| Model Type | Text Detection & Recognition |
|---|---|
| Framework | LiteRT (TensorFlow Lite), PyTorch, OpenCV |
| Algorithm | CRAFT + CRNN |
| Technical Details | This app processes input images to detect, localize, and transcribe textual elements using a CRAFT-based detector and CRNN recognizer. Outputs a JSON structure with the text content, bounding box or polygon coordinates, and confidence score for each instance. Suitable for high-accuracy OCR tasks in logistics, signage, and industrial documentation. Designed for robustness over varied lighting and text styles. |
Scene Text Detection – High Accuracy
High-precision OCR application that detects and transcribes text from real-world images with superior accuracy, ideal for industrial and logistics use cases.
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Scene Text Detection – High Accuracy
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Scene Text Detection – Light Model
Lightweight OCR application that detects and reads text in images using a faster, lower-resource model designed for embedded and edge devices.
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