Update README.md

README.md

@@ -5,6 +5,7 @@ colorFrom: indigo
 colorTo: purple
 sdk: docker
 app_port: 7860
+sdk_version: 1.49.1
 license: mit
 tags:
   - video
@@ -21,14 +22,15 @@ BackgroundFX Pro is a GPU-accelerated app for Hugging Face Spaces (Docker) that
 - **SAM2** — high-quality object segmentation  
 - **MatAnyone** — temporal video matting for stable alpha over time
 
-Built on: **CUDA 12.1.1**, **PyTorch 2.5.1 (cu121)**, **torchvision 0.20.1**, **Gradio 4.41.0**.
+Built on: **CUDA 12.1.1**, **PyTorch 2.5.1 (cu121)**, **torchvision 0.20.1**, **Streamlit 1.49.1**.
 
 ---
 
 ## ✨ Features
 
-- Replace backgrounds with: **solid color**, **AI-generated** image (procedural), **custom uploaded image**, or **Unsplash** search  
+- Replace backgrounds with: **solid color**, **AI-generated** image (procedural), **custom uploaded image**, or **professional backgrounds**  
 - Optimized for **T4 GPUs** on Hugging Face  
+- Two-stage pipeline: SAM2 segmentation → MatAnyone refinement → compositing
 - Caching & logs stored in the repo volume:
   - HF cache → `./.hf`  
   - Torch cache → `./.torch`  
@@ -45,37 +47,37 @@ https://huggingface.co/spaces/MogensR/VideoBackgroundReplacer2
 
 ## 🖱️ How to Use
 
-1. **Upload a video** (`.mp4`, `.avi`, `.mov`, `.mkv`).  
-2. Choose a **Background Type**: Upload Image, AI Generate, Gradient, Solid, or Unsplash.  
-3. If not uploading, enter a prompt and click **Generate Background**.  
-4. Click **Process Video**.  
-5. Preview and **Download Result**.
+1. **Upload a video** (`.mp4`, `.mov`, `.avi`, `.mkv`).  
+2. Choose a **Background Type**: Image, Color, Blur, Professional Backgrounds, or AI Generated.  
+3. If using custom background, upload your image or select from professional options.  
+4. Click **🚀 Process Video**.  
+5. Preview and **💾 Download Result**.
 
-> Tip: Start with 720p/1080p on T4; 4K can exceed memory.
+> Tip: Start with 720p/1080p on T4; 4K can exceed memory limits.
 
 ---
 
 ## 🗂️ Project Structure (key files)
 
-- `Dockerfile`  
-- `requirements.txt`  
-- `ui.py`  
-- `ui_core_interface.py`  
-- `ui_core_functionality.py`  
-- `two_stage_pipeline.py`  
-- `models/sam2_loader.py`  
-- `models/matanyone_loader.py`  
-- `utils/__init__.py`  
-- `data/`  (created at runtime for logs/outputs)  
-- `tmp/`   (created at runtime for jobs/temp files)
+- `Dockerfile` — CUDA 12.1.1 + PyTorch 2.5.1 container
+- `requirements.txt` — Python dependencies
+- `app.py` — Main Streamlit application
+- `integrated_pipeline.py` — Two-stage processing pipeline
+- `models/sam2_loader.py` — SAM2 model loader with HF Hub integration
+- `models/matanyone_loader.py` — MatAnyone model loader
+- `utils/` — Utility functions
+- `data/` — Created at runtime for logs/outputs  
+- `tmp/` — Created at runtime for processing jobs
 
 ---
 
 ## ⚙️ Runtime Notes
 
-- Binds to `PORT` / `GRADIO_SERVER_PORT` (defaults to **7860**).  
-- Heartbeat logs every ~2s with memory & disk stats.  
-- If there’s no final “PROCESS EXITING” line, it was likely an **OOM** or hard kill.
+- Binds to `PORT` / `STREAMLIT_SERVER_PORT` (defaults to **7860**)
+- File upload limit: 200MB via `--server.maxUploadSize=200`
+- CORS disabled for Docker compatibility: `--server.enableCORS=false`
+- Memory management with automatic cleanup between stages
+- If processing fails, check Space logs for detailed error information
 
 ---
 
@@ -92,3 +94,31 @@ docker build -t backgroundfx-pro .
 
 # Run
 docker run --gpus all -p 7860:7860 backgroundfx-pro
+```
+
+Access at: http://localhost:7860
+
+---
+
+## 🔧 Technical Details
+
+### Pipeline Architecture
+1. **Stage 1**: SAM2 generates object masks using click points
+2. **Stage 2**: MatAnyone refines masks for temporal consistency  
+3. **Stage 3**: Composite foreground with new background
+
+### Model Loading
+- SAM2 models downloaded from Hugging Face Hub automatically
+- Supports small/base/large variants (small recommended for T4)
+- MatAnyone loaded from official repository
+
+### Performance Optimizations
+- T4-specific optimizations (fp16, channels_last)
+- Memory pruning during long video processing
+- Automatic model unloading between stages
+
+---
+
+## 📝 License
+
+MIT License - See LICENSE file for details.