inference4j/craft-mlt-25k

CRAFT Text Detection (MLT 25K) — ONNX

ONNX export of CRAFT (Character Region Awareness for Text Detection) trained on SynthText + IC13/IC17 (MLT 25K variant).

Converted for use with inference4j, an inference-only AI library for Java.

Usage with inference4j

try (CraftTextDetector detector = CraftTextDetector.builder().build()) {
    List<TextRegion> regions = detector.detect(Path.of("document.jpg"));
    for (TextRegion r : regions) {
        System.out.printf("Text at [%.0f, %.0f, %.0f, %.0f] (confidence=%.2f)%n",
            r.box().x1(), r.box().y1(), r.box().x2(), r.box().y2(),
            r.confidence());
    }
}

Model Details

Preprocessing

1. Resize maintaining aspect ratio (long side to target size, e.g. 1280)
2. Round both dimensions to nearest multiple of 32
3. ImageNet normalization: (pixel / 255 - mean) / std
   • mean = [0.485, 0.456, 0.406]
   • std = [0.229, 0.224, 0.225]
4. NCHW layout: [1, 3, H, W]

Postprocessing

1. Combine: clip(region_score + affinity_score, 0, 1)
2. Binary threshold at low_text_threshold (default 0.4)
3. Connected component labeling (4-connectivity)
4. For each component: compute mean region score, filter by text_threshold (default 0.7)
5. Extract axis-aligned bounding box, scale back to original image coordinates

Original Paper

Baek, Y., Lee, B., Han, D., Yun, S., & Lee, H. (2019). Character Region Awareness for Text Detection. CVPR 2019. arXiv:1904.01941

License

The original CRAFT model weights are released under the MIT License by Clova AI Research (NAVER Corp).