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Marcel Weschke
2025-09-14 15:02:38 +02:00
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# 🏃‍♂️ GPX Jogging Dashboard
# 🏃‍♂️ Jogging Dashboard
An interactive Python Dash app to visualize, analyze, and explore your jogging or running sessions recorded as GPX files.
An interactive Python Dash app to visualize, analyze, and explore your jogging or running sessions recorded as GPX/FIT files.
<p align="left">
<img src="WebAppGPXDashboard.jpg" alt="Description" width="800">
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- **Info Banner** with total distance, duration, and average pace
- **Interactive Map View** with route trace and start/stop markers
- **Elevation Profile** with relative height and gradient fill
- **Speed Over Time** plot with smoothing and average line
- **Speed Over Time** plot with smoothing and average line
- **Heart Rate Over Time** plot with smoothing and average line (if .fit)
- **Deviation from Mean Speed** to see pacing consistency
- **Pace Bar Chart** showing per-kilometer pace breakdown
@@ -22,9 +23,11 @@ An interactive Python Dash app to visualize, analyze, and explore your jogging o
## Project Structure
```
app.py # Main Dash application
gpx_app.py # Main Dash application for gpx files
gpx_files/ # Folder for storing GPX files
requirements.txt # Required Python packages (TODO!)
fit_app.py # Main Dash application for fit files
fit_files/ # Folder for storing FIT files
requirements.txt # Required Python packages
README.md # This file
```
@@ -35,8 +38,8 @@ README.md # This file
### 1. Clone the repository
```bash
git clone https://github.com/yourusername/gpx-jogging-dashboard.git
cd gpx-jogging-dashboard
git clone https://github.com/yourusername/jogging-dashboard.git
cd jogging-dashboard
```
### 2. Install dependencies
@@ -55,13 +58,15 @@ pip install -r requirements.txt
- plotly
- pandas
- numpy
- scipy
- gpxpy
- fitparse
### 3. Run the app
```bash
python app.py
python fit_app.py
```
Then open your browser and go to:
@@ -71,8 +76,8 @@ Then open your browser and go to:
## Uploading Your GPX File
1. Export your activity (e.g., from Strava, Garmin, etc.) as a `.gpx` file
2. Place the file into the `gpx_files/` directory
1. Export your activity (e.g., from Strava, Garmin, etc.) as a `.gpx` or `.fit` file
2. Place the file into the `gpx_files/` or `fit_files/` directory
3. Select it via the dropdown in the dashboard
---
@@ -82,21 +87,22 @@ Then open your browser and go to:
- **Dash** (by Plotly) for building the UI and graphs
- **Pandas** for data wrangling
- **Plotly Graph Objects & Express** for advanced visuals
- **Scipy** for smoothing the data lines
- **GPXPy** for parsing `.gpx` files
- **Numpy** for vectorized math and smoothing
- **FitParse** for parsing `.fit` files
---
## Example GPX File
You can test the dashboard by placing any valid `.gpx` file in the `gpx_files/` directory. Make sure it contains track points with elevation and time data.
You can test the dashboard by either placing any valid `.gpx` file in the `gpx_files/` or any valid `.fit` file in the `fit_files/` directory. Make sure it contains track points with elevation and time data.
---
## To Do / Ideas
- [ ] Heart rate support if present in GPX
- [ ] Export graphs as images
- [X] Heart rate support if present in FIT
- [ ] Export as PDF report
- [ ] Multi-run comparison