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Object Detection in an Image using Python REST API

Follow this article for Python ImagingApi object detection in an image using the REST API. You will learn image processing for object detection with the help of the Aspose.Imaging Cloud SDK for Python, covering the entire workflow from uploading an image to saving the output with detected objects. For more format details, see the JPG file info and PNG file info pages.

Prerequisite

Steps for Image Object Recognition using Python Low Code API

  1. Create the ImagingApi using your credentials and cloud endpoint to detect an image object
  2. Define the source image file path and set the file path for the output image
  3. Define the detection parameters, including detection method, confidence threshold, and a flag to include labels and scores
  4. Load the input image file into a stream for API processing
  5. Create the CreateVisualObjectBoundsRequest using the image stream and custom detection options
  6. Output the request configuration details to the console for debugging
  7. Invoke the CreateVisualObjectBounds call to detect objects and generate an output image stream with visual bounding boxes
  8. Save the resulting stream as an output image

These steps summarize the process for image object identification using the Python REST API. First, you set up the Imaging API with your credentials, choose the input and output image paths, configure the object detection settings, and load the source image as a stream while logging the request details for visibility. Then, you send the request to detect objects in the image and save the returned stream as a new image with visual bounding boxes applied.

Code for Object Detection in Image using Python RESTful Service

This code demonstrates image processing and object detection using the Python Low Code API. You may add dynamic detection tuning for switching the detection models. If you set the debug flag to true, detailed messages are displayed throughout the detection process by the API.

This article has taught us the process for image processing and object recognition. To detect duplicate images in a collection of images, refer to the article Detect Duplicate Images using Reverse Image Search with Python REST API.

Keywords: image detection using Python REST Interface; object detection in an image using Python REST API; image processing for object detection using Python-based API; image object identification using Python REST API; image processing and object detection using Python Low Code API.