https://github.com/kavishannip/blurblend
Identify people in the image and blur the background with the given intensity while keeping the foreground sharp.
https://github.com/kavishannip/blurblend
image-processing python streamlit
Last synced: about 1 month ago
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Identify people in the image and blur the background with the given intensity while keeping the foreground sharp.
- Host: GitHub
- URL: https://github.com/kavishannip/blurblend
- Owner: kavishannip
- Created: 2025-04-28T18:55:13.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2025-04-29T09:34:11.000Z (about 1 year ago)
- Last Synced: 2025-04-30T03:53:29.919Z (about 1 year ago)
- Topics: image-processing, python, streamlit
- Language: Python
- Homepage: https://blurblend.streamlit.app/
- Size: 1.93 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# BlurBlend 🖼️
BlurBlend is an AI-powered tool that automatically detects and separates foreground subjects from backgrounds in images and applies a professional-looking blur effect to the background while keeping the subject sharp and in focus.
Live Demo: [https://blurblend.streamlit.app/](https://blurblend.streamlit.app/)
GitHub Repository: [https://github.com/kavishannip/BlurBlend](https://github.com/kavishannip/BlurBlend)
---
## Features
- 🤖 **AI-Powered Segmentation**: Uses state-of-the-art image segmentation models to automatically detect people and other foreground objects.
- 🎚️ **Adjustable Blur**: Control the blur intensity with an easy-to-use slider.
- 🧠 **Multiple Models**: Choose from different AI models optimized for various use cases.
- ⚡ **GPU Acceleration**: Leverages CUDA when available for faster processing.
- 💾 **One-Click Download**: Easily download the processed images.
---
## Live Demo
Try out BlurBlend at [https://blurblend.streamlit.app/](https://blurblend.streamlit.app/).
---
## How It Works
1. **Upload**: Select an image containing people or objects.
2. **Segment**: The AI model identifies foreground objects.
3. **Blur**: BlurBlend applies a blur effect to the background while keeping the foreground sharp.
---
## Available Models
- **Segmentation Model (Default)**: `facebook/mask2former-swin-base-coco-panoptic` - Best all-around segmentation.
- **Smaller Model**: `nvidia/segformer-b0-finetuned-ade-512-512` - Faster but less accurate.
- **Person Detection**: `facebook/detr-resnet-50-panoptic` - Specialized for people detection.
- **Person Detection+**: `mattmdjaga/segformer_b2_clothes` - Enhanced model that detects clothing items.
---
## Technical Implementation
The project consists of two main components:
### 1. BlurBlend Class
Handles the AI segmentation and blur application logic:
- Loads and manages AI segmentation models.
- Processes images to separate foreground from background.
- Applies configurable blur effects to the background.
### 2. Streamlit Web Interface
Provides a user-friendly interface:
- Upload and preview images.
- Configure segmentation model and blur settings.
- Process and download results.
---
## Installation
To run BlurBlend locally, follow these steps:
1. Clone the repository:
```bash
git clone https://github.com/kavishannip/BlurBlend.git
cd BlurBlend
```
2. Install the required dependencies:
```bash
pip install -r requirements.txt
```
3. Run the Streamlit app:
```bash
streamlit run app.py
```
---
## Usage
### Basic Usage of `BlurBlend` Class
```python
from blurblend import BlurBlend
# Initialize with chosen model
blur_tool = BlurBlend(model_path="facebook/mask2former-swin-base-coco-panoptic")
# Process an image
result_image = blur_tool.process_image(
image_path="path/to/image.jpg",
blur_radius=15
)
# Save the result
result_image.save("blurred_background.png")
```
### Running the Web App
1. Open the app in your browser after running `streamlit run app.py`.
2. Upload an image, configure the blur intensity, and select the segmentation model.
3. Click "Apply Background Blur" to process the image.
4. Download the result using the provided button.
---
## Requirements
The following dependencies are required to run BlurBlend:
- `streamlit>=1.22.0`
- `transformers>=4.30.0`
- `torch>=2.0.0`
- `Pillow>=9.0.0`
- `numpy>=1.24.0`
- `scipy>=1.10.0`
- `timm>=0.9.0`
Install them using:
```bash
pip install -r requirements.txt
```
---
## Author
Developed by [Kavishan Nipun](https://www.linkedin.com/in/kavishan-nipun-876930222/).
GitHub: [https://github.com/kavishannip](https://github.com/kavishannip)
LinkedIn: [https://www.linkedin.com/in/kavishan-nipun-876930222/](https://www.linkedin.com/in/kavishan-nipun-876930222/)