Object Analysis API

The Object Analysis API provides developers with tools to analyze and extract insights from visual content. It identifies and categorizes objects within images or videos, enabling detailed examination and data extraction. This API supports applications in fields like image understanding, automated annotation, and visual data analytics, enhancing decision-making processes.

About the API:  

The Object Analysis API equips developers with powerful tools to analyze and interpret visual content effectively. Using advanced algorithms, it identifies, categorizes, and analyzes objects within images or videos, enabling detailed insights and data extraction. This API is invaluable for applications requiring precise image understanding, automated annotation, and visual data analytics across diverse industries. By integrating seamlessly into workflows, it enhances efficiency in tasks such as content moderation, inventory management, and automated surveillance. Developers benefit from its robust capabilities in extracting meaningful information from visual data, supporting informed decision-making and enhancing overall application functionality.

 

What this API receives and what your API provides (input/output)?

Pass the image file that you want to recognize the object from. Receive the label and confidence score. 

 

What are the most common uses cases of this API?

  • Security Surveillance: The API can be utilized in security systems to monitor and analyze live video feeds, identifying potential threats such as unauthorized access, suspicious objects, or unusual activities, enhancing real-time security response.

  • Autonomous Driving: In self-driving cars, the API plays a crucial role in identifying and classifying objects on the road, such as pedestrians, other vehicles, traffic signs, and obstacles, ensuring safe and efficient navigation.

  • E-Commerce: Online retailers can use the API to automatically tag and categorize products in images, improving search functionality, product recommendations, and inventory management by recognizing items and their attributes.

  • Healthcare: In medical imaging, the API aids in diagnosing conditions by detecting anomalies in X-rays, MRIs, or CT scans, such as tumors, fractures, or other medical conditions, thus supporting accurate and timely diagnosis.

  • Augmented Reality (AR): The API enhances AR applications by detecting and tracking objects in real-time, enabling interactive experiences such as virtual object placement, real-time information overlays, and immersive gaming environments.

 

Are there any limitations to your plans?

Besides the number of API calls, there is no other limitation.

API Documentation

Endpoints


Given an input image, return a list of detected objects labels, confidence percentages and bounding boxes. Objects with confidence less than 0.3 (30%) are filtered out.



                                                                            
POST https://zylalabs.com/api/4496/object+analysis+api/5517/detection
                                                                            
                                                                        

Detection - Endpoint Features

Object Description
Request Body [Required] File Binary
Test Endpoint

API EXAMPLE RESPONSE

       
                                                                                                        
                                                                                                                                                                                                                            [{"label": "dog", "confidence": "0.82", "bounding_box": {"x1": "29", "y1": "200", "x2": "886", "y2": "847"}}]
                                                                                                                                                                                                                    
                                                                                                    

Detection - CODE SNIPPETS


    curl --location 'https://zylalabs.com/api/4496/object+analysis+api/5517/detection' \
    --header 'Content-Type: application/json' \ 
    --form 'image=@"FILE_PATH"'


API Access Key & Authentication

After signing up, every developer is assigned a personal API access key, a unique combination of letters and digits provided to access to our API endpoint. To authenticate with the Object Analysis API REST API, simply include your bearer token in the Authorization header.
Headers
Header Description
Authorization [Required] Should be Bearer access_key. See "Your API Access Key" above when you are subscribed.

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The API supports various image formats, including JPEG, PNG, BMP, and TIFF. It can process images of different resolutions, though higher quality images may yield more accurate results.

The API is designed to detect and recognize multiple objects within a single image. It returns bounding boxes for each identified object along with the corresponding classification labels and confidence scores.

The API delivers high accuracy in object detection, with precision and recall metrics varying based on the complexity of the scene and the quality of the input image. Regular updates and model improvements enhance performance over time.

The response time depends on the image size and the number of objects within the image. Generally, the API is optimized for low latency, providing results within a few hundred milliseconds for standard image sizes.

While the API comes pre-trained on large, diverse datasets, customization options are available. Users can fine-tune the model on their own datasets to improve accuracy for specific object categories relevant to their application.

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