PyTorch FastAPI Image Prediction

Run the Application

To run the FastAPI application locally, use the following command:

make run

This will start the server at http://127.0.0.1:8000.

Send an Image

To send an image for prediction, you can use the following curl command:

make send-image

This command will POST the image located at test_images/dog.png to the /predict/ endpoint of the API. Make sure to replace the path with the image you want to test.

Docker Commands

If you prefer to run the application in a Docker container, you can use the following commands:

Build the Docker Image

To build the Docker image, run:

make docker-build

Run the Docker Container

To run the Docker container, use:

make docker-run

This will start the container and expose the application on port 8000.

API Endpoint

POST /predict/: Upload an image and receive the predicted class.

Example Request

curl -X POST     'http://127.0.0.1:8000/predict/'     -H 'accept: application/json'     -H 'Content-Type: multipart/form-data'     -F 'file=@test_images/dog.png'

Response

The response will include the predicted class in JSON format:

{
    "predicted_class": "your_class_name"
}