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Thareah
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thaocr

ONNX
Safetensors
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  1. README.md +34 -0
  2. model.onnx +3 -0
  3. model_vocab.json +186 -0
README.md ADDED
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+ # Model 9k (Small)
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+
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+ This directory contains a **lightweight** version of the **ThaoNet** recognition model, trained on approximately **9,000** samples (Khmer script).
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+
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+ ## Model Architecture (`model-small`)
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+
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+ This model uses the **ThaoNet-Small** architecture, optimized for speed and low memory usage.
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+
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+ | Component | Setting | Notes |
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+ |-----------|---------|-------|
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+ | **Backbone** | `lightweight` | Use a 3-stage CNN (faster than ResNet). |
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+ | **Head** | `transformer_ctc` | Shallow Transformer (2 layers, d=128). |
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+ | **Input Size** | `32px` | Lower resolution for speed. |
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+ | **Params** | **~1.6 Million** | Very small, suitable for mobile/CPU. |
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+
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+ ## Usage
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+
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+ ### 1. Run Inference (ONNX)
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+
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+ ```bash
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+ python tools/export/predict.py \
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+ --onnx model9k/model.onnx \
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+ --vocab model9k/model_vocab.json \
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+ --image path/to/image.png \
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+ --height 32
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+ ```
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+ *Note: Ensure you use `--height 32` as this model was trained on lower resolution images.*
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+
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+ ### 2. Performance & Data
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+ * **Training Data**: 9,000 (9k) synthetic Khmer text line images.
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+ * **CER (Character Error Rate)**: ~15-20% (Estimated on diverse data).
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+ * **WER (Word Error Rate)**: ~30-40%.
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+ * **Speed**: ~2-3x faster than the base model.
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+ * **Accuracy**: Lower than `base` or `handwriting` models, especially on complex backgrounds. Best for simple, clean, printed text.
model.onnx ADDED
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model_vocab.json ADDED
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