Our Image Dehaze API is designed to effectively remove haze from images taken in foggy conditions, restoring clarity and revealing hidden details. Utilizing advanced dehazing algorithms, this API enhances image quality by eliminating the obscuring effects of fog and haze, resulting in sharper, more realistic visuals. Ideal for photographers, environmental researchers, and digital content creators, this tool ensures that your images maintain high levels of detail and accuracy, even in challenging weather conditions. Integrate our Image Dehaze API into your workflow to effortlessly improve the visibility and clarity of your photos, making them more vibrant and true to life. Perfect for applications in photography, surveillance, and any scenario where clear image quality is crucial.
{"error_code":0,"error_detail":{"status_code":200,"code":"","code_message":"","message":""},"_note":"Response truncated for documentation purposes"}
curl --location 'https://pr197-testing.zylalabs.com/api/4419/image+dehaze+api/5428/image+dehaze' \
--header 'Content-Type: application/json' \
--form 'image=@"FILE_PATH"'
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Authorization
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[Required] Should be Bearer access_key. See "Your API Access Key" above when you are subscribed. |
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Our Image Dehaze API is designed to effectively remove haze from images taken in foggy conditions, restoring clarity and revealing hidden details. Utilizing advanced dehazing algorithms, this API enhances image quality by eliminating the obscuring effects of fog and haze, resulting in sharper, more realistic visuals. Integrate our Image Dehaze API into your workflow to effortlessly improve the visibility and clarity of your photos, making them more vibrant and true to life. Perfect for applications in photography, surveillance, and any scenario where clear image quality is crucial.
Photography and Videography: Enhancing landscape and outdoor images and videos by removing haze to reveal clearer and more detailed scenes. Surveillance and Security: Improving the clarity of images and footage captured by security cameras in foggy or hazy conditions, aiding in better identification and monitoring. Aerial and Satellite Imaging: Enhancing images captured by drones and satellites, providing clearer visuals for mapping, environmental monitoring, and urban planning. Automotive Applications: Enhancing the performance of vehicle cameras and sensors in foggy or hazy conditions, contributing to safer driving experiences.
Enhanced Clarity: Removes haze from images, revealing clearer and more detailed visuals, which improves overall image quality. Improved Visibility: Increases visibility in hazy or foggy conditions, making important details more discernible. Real-Time Processing: Capable of real-time haze removal, especially useful for applications like video surveillance and automotive systems. Enhanced Aesthetic Appeal: Improves the aesthetic quality of outdoor and landscape photographs, making them more visually appealing. Safety Benefits: Contributes to safety in applications like automotive and surveillance by providing clearer images in adverse weather conditions.
The Image Dehaze API returns a JSON response containing the processed image in base64 format, along with metadata such as request ID, log ID, error codes, and messages to indicate the status of the request.
Key fields in the response include `request_id`, `log_id`, `error_code`, `error_msg`, and `image`. The `image` field contains the base64 encoded version of the dehazed image.
The returned data is structured in JSON format. It includes public parameters for request tracking and error handling, as well as the processed image data encoded in base64.
The primary parameter for the Image Dehaze endpoint is `image`, which is required and must be a file in supported formats (PNG, JPG, JPEG, BMP) with specific size and resolution constraints.
Users can customize their requests by ensuring the input image meets the specified requirements, such as format, size (up to 8 MB), resolution (between 10x10px and 5000x5000px), and aspect ratio (within 4:1).
The response data is organized into a JSON object with distinct sections for public parameters, error details, and the processed image. This structure allows users to easily identify the status and access the dehazed image.
Typical use cases include enhancing images for photography, improving video surveillance clarity in foggy conditions, and refining aerial imagery for mapping and environmental studies.
If the API returns an error or empty results, check the `error_code` and `error_msg` fields for troubleshooting. Ensure the input image meets all requirements to avoid processing issues.
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