Updated readme with proper configs

README.md

@@ -1,226 +1,39 @@
-# DeepDefend
+# In your local folder, update README.md
+@"
+---
+title: DeepDefend API
+emoji: 🛡️
+colorFrom: red
+colorTo: blue
+sdk: docker
+app_port: 7860
+pinned: false
+---
 
-> **Multi-Modal Deepfake Detection System**  
-> Detect AI-generated deepfakes in videos using computer vision and audio analysis
+# 🛡️ DeepDefend API
 
-[![Python 3.10+](https://img.shields.io/badge/python-3.10+-blue.svg)](https://www.python.org/downloads/)
-[![FastAPI](https://img.shields.io/badge/FastAPI-0.109.0-009688.svg)](https://fastapi.tiangolo.com)
+Advanced Multi-Modal Deepfake Detection System
 
-## Overview
+## API Endpoints
 
-DeepDefend is a comprehensive deepfake detection system that combines **video frame analysis** and **audio analysis** to identify AI-generated synthetic media. Using machine learning models and AI-powered evidence fusion, it provides detailed, interval-by-interval analysis with explainable results.
+- POST /api/analyze - Analyze video for deepfakes
+- GET /api/health - Health check
+- GET /api/stats - Statistics
+- GET /docs - Interactive API documentation
 
-### Why DeepDefend?
+## Usage
 
-- **Multi-Modal Analysis**: Combines video and audio detection for higher accuracy
-- **AI-Powered Fusion**: Uses LLM to generate human-readable reports
-- **Interval Breakdown**: Shows exactly which parts of the video are suspicious
-- **REST API**: Easy integration with any frontend or application
+Upload a video file to analyze:
 
-## Features
+\`\`\`bash
+curl -X POST "https://nishchandel-deepdefend-api.hf.space/api/analyze" \\
+  -F "file=@video.mp4"
+\`\`\`
 
-### Core Detection Capabilities
+Visit /docs for interactive documentation.
+"@ | Out-File -FilePath README.md -Encoding utf8
 
-- **Video Analysis**
-  - Frame-by-frame deepfake detection using pre-trained models
-  - Face detection and region-specific analysis
-  - Suspicious region identification (eyes, mouth, face boundaries)
-  - Confidence scoring per frame
-
-- **Audio Analysis**
-  - Voice synthesis detection
-  - Spectrogram analysis for audio artifacts
-  - Frequency pattern recognition
-  - Audio splicing detection
-
-- **AI-Powered Reporting**
-  - LLM-based evidence fusion (Google Gemini)
-  - Natural language explanation of findings
-  - Verdict with confidence percentage
-  - Timestamped suspicious intervals
-
-### Processing Pipeline
-
-```
-Video Input
-    ↓
-┌───────────────────┐
-│ Media Extraction  │ → Extract frames (5 per interval)
-│                   │ → Extract audio chunks
-└────────┬──────────┘
-         │
-         ├──────────────────────┬──────────────────────┐
-         ▼                      ▼                      ▼
-┌─────────────────┐   ┌─────────────────┐   ┌────────────────┐
-│ Video Analysis  │   │ Audio Analysis  │   │ Timeline Gen   │
-│ • Face detect   │   │ • Spectrogram   │   │ • 2s intervals │
-│ • Region scan   │   │ • Voice synth   │   │ • Metadata     │
-│ • Fake score    │   │ • Artifacts     │   │                │
-└────────┬────────┘   └────────┬────────┘   └────────┬───────┘
-         │                     │                      │
-         └──────────────┬──────────────┬─────────────┘
-                        ▼              ▼
-                ┌──────────────────────────┐
-                │   LLM Fusion Engine      │
-                │ • Combine evidence       │
-                │ • Generate verdict       │
-                │ • Natural language report│
-                └────────────┬─────────────┘
-                             ▼
-                      Final Report
-                    (JSON Response)
-```
-
-## Demo
-
-### Live Demo
-**API**: [https://deepdefend-api.hf.space](https://deepdefend-api.hf.space)  
-**Docs**: [https://deepdefend-api.hf.space/docs](https://deepdefend-api.hf.space/docs)
-
-### Example Analysis
-
-<details>
-<summary>Click to see sample output</summary>
-
-```json
-{
-  "verdict": "DEEPFAKE",
-  "confidence": 87.5,
-  "overall_scores": {
-    "overall_video_score": 0.823,
-    "overall_audio_score": 0.756,
-    "overall_combined_score": 0.789
-  },
-  "detailed_analysis": "This video shows strong indicators of deepfake manipulation...",
-  "suspicious_intervals": [
-    {
-      "interval": "4.0-6.0",
-      "video_score": 0.891,
-      "audio_score": 0.834,
-      "video_regions": ["eyes", "mouth"],
-      "audio_regions": ["voice_synthesis_artifacts"]
-    }
-  ],
-  "total_intervals_analyzed": 15,
-  "video_info": {
-    "duration": 12.498711111111112,
-    "fps": 29.923085402583734,
-    "total_frames": 374,
-    "file_size_mb": 31.36
-  },
-  "analysis_id": "4cd98ea5-8c14-4cae-8da4-689345b0aabc",
-  "timestamp": "2025-10-10T23:34:35.724916"
-}
-```
-</details>
-
-## Installation
-
-### Prerequisites
-
-- Python 3.10 or higher
-- FFmpeg installed on your system
-- Google Gemini API key 
-
-### Local Setup
-
-1. **Clone the repository**
-```bash
-git clone https://github.com/yourusername/deepdefend.git
-```
-
-2. **Create virtual environment**
-```bash
-python -m venv venv
-
-# On Linux/Mac
-source venv/bin/activate
-
-# On Windows
-venv\Scripts\activate
-```
-
-3. **Install dependencies**
-```bash
-pip install -r requirements.txt
-```
-
-4. **Download ML models**
-```bash
-python models/download_model.py
-```
-*This will download ~2GB of models from Hugging Face*
-
-5. **Configure environment**
-```bash
-cp .env.example .env
-# Edit .env and add your GOOGLE_API_KEY
-```
-
-6. **Run the server**
-```bash
-uvicorn main:app --reload
-```
-
-The API will be available at `http://127.0.0.1:8000`
-
-### Docker Setup
-
-```bash
-# Build image
-docker build -t deepdefend .
-
-# Run container
-docker run -p 8000:8000 -e GOOGLE_API_KEY=your_key deepdefend
-```
-
-## Tech Stack
-
-### Backend
-- **Framework**: FastAPI 0.109.0
-- **Server**: Uvicorn
-- **ML Framework**: PyTorch 2.3.1
-- **Transformers**: Hugging Face Transformers 4.36.2
-
-### ML Models
-- **Video Detection**: [dima806/deepfake_vs_real_image_detection](https://huggingface.co/dima806/deepfake_vs_real_image_detection)
-- **Audio Detection**: [mo-thecreator/Deepfake-audio-detection](https://huggingface.co/mo-thecreator/Deepfake-audio-detection)
-- **LLM Fusion**: Google Gemini 2.5 Flash
-
-### Processing
-- **Computer Vision**: OpenCV, Pillow
-- **Audio Processing**: Librosa, SoundFile
-- **Video Processing**: FFmpeg
-
-### Deployment
-- **Container**: Docker
-- **Platforms**: Hugging Face Spaces
-
-## Project Structure
-
-```
-deepdefend/
-│   
-│── extraction/
-│   ├── media_extractor.py     # Frame & audio extraction
-│   └── timeline_generator.py  # Timeline creation
-│
-│── analysis/
-│   ├── video_analyser.py      # Video deepfake detection
-│   ├── audio_analyser.py      # Audio deepfake detection
-│   ├── llm_analyser.py        # LLM-based fusion
-│   └── prompt.py              # LLM prompts
-│ 
-│── models/
-│   ├── download_model.py      # Model downloader
-│   ├── load_models.py         # Model loader
-│   ├── video_model/           # (Downloaded)
-│   └── audio_model/           # (Downloaded)
-│
-│── main.py                    # FastAPI application
-│── pipeline.py                # Main detection pipeline
-│── requirements.txt           # Python dependencies
-│── Dockerfile                 # Container configuration
-├── .gitignore
-└── README.md
-```
+# Commit and push
+git add README.md
+git commit -m "Fix README configuration"
+git push space main