
5. **Saves Results**: Saves processed images as transparent PNGs in the output folder
6. **Shows Summary**: Displays statistics about processed, skipped, and failed images

## Output

After processing, you'll see a summary like this:

```
----- Summary -----
Processed : 45
Skipped   : 0 (already exists)
Errors    : 0

✅ Finished. Output folder:
https://drive.google.com/drive/folders/[YOUR_OUTPUT_FOLDER_ID]
```

## Troubleshooting

### "Could not extract a folder ID"
- Make sure you replaced the placeholder text with your actual folder link
- Ensure the link is a Google Drive **folder** link, not a file link

### "No images found"
- Check that your folder contains supported image formats
- Make sure the folder link is correct and accessible

### Permission Errors
- Make sure you click "Allow" when Google Colab requests permissions
- Try running the cell again after granting permissions

### Out of Memory
- If processing very large images, try using the `"u2netp"` model (faster, less memory)
- Process images in smaller batches

## Technical Details

- **AI Model**: Uses [rembg](https://github.com/danielgatis/rembg) library
- **Runtime**: Google Colab (free tier works fine)
- **Processing Time**: Depends on number and size of images (~2-5 seconds per image)
- **Output Format**: PNG with alpha channel (transparency)

## License

This script is provided as-is for personal and commercial use. The rembg library is licensed under MIT.

## Credits

- Built with [rembg](https://github.com/danielgatis/rembg) for background removal
- Designed for easy use with Google Colab

## Contributing

Found a bug or have a feature request? Feel free to open an issue or submit a pull request!

---

**Made with ❤️ for easy bulk background removal**

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