Redback-Operations · ishita230702 · Sep 5, 2025 · Sep 13, 2025 · Sep 14, 2025 · Sep 15, 2025
diff --git a/.gitignore b/.gitignore
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+# Node
+node_modules/
+.vite/
+
+# Python
+__pycache__/
+*.pyc
+*.pyo
+
+
+# Python virtual environments
+venv/
+venv*/
+*/venv*/
+*/venv310/
+
+# Env
+.env
+
+# Generated data/outputs
+backend/data/
+backend/analytics/
+backend/uploads/
+backend/heatmaps/
+
+# OS junk
+*.log
+*.DS_Store
+Thumbs.db
+
+# Generated analytics
+tracking_code/analytics/
diff --git a/Player_Tracking/afl_player_tracking_and_crowd_monitoring/backend/README.md b/Player_Tracking/afl_player_tracking_and_crowd_monitoring/backend/README.md
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+📄 README.md (Backend Service)
+# ⚡ Backend Service (FastAPI + PostgreSQL)
+
+This backend service manages:
+- Video uploads
+- Player tracking inference (calls Player Tracking microservice)
+- Crowd monitoring inference (calls external API provided by Son Tung Bui)
+- Authentication (JWT)
+- Analytics storage in PostgreSQL
+
+---
+
+## ⚙️ Requirements
+
+- **Python 3.10** (recommended)
+- **PostgreSQL 15** (via Docker or local installation)
+
+---
+
+## 📦 Setup Instructions
+
+### 1. Clone the repository
+```bash
+git clone https://github.com/<your-repo>.git
+cd afl-redback-orion/Player_Tracking/afl_player_tracking_and_crowd_monitoring/backend
+
+2. Create a virtual environment
+py -3.10 -m venv venv
+.\venv\Scripts\activate   # (Windows)
+# or
+source venv/bin/activate  # (Linux/Mac)
+
+3. Upgrade pip
+python -m pip install --upgrade pip
+
+4. Install dependencies
+pip install -r requirements.txt
+
+🗄️ Run PostgreSQL in Docker
+
+Run PostgreSQL locally in Docker:
+
+docker run --name afl-postgres ^
+  -e POSTGRES_USER=postgres ^
+  -e POSTGRES_PASSWORD=postgres ^
+  -e POSTGRES_DB=aflvision ^
+  -p 5432:5432 ^
+  -d postgres:15
+
+⚙️ Environment Variables
+
+Create a .env file inside the backend/ folder:
+
+# Database connection
+DATABASE_URL=postgresql+psycopg2://postgres:postgres@localhost:5432/aflvision
+
+# JWT secret key
+JWT_SECRET=your-secret-key
+
+🌐 Configure Crowd Monitoring API
+
+Open:
+
+backend/routes/crowd.py
+
+
+Update this line with the API URL provided by Son Tung Bui:
+
+CROWD_API_URL = "https://<provided-api-url>/analyze_frame/"
+
+🚀 Run the Backend
+
+Start the FastAPI server:
+
+uvicorn main:app --reload --port 8000
+
+
+Backend will run at:
+
+http://127.0.0.1:8000
+
+
+Swagger docs available at:
+
+http://127.0.0.1:8000/docs
+
+🧪 Example Workflow
+
+Upload a video via backend → stored in uploaded_videos/.
+
+Backend calls:
+
+Player Tracking Service (http://127.0.0.1:8001)
+
+Crowd Monitoring API (Son Tung Bui’s endpoint).
+
+PostgreSQL stores analytics + user data.
+
+Results available via API endpoints.
+
+🛠️ Notes
+
+Ensure PostgreSQL is running before starting backend.
+
+Update CROWD_API_URL whenever Son Tung Bui provides a new endpoint (e.g., ngrok link).
+
+Works best when combined with Player Tracking Service.
diff --git a/...er_Tracking/afl_player_tracking_and_crowd_monitoring/backend/TRACKING_README.md b/...er_Tracking/afl_player_tracking_and_crowd_monitoring/backend/TRACKING_README.md
@@ -0,0 +1,187 @@
+# Player Tracking Analysis System
+
+This system implements the player tracking logic from the Week 5-6 notebook, providing a comprehensive backend API for analyzing player movement data, generating heatmaps, and computing player statistics.
+
+## Features
+
+### 🎯 **Core Functionality**
+- **CSV Upload & Processing**: Handle tracking data in the same format as the notebook
+- **Player Statistics**: Calculate distance, speed, participation, and intensity metrics
+- **Heatmap Generation**: Create movement heatmaps for individual players
+- **Movement Path Analysis**: Extract detailed movement trajectories
+- **Real-time Processing**: Fast analysis with configurable parameters
+
+### 📊 **Player Metrics Computed**
+- **Frame Count**: Total frames each player appears in
+- **Total Distance**: Cumulative movement in pixels
+- **Average Speed**: Mean movement speed (pixels/second)
+- **Max Speed**: Peak movement speed
+- **Participation Score**: Time presence ratio
+- **Intensity Score**: Average confidence level
+- **Confidence Statistics**: Min, max, and average confidence
+
+### 🗺️ **Heatmap Generation**
+- **Field Scaling**: Automatically scales to AFL oval dimensions (165m x 135m)
+- **Configurable Grid**: Adjustable resolution (default: 200x150 cells)
+- **Gaussian Smoothing**: Configurable sigma for visual appeal
+- **Confidence Weighting**: Heatmap intensity based on detection confidence
+
+## API Endpoints
+
+### 📤 **Upload & Processing**
+```
+POST /api/v1/tracking/upload-csv
+```
+Upload a tracking CSV file and get basic dataset information.
+
+### 📈 **Player Statistics**
+```
+POST /api/v1/tracking/player-stats
+```
+Upload CSV file to get comprehensive statistics for all players in the dataset.
+
+### 🗺️ **Heatmap Generation**
+```
+POST /api/v1/tracking/generate-heatmap
+```
+Generate a heatmap for a specific player with configurable parameters.
+
+### 🖼️ **Heatmap Retrieval**
+```
+GET /api/v1/tracking/heatmap/{filename}
+```
+Retrieve a generated heatmap image.
+
+### 🏃 **Movement Analysis**
+```
+POST /api/v1/tracking/player-movement/{player_id}
+```
+Upload CSV file to get detailed movement path data for a specific player.
+
+### 📋 **Player Information**
+```
+POST /api/v1/tracking/available-players
+```
+Upload CSV file to get list of all available player IDs in the dataset.
+
+### 🧹 **Cleanup**
+```
+DELETE /api/v1/tracking/cleanup-heatmaps
+```
+Remove all generated heatmap files.
+
+## CSV Format Requirements
+
+The system expects CSV files with the following columns:
+
+| Column | Type | Description |
+|--------|------|-------------|
+| `frame_id` | int | Frame number from video |
+| `player_id` | int | Unique player identifier |
+| `timestamp_s` | float | Timestamp in seconds |
+| `x1, y1` | int | Top-left bounding box coordinates |
+| `x2, y2` | int | Bottom-right bounding box coordinates |
+| `cx, cy` | int | Center coordinates (auto-calculated if missing) |
+| `w, h` | int | Bounding box width and height |
+| `confidence` | float | Detection confidence (0.0-1.0) |
+
+## Usage Examples
+
+### 1. **Upload and Process CSV**
+```bash
+curl -X POST "http://localhost:8000/api/v1/tracking/upload-csv" \
+     -H "Content-Type: multipart/form-data" \
+     -F "file=@tracking.csv"
+```
+
+### 2. **Get Player Statistics**
+```bash
+curl -X POST "http://localhost:8000/api/v1/tracking/player-stats" \
+     -H "Content-Type: multipart/form-data" \
+     -F "file=@tracking.csv"
+```
+
+### 3. **Generate Player Heatmap**
+```bash
+curl -X POST "http://localhost:8000/api/v1/tracking/generate-heatmap" \
+     -H "Content-Type: multipart/form-data" \
+     -F "player_id=1" \
+     -F "file=@tracking.csv" \
+     -F "field_length=165" \
+     -F "field_width=135" \
+     -F "nx=200" \
+     -F "ny=150" \
+     -F "sigma=2.0"
+```
+
+### 4. **Get Movement Path**
+```bash
+curl -X POST "http://localhost:8000/api/v1/tracking/player-movement/1" \
+     -H "Content-Type: multipart/form-data" \
+     -F "file=@tracking.csv"
+```
+
+## Configuration Options
+
+### **Heatmap Parameters**
+- `field_length`: Field length in meters (default: 165)
+- `field_width`: Field width in meters (default: 135)
+- `nx`: Grid resolution in X direction (default: 200)
+- `ny`: Grid resolution in Y direction (default: 150)
+- `sigma`: Gaussian smoothing parameter (default: 2.0)
+
+### **Performance Tuning**
+- **Grid Resolution**: Higher values (400x300) for detailed analysis, lower (100x75) for faster processing
+- **Smoothing**: Higher sigma (3.0-5.0) for smoother visuals, lower (1.0-2.0) for sharper details
+
+## Integration with Frontend
+
+The system is designed to work seamlessly with React frontends:
+
+1. **Upload Interface**: Drag & drop CSV files
+2. **Player Selection**: Dropdown with available player IDs
+3. **Real-time Analysis**: Instant statistics and heatmap generation
+4. **Visual Dashboard**: Display heatmaps, movement paths, and metrics
+
+## Error Handling
+
+The system includes comprehensive error handling for:
+- **Invalid CSV Format**: Missing columns or wrong data types
+- **File Processing Errors**: Corrupted or unreadable files
+- **Player Not Found**: Invalid player ID requests
+- **Memory Issues**: Large dataset handling
+
+## Performance Considerations
+
+- **Large Datasets**: Optimized for datasets with 1000+ frames
+- **Memory Usage**: Efficient pandas operations with minimal memory overhead
+- **Heatmap Generation**: Fast processing with matplotlib optimization
+- **File Storage**: Automatic cleanup of generated heatmaps
+
+## Dependencies
+
+- **pandas**: Data processing and analysis
+- **numpy**: Numerical computations
+- **matplotlib**: Heatmap visualization
+- **scipy**: Gaussian filtering
+- **PIL**: Image processing
+- **fastapi**: Web framework
+
+## Testing
+
+Use the included `sample_tracking.csv` file to test the system:
+
+```bash
+# Test with sample data
+curl -X POST "http://localhost:8000/api/v1/tracking/upload-csv" \
+     -H "Content-Type: multipart/form-data" \
+     -F "file=@sample_tracking.csv"
+```
+
+## Future Enhancements
+
+- **Batch Processing**: Handle multiple CSV files simultaneously
+- **Advanced Analytics**: Acceleration, direction changes, player interactions
+- **Real-time Streaming**: Process live video feeds
+- **Machine Learning**: Predictive movement patterns
+- **Export Formats**: JSON, CSV, and image exports
diff --git a/Player_Tracking/afl_player_tracking_and_crowd_monitoring/backend/__init__.py b/Player_Tracking/afl_player_tracking_and_crowd_monitoring/backend/__init__.py
diff --git a/...ng_and_crowd_monitoring/backend/analytics/crowd_8703ba69-e28a-4c3f-9e45-81ba616dec15.json b/...ng_and_crowd_monitoring/backend/analytics/crowd_8703ba69-e28a-4c3f-9e45-81ba616dec15.json
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diff --git a/...ing/afl_player_tracking_and_crowd_monitoring/backend/app/__pycache__/main.cpython-313.pyc b/...ing/afl_player_tracking_and_crowd_monitoring/backend/app/__pycache__/main.cpython-313.pyc
diff --git a/Player_Tracking/afl_player_tracking_and_crowd_monitoring/backend/app/main.py b/Player_Tracking/afl_player_tracking_and_crowd_monitoring/backend/app/main.py