ml_features.py advanced_visualization.py advanced_example.py README.md ERROR_CHECK_REPORT.md example_events.py

README.md

# Sports Analysis Dataset



## Overview

Sports video dataset with game footage, player tracking, and event annotations for sports analytics and performance analysis.

This dataset contains sports video footage with player tracking, game events, and performance annotations. Perfect for sports analytics, player tracking, event detection, and performance analysis applications.

## Dataset Information

- **ID**: 29
- **Title**: Sports Analysis Dataset
- **Category**: Video Data
- **Difficulty**: Advanced
- **Technologies**: MP4, MOV, OpenCV, Tracking, Video Analysis

## Features

- ✅ Game footage
- ✅ Player tracking
- ✅ Event annotations
- ✅ Multiple sports
- ✅ Ready for sports AI

## Technologies Used

- **MP4**: Standard video format for game footage
- **MOV**: Alternative video format support
- **OpenCV**: Computer vision and image processing
- **Tracking**: Player and object tracking algorithms
- **Video Analysis**: Advanced video processing and analytics

## Installation

1. Download the dataset from the [download section](#download) or use the direct link: `./sports-analysis/sports-analysis.zip`
2. Extract the ZIP file to your desired location
3. Review the documentation included in the dataset

## Usage

This dataset is designed for:

- Sports analytics research
- Player tracking algorithm development
- Event detection and classification
- Performance analysis applications
- Machine learning and AI model training
- Computer vision projects

## File Structure

```
sports-analysis/
├── index.html # Main demo page
├── README.md # This file
├── assets/
│ ├── css/
│ │ └── style.css # Stylesheet
│ └── js/
│ └── main.js # JavaScript functionality
├── sports-analysis.zip # Dataset archive
└── sports-analysis.png # Project image
```

## Demo

Visit the demo page at: `./sports-analysis/`

## Contact

**RSK World**

- **Founder**: Molla Samser
- **Designer & Tester**: Rima Khatun
- **Email**: help@rskworld.in
- **Phone**: +91 93305 39277
- **Address**: Nutanhat, Mongolkote, Purba Burdwan, West Bengal, India, 713147
- **Website**: https://rskworld.in/

## License

This dataset is provided by RSK World for research and development purposes.

## Support

For questions, support, or inquiries about this dataset, please contact us at help@rskworld.in or visit https://rskworld.in/

---

© 2026 RSK World. All rights reserved.

ERROR_CHECK_REPORT.md

Raw Download

ERROR_CHECK_REPORT.md

# Error Check Report



## Issues Found and Fixed

### ✅ Fixed: File Path Issues in games_metadata.json

**Problem:** File paths in `data/metadata/games_metadata.json` were missing the "data/" prefix.

**Files Affected:**
- `data/metadata/games_metadata.json`

**Fix Applied:**
- Updated `tracking_file` paths: `"annotations/tracking_001.json"` → `"data/annotations/tracking_001.json"`
- Updated `events_file` paths: `"annotations/events_001.json"` → `"data/annotations/events_001.json"`
- Updated `video_file` paths: `"videos/game_001.mp4"` → `"data/videos/game_001.mp4"`
- Updated `performance_file` paths: `"annotations/performance_metrics_001.csv"` → `"data/annotations/performance_metrics_001.csv"`

**Impact:** This ensures that both browser-based JavaScript fetch calls and server-side file access work correctly.

---

### ✅ Fixed: Duplicate Scripts in package.json

**Problem:** `package.json` had duplicate "scripts" keys which is invalid JSON.

**Files Affected:**
- `package.json`

**Fix Applied:**
- Removed duplicate scripts entry (kept the one with API server configuration)
- Consolidated scripts to include both server and HTTP server options

**Result:**
```json
"scripts": {
"start": "node server.js",
"dev": "node server.js",
"serve": "npx http-server . -p 8080"
}
```

---

## Verification Results

### ✅ JSON Files
- `data/metadata/games_metadata.json` - ✅ Valid
- `package.json` - ✅ Valid
- All other JSON files - ✅ Valid

### ✅ Python Files
- `examples/statistics_calculator.py` - ✅ Syntax OK
- `examples/example_tracking.py` - ✅ Syntax OK
- `examples/example_events.py` - ✅ Syntax OK
- `scripts/create_dataset_zip.py` - ✅ Syntax OK

### ✅ HTML Files
- `index.html` - ✅ No linting errors
- `dashboard.html` - ✅ No linting errors
- `explorer.html` - ✅ No linting errors
- `api.html` - ✅ No linting errors

### ✅ JavaScript Files
- `assets/js/main.js` - ✅ No linting errors
- `assets/js/dashboard.js` - ✅ No linting errors
- `assets/js/explorer.js` - ✅ No linting errors

### ✅ CSS Files
- `assets/css/style.css` - ✅ No linting errors
- `assets/css/dashboard.css` - ✅ No linting errors
- `assets/css/explorer.css` - ✅ No linting errors

### ✅ Node.js Files
- `server.js` - ✅ Syntax OK (requires npm install for dependencies)

---

## File Structure Verification

All expected files and directories are present:

✅ `/assets/css/` - CSS files present
✅ `/assets/js/` - JavaScript files present
✅ `/data/annotations/` - Annotation files present
✅ `/data/metadata/` - Metadata files present
✅ `/data/videos/` - README present
✅ `/docs/` - Documentation present
✅ `/examples/` - Example scripts present
✅ `/scripts/` - Utility scripts present

---

## Remaining Notes

### Dependencies
To use the API server (`server.js`), run:
```bash
npm install
```

This will install:
- express
- cors

### Image File
The project references `sports-analysis.png` which exists in the project root.

### ZIP File
The `sports-analysis.zip` file exists and contains the dataset.

---

## Summary

**Total Issues Found:** 2
**Total Issues Fixed:** 2
**Status:** ✅ All Clear

All files have been checked and validated. The project is ready for use!

---

**RSK World**
- Email: help@rskworld.in
- Website: https://rskworld.in/

© 2026 RSK World. All rights reserved.

examples/example_events.py

Raw Download

#!/usr/bin/env python3
"""
RSK World
Founder: Molla Samser
Designer & Tester: Rima Khatun
Email: help@rskworld.in
Phone: +91 93305 39277
Address: Nutanhat, Mongolkote, Purba Burdwan, West Bengal, India, 713147
Website: https://rskworld.in/

Example script for event detection and analysis using the Sports Analysis Dataset
"""

import json
from collections import Counter
from datetime import datetime

def load_events(json_path):
    """
    Load event annotations from JSON file
    
    Args:
        json_path: Path to events JSON file
        
    Returns:
        List of event dictionaries
    """
    with open(json_path, 'r') as f:
        return json.load(f)

def analyze_events(events):
    """
    Analyze events and generate statistics
    
    Args:
        events: List of event dictionaries
        
    Returns:
        Dictionary with statistics
    """
    stats = {
        'total_events': len(events),
        'event_types': Counter([e['event_type'] for e in events]),
        'events_by_player': Counter([e.get('player_id', 'unknown') for e in events]),
        'time_range': {
            'start': min([e['timestamp'] for e in events]),
            'end': max([e['timestamp'] for e in events])
        }
    }
    return stats

def filter_events_by_type(events, event_type):
    """
    Filter events by type
    
    Args:
        events: List of event dictionaries
        event_type: Type to filter by
        
    Returns:
        Filtered list of events
    """
    return [e for e in events if e['event_type'] == event_type]

def print_statistics(stats):
    """
    Print event statistics in a readable format
    
    Args:
        stats: Statistics dictionary
    """
    print("\n=== Event Statistics ===")
    print(f"Total Events: {stats['total_events']}")
    print("\nEvents by Type:")
    for event_type, count in stats['event_types'].items():
        print(f"  {event_type}: {count}")
    print("\nTop Players by Events:")
    for player_id, count in stats['events_by_player'].most_common(5):
        print(f"  Player {player_id}: {count} events")
    print(f"\nTime Range: {stats['time_range']['start']} to {stats['time_range']['end']}")

def main():
    """
    Main function to run event analysis example
    """
    # Example path (adjust based on your dataset structure)
    events_path = '../data/annotations/events_001.json'
    
    print("Loading event data...")
    events = load_events(events_path)
    
    print("Analyzing events...")
    stats = analyze_events(events)
    print_statistics(stats)
    
    # Example: Filter goals
    print("\n=== Goals ===")
    goals = filter_events_by_type(events, 'goal')
    print(f"Total Goals: {len(goals)}")
    for goal in goals:
        print(f"  Player {goal.get('player_id', 'unknown')} at {goal['timestamp']}")

if __name__ == '__main__':
    main()

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