This is a python app to predict animal and healthy status with azure custom vision service

predict.py

import requests
from dotenv import load_dotenv
import os

def classify_image(image: str, local: bool = False):
    load_dotenv()

    if local:
        endpoint = "https://japaneast.api.cognitive.microsoft.com/customvision/v3.0/Prediction/44bd0c2b-20c3-43d9-9805-2f5de1476c3b/classify/iterations/Iteration2/image"
        headers = {
            "Prediction-Key": os.getenv("PredictionKey"),
            "Content-Type": "application/octet-stream",
        }

        # read the image file and send it in the request body
        with open(image, "rb") as f:
            image_data = f.read()
        response = requests.post(endpoint, headers=headers, data=image_data)

        return response.json()
    else:
        endpoint = "https://japaneast.api.cognitive.microsoft.com/customvision/v3.0/Prediction/44bd0c2b-20c3-43d9-9805-2f5de1476c3b/classify/iterations/Iteration2/url"
        headers = {
            "Prediction-Key": os.getenv("PredictionKey"),
            "Content-Type": "application/json",
        }
        body = {"Url": image}
        response = requests.post(endpoint, headers=headers, json=body)
        return response.json()


if __name__ == "__main__":
    # predict tags for an image URL
    # url = "https://cf.ltkcdn.net/dogs/images/std/204812-800x410-Sick-dog.jpg"
    # result = classify_image(url)

    # predict tags for a local image
    image = "test.jpg"
    result = classify_image(image, local=True)
    
    # display the results on the console with top 2 tags
    print(
        [f"{x['tagName']}: {x['probability']:.2%}" for x in result["predictions"][:2]]
    )

To run the app, you need to create a .env file in the same folder, and the content should like below.

PredictionKey=yourkey

Please also install below dependencies by pip.

pip install requests python-dotenv

The app was tested in python 3.10.9 64bit.