| # Image CAPTCHA Usage |
|
|
| ## Task type |
|
|
| - `ImageToTextTask` |
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|
| ## Request |
|
|
| ```json |
| { |
| "clientKey": "your-client-key", |
| "task": { |
| "type": "ImageToTextTask", |
| "body": "<base64-encoded-image>" |
| } |
| } |
| ``` |
|
|
| ## Implementation notes |
|
|
| The image solver is implemented in `src/services/recognition.py` and is inspired by Argus-style structured multimodal annotation. |
|
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| Current behavior: |
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| - image input is resized to **1440×900** |
| - the model is prompted to classify the captcha into structured action types |
| - the normalized coordinate space starts at `(0, 0)` in the top-left corner |
|
|
| Supported response styles in the prompt: |
|
|
| - `click` |
| - `slide` |
| - `drag_match` |
|
|
| ## Result shape |
|
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| The current API returns the structured model output serialized as a string in `solution.text`. |
|
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| Example: |
|
|
| ```json |
| { |
| "errorId": 0, |
| "status": "ready", |
| "solution": { |
| "text": "{\"captcha_type\":\"slide\",\"drag_distance\":270}" |
| } |
| } |
| ``` |
|
|
| ## Backend compatibility |
|
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| The multimodal path is designed for **OpenAI-compatible** APIs. This makes it suitable for hosted or self-hosted backends as long as they expose compatible image-capable chat completion behavior. |
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| Accuracy depends heavily on the selected model and provider implementation. |
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|
