https://github.com/sentinel-hub/classification-app-backend
Code to reproduce the back-end service for ClassificationApp
https://github.com/sentinel-hub/classification-app-backend
Last synced: about 2 months ago
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Code to reproduce the back-end service for ClassificationApp
- Host: GitHub
- URL: https://github.com/sentinel-hub/classification-app-backend
- Owner: sentinel-hub
- License: mit
- Created: 2019-06-18T08:24:20.000Z (almost 6 years ago)
- Default Branch: master
- Last Pushed: 2019-06-18T08:40:18.000Z (almost 6 years ago)
- Last Synced: 2025-01-19T06:52:33.549Z (3 months ago)
- Language: Python
- Homepage: https://apps.sentinel-hub.com/classificationApp/#lat=16.969046833518632&lng=36.77102565765381&zoom=14
- Size: 115 KB
- Stars: 3
- Watchers: 3
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE.md
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README
# ClassificationApp back-end service
A server site support for [ClassificationApp](https://apps.sentinel-hub.com/classificationApp/#lat=16.969046833518632&lng=36.77102565765381&zoom=14).
**In order to run the back-end service, a Geopedia or equivalent database with
tables as defined in `schemas.py` needs to be created. Get in touch if you are interested in
reproducing the results using Geopedia.**
A valid Sentinel Hub instance ID is required to retrieve Sentinel imagery. The instance ID
need be added to the `data/input_sources.json` file.
## How to run the service
There are multiple ways how to run the service:
### Running development server locally (using pip)
(Required: Python >= 3.5)
- Clone git repository, move to the main project folder and install the project as a normal Python package. The following will install it in editable mode:
```bash
pip install -e . --upgrade
```
(On Windows some dependency packages might raise an error during installation. Install them from [wheels repo](https://www.lfd.uci.edu/~gohlke/pythonlibs/).)
- Start running the service with:
```bash
python main.py
```
### Running development server locally (using pipenv)
(Required: Python >= 3.5)
- Clone git repository, move to the main project folder and install packages:
```bash
pipenv install
```
- Enter virtual environment:
```bash
pipenv shell
```
- Start the service:
```bash
python main.py
```
### Running production server locally
(Required: docker)
- Clone git repository, move to the main project folder and create a docker image:
```bash
docker build . --tag=class-service
```
- Run the image in a container:
```bash
docker run -p 5000:80 class-service
```
(The service will be available at port 5000)
## Development
### Service end points
The running service will produce a swagger documentation at `/docs` (e.g locally that is 'http://127.0.0.1:5000/docs').
For more details check `./classification-service/service.py`. There you will also see example calls with `curl`.