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.
[{"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.
To obtain your API key, first sign in to your account and navigate to the API you want to use. From the API's Pricing section, choose a plan and complete the subscription process. Once subscribed, return to the API page and you will see your API Access Key displayed at the top of the documentation page. You can use this key to authenticate your requests.
You can’t switch APIs during the free trial. If you subscribe to a different API, your trial will end and the new subscription will start as a paid plan.
The free trial lasts for 7 days and allows you to make up to 50 API requests.
No, the free trial is available only once, so we recommend using it on the API that interests you the most. Most of our APIs offer a free trial, but some may not include this option.
Yes. If the API offers a free trial, you will see a "Free 7-Day Trial" option in its Pricing section. The trial lasts for 7 days and allows up to 50 API requests, enabling you to evaluate the API before subscribing to a paid plan.
Zyla API Hub is like a big store for APIs, where you can find thousands of them all in one place. We also offer dedicated support and real-time monitoring of all APIs. Once you sign up, you can pick and choose which APIs you want to use. Just remember, each API needs its own subscription. But if you subscribe to multiple ones, you'll use the same key for all of them, making things easier for you.
You can monitor your API usage through the response headers included with every request:
x-zyla-api-calls-monthly-used: Shows the total number of API requests you have used during the current billing period.
x-zyla-api-calls-monthly-remaining: Shows the number of API requests you have remaining for the current billing period.
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Please have a look at our Refund Policy: https://zylalabs.com/terms#refund
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