Introduction

Hi, developers, welcome to use Dewatermark's API. The following are some basic introductions to your access service. Hope you can find the AI ​​technology capabilities that are suitable for your business here. Thank you for using!

Authentication

To authorize, use this code:

# With shell, you can just pass the correct header with each request
curl "https://platform.dewatermark.ai/api/object_removal/v1/erase_watermark" \
  -H "X-API-KEY: <API-KEY>"

Make sure to replace <API-KEY> with your API key.

Dewatermark uses API keys to allow access to the API. You can receive your unique API key by signing up and opening API managent page).

The API key must be included in all API requests to the server in a header that looks like the following:

X-API-KEY: API_KEY

Image Processing API

Remove Watermark

Remove Watermark

curl -X POST "https://platform.dewatermark.ai/api/object_removal/v1/erase_watermark" \
  -H "X-API-KEY: API_KEY" \
  --form 'session_id="SESSION_ID"' \
  --form 'original_preview_image=@"IMAGE_FILE"' \
  --form 'mask_base=@"MASK_BASE_FILE"'\
  --form 'mask_brush=@"MASK_BRUSH_FILE"' \
  --form 'remove_text="true"'

This API allows you to remove watermark from an image and seamlessly inpaint the erased area to blend it naturally with the surrounding background. Each remove watermark image API call is counted as 1 credits.

The above command returns JSON structured like this:

{
  "edited_image": {
    "image": "BASE_64_IMAGE",
    "image_id": "image_id",
    "mask": "BASE64_MASK",
    "watermark_mask":"BASE64_MASK"
  },
  "event_id": "event_id",
  "session_id": "session_id"
}

HTTP Request

POST https://platform.dewatermark.ai/api/object_removal/v1/erase_watermark

Request body

In the request form data, while either original_preview_image or session_id parameter is required, it is recommended to include session_id if it's already available.

The inital request doesn't require mask_base and mask_brush.

Response

Continuing Watermark Removal with Manual Refinement

Even after the initial API call, you can achieve even more precise results by manually specifying the remaining watermark area you want to erase. Here's the process:

Manual Selection: Define a mask that isolates the specific part of the image containing the remaining watermark or unwanted element. This mask acts as a guide for the API.

API Call with Session ID and Mask: Make a subsequent API call to remove the designated area. Remember to include these important parameters:

original_preview_image: The output image (edited_image.image) from the previous automatic Watermark removal. For the first manual refinement, you must send this output image from the initial API call. It should be a JPEG image, and the largest dimension is not greater than 1920.

session_id: This unique identifier is generated during the initial watermark removal process. It allows the API to link your refinement request to the specific image you're working on. In the second manual refinement, you must use this session_id instead of original_preview_image.

mask_brush: This parameter allows you to provide a new, more refined mask that focuses on the remaining watermark area you want to erase.

remove_text: If you want to enable the text removal feature, set remove_text to 'true' in the request body to remove text from the image. If the watermark is purely text, enable the text remover for improved results. Note that this may remove all text from your image.

By following these steps, you can iteratively remove watermarks and achieve a highly refined final image.

Save Image

curl -X POST "https://platform.dewatermark.ai/api/object_removal/v1/save_large_image" \
  -H "X-API-KEY: API_KEY" \
  --form 'session_id="SESSION_ID"' \
  --form 'preview_image_to_save=@"IMAGE_FILE"' \
  --form 'preview_mask_to_save=@"MASK_BRUSH_FILE"' \
  --form 'original_large_image=@"ORIGINAL_IMAGE_FILE"' \
  --form 'remove_text="true"'

This API enables you to save the image from the remove watermark API with a higher resolution, up to 4000px. If your image is smaller than 1408, you don't need to utilize this API.

Each save image API call is counted as 2 credits.

Request body

The above command returns JSON structured like this:

{
    "event_id": "event_id",
    "large_image_to_save": "BASE64_IMAGE",
    "session_id": "session_id"
}

large_image_to_save is the final output, it's a base64 image, you can encode it back to JPEG image.

Demo

This image demonstrates the watermark removal process using our API. The left side shows the original image with a watermark, and the right side shows the result after processing with our API.

Errors

The Kittn API uses the following error codes: