Image processing is made easy with platforms like landing.ai

As an example, the following is an application that counts cars in drone images. The dataset is based on 512x512 resolution images of highways and is annotated in the Pascal VoC format. The model is hosted and usable with a sample web-request as follows:

from PIL import Image

from landingai.predict import Predictor

# Enter your API Key

endpoint_id = "11cb6c44-3b6a-4b47-bac9-031826bc80ea"

api_key = "YOUR_API_KEY"

# Load your image

image = Image.open("image.png")

# Run inference

predictor = Predictor(endpoint_id, api_key=api_key)

predictions = predictor.predict(image)

And it can even be requested with agentic ai framework as follows:

import requests

url = "https://api.va.landing.ai/v1/tools/agentic-object-detection"

files = {

  "image": open("{{path_to_image}}", "rb")

}

data = {

  "prompts": "{{prompt}}",

  "model": "agentic"

}

headers = {

  "Authorization": "Basic {{your_api_key}}"

}

response = requests.post(url, files=files, data=data, headers=headers)

print(response.json())

For context on DFCS drone video sensing platform, please check the references.