{"status":"success","message":"Car analysis completed successfully","result":{"make":"Volkswagen","model":"Golf GTI","year":"2023","type":"hatchback","color":"gray","condition":"new and pristine, still in the shipping or display setup stage","exteriorFeatures":["LED headlights","red accent line on front grille","black alloy wheels","side mirrors with integrated turn signals"],"visibleModifications":["black wheels","red brake calipers"],"damages":["none visible, appears to be in perfect condition"],"confidence":"90 - Very high confidence based on the visible features and the vehicle's condition","additionalNotes":"The car is secured on a platform with straps, likely in a dealership or exhibition setting, awaiting transport or display."},"cacheTime":1761786349166,"metadata":{"language":"en","queryTime":"2025-10-30T01:05:49.166Z"}}
curl --location 'https://zylalabs.com/api/11060/car+data+capture+api/20834/vehicle+analyzer' \
--header 'Content-Type: application/x-www-form-urlencoded' \
--form 'image=@"FILE_PATH"'
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 Car Data Capture API simply include your bearer token in the Authorization header.
| Header | Description |
|---|---|
Authorization
|
Required
Should be Bearer access_key. See "Your API Access Key" above when you are subscribed.
|
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This API identifies and describes vehicles from an image. Its main objective is to provide an automatic and detailed analysis of the detected car, recognizing its make, model, estimated year, type, predominant color, visual condition, and other relevant external characteristics.
When an image is sent to the endpoint, the system processes the photograph using neural networks trained on millions of images of vehicles of different makes and models. The result includes a comprehensive report with structured information that is easy to integrate into applications or platforms.
In short, this API converts a simple image into an intelligent vehicle analysis, providing accurate visual and technical information. Thanks to its combination of artificial intelligence and image processing, it simplifies the processes of identifying, verifying, and classifying cars with a high degree of reliability and easy integration into any modern application.
The Vehicle Analyzer endpoint returns detailed information about a vehicle, including its make, model, estimated year, type, color, condition, exterior features, visible modifications, damages, confidence level, and additional notes.
Key fields in the response include "make," "model," "year," "type," "color," "condition," "exteriorFeatures," "visibleModifications," "damages," "confidence," and "additionalNotes," providing a comprehensive overview of the analyzed vehicle.
The response data is structured in a JSON format, with a top-level object containing "status," "message," and "result." The "result" object includes detailed vehicle attributes, making it easy to parse and integrate into applications.
The endpoint provides information on vehicle make, model, year, type, color, condition, external features, modifications, damages, and a confidence level, offering a thorough analysis for identification and verification.
Data accuracy is maintained through the use of advanced neural networks trained on millions of vehicle images, ensuring reliable identification and analysis based on visual features and conditions observed in the input image.
Typical use cases include vehicle identification for dealerships, insurance assessments, inventory management, and enhancing applications that require vehicle recognition and classification based on images.
Users can utilize the returned data by integrating it into applications for vehicle verification, creating detailed reports, or enhancing user experiences in automotive platforms, leveraging the structured information for various functionalities.
Users can expect consistent data patterns, such as high confidence levels for well-defined vehicles and detailed descriptions for common makes and models, while less common vehicles may yield lower confidence and fewer details.
The Vehicle Analyzer endpoint primarily accepts an image file of the vehicle for analysis. Users should ensure the image is clear and captures the vehicle's exterior features for optimal results.
Users can customize their requests by providing images from different angles or with varying lighting conditions to enhance the accuracy of the analysis. However, the API does not support additional parameters beyond the image input.
The "confidence" field indicates the reliability of the analysis, while "condition" describes the vehicle's physical state. "ExteriorFeatures" lists notable characteristics, and "damages" highlights any visible issues, providing a comprehensive overview.
The API employs advanced neural networks trained on millions of vehicle images, ensuring high-quality analysis. Continuous updates and retraining of models help maintain accuracy and reliability in vehicle identification.
If the API returns partial or empty results, users should verify the image quality and ensure it clearly depicts the vehicle. Adjusting the image angle or lighting may improve the analysis outcome in subsequent requests.
The API is designed to analyze a wide range of vehicles, including cars, trucks, and SUVs, across various makes and models. It is applicable globally, but results may vary based on the vehicle's visibility and features in the image.
Users can expect high confidence levels for well-known makes and models, with detailed descriptions. Lesser-known vehicles may yield lower confidence and fewer details, reflecting the model's training data and image clarity.
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.
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