Pass the image file that you want to recognize the object from. Receive the label and confidence score.
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.
Besides the number of API calls, there is no other limitation.
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.
Detection - Endpoint Features
| Object | Description |
|---|---|
Request Body |
[Required] File Binary |
[{"label": "boat", "confidence": "0.82", "bounding_box": {"x1": "85", "y1": "50", "x2": "621", "y2": "328"}}, {"label": "person", "confidence": "0.48", "bounding_box": {"x1": "528", "y1": "232", "x2": "541", "y2": "248"}}, {"label": "person", "confidence": "0.43", "bounding_box": {"x1": "563", "y1": "231", "x2": "573", "y2": "247"}}, {"label": "person", "confidence": "0.41", "bounding_box": {"x1": "203", "y1": "64", "x2": "217", "y2": "92"}}, {"label": "person", "confidence": "0.38", "bounding_box": {"x1": "556", "y1": "264", "x2": "572", "y2": "293"}}, {"label": "person", "confidence": "0.37", "bounding_box": {"x1": "558", "y1": "189", "x2": "578", "y2": "212"}}, {"label": "person", "confidence": "0.34", "bounding_box": {"x1": "229", "y1": "66", "x2": "240", "y2": "94"}}, {"label": "person", "confidence": "0.34", "bounding_box": {"x1": "203", "y1": "79", "x2": "216", "y2": "98"}}, {"label": "person", "confidence": "0.33", "bounding_box": {"x1": "155", "y1": "182", "x2": "173", "y2": "210"}}, {"label": "person", "confidence": "0.33", "bounding_box": {"x1": "231", "y1": "80", "x2": "241", "y2": "97"}}, {"label": "person", "confidence": "0.32", "bounding_box": {"x1": "536", "y1": "267", "x2": "554", "y2": "290"}}, {"label": "person", "confidence": "0.31", "bounding_box": {"x1": "492", "y1": "234", "x2": "510", "y2": "249"}}]
curl --location 'https://zylalabs.com/api/4394/object+detection+api/5400/detection' \
--header 'Content-Type: application/json' \
--form 'image=@"FILE_PATH"'
| Header | Description |
|---|---|
Authorization
|
[Required] Should be Bearer access_key. See "Your API Access Key" above when you are subscribed. |
No long-term commitment. Upgrade, downgrade, or cancel anytime. Free Trial includes up to 50 requests.
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.
The Detection endpoint returns a list of detected objects in the input image, including their labels, confidence scores, and bounding box coordinates. Each object is represented as a JSON object within an array.
The key fields in the response data include "label" (the identified object's name), "confidence" (the likelihood of the detection being accurate), and "bounding_box" (coordinates defining the object's location in the image).
The returned data is structured in JSON format. It consists of an array of objects, each containing "label," "confidence," and "bounding_box" fields, where "bounding_box" includes coordinates x1, y1, x2, and y2.
The Detection endpoint provides information on identified objects, including their categories (labels), confidence levels, and spatial locations within the image, enabling detailed analysis of the visual content.
The response data is organized as a JSON array, where each element corresponds to a detected object. Each object contains fields for the label, confidence score, and bounding box coordinates, facilitating easy parsing and analysis.
Typical use cases include security surveillance for threat detection, autonomous driving for obstacle recognition, e-commerce for product tagging, and healthcare for identifying anomalies in medical images.
Users can utilize the returned data by analyzing the confidence scores to filter out low-confidence detections, using bounding box coordinates for visual overlays, and categorizing objects for further processing in their applications.
Data accuracy is maintained through continuous model training on diverse datasets, regular updates, and performance evaluations. This ensures the API adapts to various contexts and improves detection capabilities over time.
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The free trial ends when you reach 50 API requests or after 7 days, whichever comes first.
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Yes, we offer a 7-day free trial that allows you to make up to 50 API calls at no cost, so you can test our APIs without any commitment.
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