Translating Street Signs in Real-time

Deep dive into natural scene text recognition and our 50+ language auto-detection pipeline.

Natural Scene Processing

Extracting text from "in-the-wild" imagery (street signs, billboards, graffiti) is fundamentally harder than flat document scans. It requires handling curved perspective transformations, drastic lighting changes, and noisy backgrounds.

The Solution

When calling the API, supply the scene_text: true flag. This engages the heavy-weight ResNet backbone specialized in curving and shadow removal before passing data to the recognizer.

await solveocr.extract("tokyo_neon.jpg", {
  scene_text: true
})

Language Auto-Detection

If you don't know the language of the sign (e.g. touring a foreign country), omit the `languages` array. The vision model will perform a global classification pass.

Fallback translation pipeline

You can chain the extracted UTF-8 output directly into Google Translate API or an LLM for instant comprehension.