Paddle Ocr | AI Image Understanding API

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.

Paddle Ocr API — Quick start

Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/wavespeed-ai/paddle-ocr with your input as JSON. The endpoint returns a prediction id; poll the prediction endpoint until status flips to completed, then read the output URL from data.outputs[0]. Examples for Paddle Ocr below.

HTTP example

# Submit the prediction
curl -X POST "https://api.wavespeed.ai/api/v3/wavespeed-ai/paddle-ocr" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $WAVESPEED_API_KEY" \
  -d '{
    "image": "https://example.com/your-input.jpg",
    "output_format": "markdown",
    "enable_sync_mode": false
}'

# Response includes a prediction id. Poll for the result:
curl -X GET "https://api.wavespeed.ai/api/v3/predictions/{request_id}/result" \
  -H "Authorization: Bearer $WAVESPEED_API_KEY"

# When status is "completed", read the output from data.outputs[0].

Node.js example

// npm install wavespeed
const WaveSpeed = require('wavespeed');

const client = new WaveSpeed(); // reads WAVESPEED_API_KEY from env

const result = await client.run("wavespeed-ai/paddle-ocr", {
        "image": "https://example.com/your-input.jpg",
        "output_format": "markdown",
        "enable_sync_mode": false
});

console.log(result.outputs[0]); // → URL of the generated output

Python example

# pip install wavespeed
import wavespeed

output = wavespeed.run(
    "wavespeed-ai/paddle-ocr",
    {
    "image": "https://example.com/your-input.jpg",
    "output_format": "markdown",
    "enable_sync_mode": false
}
)

print(output["outputs"][0])  # → URL of the generated output

Paddle Ocr API — Frequently asked questions

What is the Paddle Ocr API?

Paddle Ocr is a WaveSpeedAI model for AI inference, exposed as a REST API on WaveSpeedAI. 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. You can call it programmatically or try it from the playground above.

How do I call the Paddle Ocr API?

POST your input parameters to the model's REST endpoint (shown in the API tab of this playground) with your WaveSpeedAI API key in the Authorization header. Submission returns a prediction ID; poll the prediction endpoint until status flips to "completed", then read the output URL from the result. The playground generates a ready-to-paste code sample in Python, JavaScript, or cURL for whatever inputs you've set. Full request/response shape is documented at https://wavespeed.ai/docs/docs-api/wavespeed-ai/paddle-ocr.

How much does Paddle Ocr cost per run?

Paddle Ocr starts at $0.010 per run. That figure is the base price — the final charge scales with the parameters you set in the form (output size, length, count, references, or whatever knobs this model exposes), so a higher-quality or larger output costs more than a minimal one. The exact cost for your current input is shown live next to the Generate button before you submit, and the actual per-call charge is recorded on the prediction afterwards.

What inputs does Paddle Ocr accept?

Key inputs: `image`, `enable_sync_mode`, `output_format`. The full JSON schema (types, defaults, allowed values) is rendered above the Generate button and mirrored in the API reference at https://wavespeed.ai/docs/docs-api/wavespeed-ai/paddle-ocr.

How long does Paddle Ocr take to generate?

Average end-to-end generation time on WaveSpeedAI is around 21 seconds per request — measured across recent runs. Queue time scales with global demand; live status is visible in the prediction record.

Can I use Paddle Ocr outputs commercially?

Commercial usage rights depend on the model's license, set by its provider (WaveSpeedAI). The license summary appears on the model card above; see WaveSpeedAI's Terms of Service for platform-level conditions.

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