object-detection

📷 Object Detection using Cloudmersive Vision API

A Python Cloud Function for object detection from an image URL.

Example input:

{
    "url": "https://picsum.photos/seed/open___runtimes/1000/1000"
}

Example output:

{
    "url": "https://picsum.photos/seed/open___runtimes/1000/1000",
    "name": "cake",
    "confidence": 0.7977721691131592,
    "x": 21,
    "y": 5,
    "width": 494,
    "height": 333
}

📝 Environment Variables

List of environment variables used by this cloud function:

CLOUDMERSIVE_API_KEY - Your Cloudmersive API key.

🚀 Deployment

1. Clone this repository, and enter this function folder:

$ git clone https://github.com/open-runtimes/examples.git && cd examples
$ cd python/object-detection

2. Enter this function folder and build the code:

docker run --rm --interactive --tty --volume $PWD:/usr/code openruntimes/python:v2-3.10 sh /usr/local/src/build.sh

As a result, a code.tar.gz file will be generated.

3. Start the Open Runtime:

docker run -p 3000:3000 -e INTERNAL_RUNTIME_KEY=secret-key -e INTERNAL_RUNTIME_ENTRYPOINT=main.py --rm --interactive --tty --volume $PWD/code.tar.gz:/tmp/code.tar.gz:ro openruntimes/python:v2-3.10 sh /usr/local/src/start.sh

Make sure to replace YOUR_API_KEY without your key.

Your function is now listening on port 3000, and you can execute it by sending POST request with appropriate authorization headers. To learn more about runtime, you can visit Python runtime README.

📝 Notes

• This function is designed for use with Appwrite Cloud Functions. You can learn more about it in Appwrite docs.
• This example is compatible with Python 3.10. Other versions may work but are not guaranteed to work as they haven't been tested.