Paddle Ocr

Playground

PaddleOCR-VL is an ultra-compact 0.9B parameter vision-language model for document parsing, supporting 109 languages with text, table, formula, and chart recognition in JSON or Markdown output. Ready-to-use REST inference API, best performance, no cold starts, affordable pricing.

Features

WaveSpeedAI PaddleOCR

Extract text from images with WaveSpeedAI PaddleOCR — a fast, accurate optical character recognition model. Simply upload an image and get clean, structured text output in JSON or Markdown format. Perfect for document digitization, data extraction, and text recognition tasks.

Why It Works Great

High accuracy: Powered by PaddleOCR for reliable text recognition.
Multi-language support: Recognizes text in multiple languages.
Flexible output: Choose between JSON or Markdown format.
Document-friendly: Handles scanned documents, screenshots, and photos.
Ultra-affordable: Just $0.005 per image.
Fast processing: Quick turnaround for high-volume workflows.

Parameters

Parameter	Required	Description
image	Yes	Image containing text (upload or public URL).
output_format	No	Output format: json or markdown. Default: markdown.

How to Use

Upload your image — drag and drop or paste a public URL.
Choose output format — select JSON for structured data or Markdown for readable text.
Run — click the button to process.
Copy or download — use the extracted text as needed.

Pricing

$0.005 per image.

Output Formats

Format	Description	Best For
markdown	Clean, readable text with formatting	Documents, articles, readable output
json	Structured data with position info	Data processing, integration, automation

Best Use Cases

Document Digitization — Convert scanned documents to editable text.
Data Extraction — Pull text from invoices, receipts, and forms.
Screenshot Text — Extract text from screenshots and images.
Business Cards — Digitize contact information quickly.
Batch Processing — Process large volumes of documents affordably.
Content Migration — Convert image-based content to text format.

Supported Content Types

Scanned documents (PDF pages, printed text)
Screenshots and screen captures
Photos of documents and signs
Handwritten text (with varying accuracy)
Multi-column layouts
Tables and structured content

Pro Tips for Best Results

Use high-resolution images for better accuracy.
Ensure good contrast between text and background.
Straighten skewed documents before processing.
Use JSON format when you need text positions or bounding boxes.
Use Markdown format for clean, human-readable output.
At $0.005 per image, batch processing is extremely cost-effective.

Notes

If using a URL, ensure it is publicly accessible.
Processing time is typically under a second per image.
Accuracy depends on image quality and text clarity.
Supports multiple languages and character sets.

Authentication

For authentication details, please refer to the Authentication Guide.

API Endpoints

Submit Task & Query Result


# Submit the task
curl --location --request POST "https://api.wavespeed.ai/api/v3/wavespeed-ai/paddle-ocr" \
--header "Content-Type: application/json" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}" \
--data-raw '{
    "output_format": "markdown",
    "enable_sync_mode": true
}'

# Get the result
curl --location --request GET "https://api.wavespeed.ai/api/v3/predictions/${requestId}/result" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}"

Parameters

Task Submission Parameters

Request Parameters

Parameter	Type	Required	Default	Range	Description
image	string	Yes		-	Document image to parse. Supports text, tables, formulas, and charts recognition in 109 languages.
output_format	string	No	markdown	json, markdown	Output format: 'json' for structured data or 'markdown' for human-readable text.
enable_sync_mode	boolean	No	true	-	If set to true, the function will wait for the result to be generated and uploaded before returning the response. It allows you to get the result directly in the response. This property is only available through the API.

Response Parameters

Parameter	Type	Description
code	integer	HTTP status code (e.g., 200 for success)
message	string	Status message (e.g., “success”)
data.id	string	Unique identifier for the prediction, Task Id
data.model	string	Model ID used for the prediction
data.outputs	array	Array of URLs to the generated content (empty when status is not `completed`)
data.urls	object	Object containing related API endpoints
data.urls.get	string	URL to retrieve the prediction result
data.has_nsfw_contents	array	Array of boolean values indicating NSFW detection for each output
data.status	string	Status of the task: `created`, `processing`, `completed`, or `failed`
data.created_at	string	ISO timestamp of when the request was created (e.g., “2023-04-01T12:34:56.789Z”)
data.error	string	Error message (empty if no error occurred)
data.timings	object	Object containing timing details
data.timings.inference	integer	Inference time in milliseconds

Result Request Parameters

Parameter	Type	Required	Default	Description
id	string	Yes	-	Task ID

Result Response Parameters

Parameter	Type	Description
code	integer	HTTP status code (e.g., 200 for success)
message	string	Status message (e.g., “success”)
data	object	The prediction data object containing all details
data.id	string	Unique identifier for the prediction, the ID of the prediction to get
data.model	string	Model ID used for the prediction
data.outputs	string	Object containing the parsed document content in the requested format (JSON or Markdown).
data.urls	object	Object containing related API endpoints
data.urls.get	string	URL to retrieve the prediction result
data.status	string	Status of the task: `created`, `processing`, `completed`, or `failed`
data.created_at	string	ISO timestamp of when the request was created (e.g., “2023-04-01T12:34:56.789Z”)
data.error	string	Error message (empty if no error occurred)
data.timings	object	Object containing timing details
data.timings.inference	integer	Inference time in milliseconds

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