Technical Specifications of kling-image-recognize
| Specification | Details |
|---|---|
| Model ID | kling-image-recognize |
| Category | Image recognition / multimodal analysis |
| Primary Capability | Recognizes image elements for downstream creative workflows, including multi-image reference video generation and multimodal video editing |
| Input Type | Image input |
| Output Type | Structured recognition results |
| Recognition Scope | Subjects, faces, clothing, and other visual elements |
| Result Volume | Can return up to 4 sets of results per request, if available |
| Use Cases | Visual asset analysis, reference preparation for video generation, content understanding for editing pipelines, subject and apparel recognition |
What is kling-image-recognize?
kling-image-recognize is a Keling image element recognition API designed to analyze visual content and identify important elements within an image. It is especially useful in workflows that require multi-image reference video generation or multimodal video editing, where understanding the contents of source images is an important preprocessing step.
The model can recognize a range of visual attributes such as subjects, faces, clothing, and related image components. Depending on the input, it can provide up to 4 sets of recognition results in a single request, helping developers capture multiple possible detections or interpretations when available.
Main features of kling-image-recognize
- Image element recognition: Detects and identifies important visual elements contained in an input image.
- Subject analysis: Recognizes primary subjects that can be used in downstream media generation or editing workflows.
- Face recognition support: Extracts face-related recognition results when faces are present in the image.
- Clothing identification: Detects apparel and clothing-related elements to support more detailed visual understanding.
- Multi-image reference workflow support: Useful for preparing and analyzing image references used in video generation pipelines.
- Multimodal video editing compatibility: Helps power editing scenarios where image content needs to be understood before transformation or composition.
- Multiple result sets per request: Can obtain up to 4 sets of results per request, if available, enabling richer recognition output.
- Integration-friendly API usage: Suitable for developers building automated media analysis and creative application pipelines.
How to access and integrate kling-image-recognize
Step 1: Sign Up for API Key
To get started, sign up on the CometAPI platform and generate your API key from the dashboard. After obtaining your key, store it securely and use it to authenticate every request to the kling-image-recognize API.
Step 2: Send Requests to kling-image-recognize API
Once you have your API key, send requests to the CometAPI endpoint using kling-image-recognize as the model ID. Include your authentication headers and provide the required image input payload based on your application workflow.
curl --request POST \
--url https://api.cometapi.com/v1/responses \
--header "Authorization: Bearer YOUR_COMETAPI_KEY" \
--header "Content-Type: application/json" \
--data '{
"model": "kling-image-recognize",
"input": [
{
"role": "user",
"content": [
{
"type": "input_text",
"text": "Recognize the main visual elements in this image."
},
{
"type": "input_image",
"image_url": "YOUR_IMAGE_URL"
}
]
}
]
}'
Step 3: Retrieve and Verify Results
After submission, the API returns recognition results generated by kling-image-recognize. Parse the response in your application, verify the detected subjects or attributes, and store the returned data for use in video generation, editing, or other downstream automation tasks.