MediaGPS2Map 🌍📸

An interactive heatmap tool to visualize your photo and video geolocation data, supporting large datasets and high-performance rendering.

Translation

中文文档：README_zh.md

Key Features

✅ Incremental updates with --add-data option ✅ Supports multiple media formats: HEIC/HEIF, JPG, PNG, MP4, MOV, and other mainstream photo and video formats
✅ Intelligent GPS data parsing (photo + video location)
✅ AMap API address parsing (automatic coordinate correction)
✅ Dynamic heatmap rendering (supports testing with 100,000+ data points)
✅ Responsive sidebar statistics panel
✅ Customizable heatmap style adjustment
✅ Spatiotemporal filtering (filter by time and map area)
✅ Efficient mechanical hard drive storage optimization

Quick Start

Prerequisites

• Python 3.8+
• ExifTool (Installation Guide)
• AMap API Key (Apply Here)

Installation Steps

1. Clone the repository:

git clone https://github.com/optimistices-me/MediaGPS2Map.git
cd MediaGPS2Map

2. Install dependencies:

pip install flask requests

3. Configure config.json:

{
    "AMAP_API_KEY": "Your AMap API key",
    "directories": [
        "Directory 1",
        "Directory 2"
    ],
    "batch_size": 200
}

Running the Program

1. Initialize the database (first-time run):

python app_hdd.py

2. Add new media files (incremental update):

python app_hdd.py --add-data "newDirectory"

3. Start the service (for subsequent runs, use --skip-db to skip database initialization):

python app_hdd.py --skip-db

4. Access the webpage:

Open your browser and go to http://localhost:5000

User Guide

1. Heatmap Interaction

• Drag the timeline to filter the date range
• Zoom the map to view heat distribution at different levels
• Click on a hotspot to view detailed media file information

2. Sidebar Features

• Real-time statistics of the data in the current view
• Display typical geographic location distribution
• Adjust heatmap parameters (radius/blurriness/opacity)

3. Performance Optimization

• When using mechanical hard drives, it is recommended to set batch_size=200-1000
• Zoom to the appropriate level to automatically aggregate data points
• Use WAL mode to enhance database concurrency performance

Tech Stack

• Backend: Python + Flask + SQLite
• Frontend: Leaflet + Leaflet.heat
• Geoservices: AMap API
• Metadata Parsing: ExifTool

Configuration Parameters

Parameter	Default Value	Description
batch_size	500	File processing batch size (recommended 200-500 for mechanical hard drives)
AMAP_API_KEY	Required	AMap Web Service API Key
directories	Required	List of media file storage paths

Notes

❗ Do not expose the API key in config.json

❗ Processing a large number of files for the first time may take a long time (recommended to run in the background)

❗ Windows systems require ExifTool to be installed separately and added to the PATH

License

MIT License © 2025 Optimistices-Me