Thareah/thaocr
By Thareah · ↓ 0 · ♥ 0 · Updated 2026-02-19
What's in this repo
This page lists the files in Thareah/thaocr, including model.onnx.
- 1 ONNX models (.onnx files)
- 7 files, including 1 .md, 1 .yml, 1 .txt, 1 .onnx, 1 .safetensors, 1 .json
- Last updated 2026-02-19
ONNX files
| File | Size | Download |
|---|---|---|
| model.onnx | — | Download |
How to use
These ONNX files can be loaded with ONNX Runtime. To inspect a model graph, upload the file to the Netron viewer. Download links point to the original files on Hugging Face.
README
Model 90k (Small-90k)
This directory contains a lightweight version of the ThaoNet recognition model, trained on approximately 90,000 samples (Khmer script).
Model Architecture (model-small)
This model uses the ThaoNet-Small architecture, optimized for speed and low memory usage.
| Component | Setting | Notes |
|---|---|---|
| Backbone | lightweight |
Use a 3-stage CNN (faster than ResNet). |
| Head | transformer_ctc |
Shallow Transformer (2 layers, d=128). |
| Input Size | 32px |
Lower resolution for speed. |
| Params | ~1.6 Million | Very small, suitable for mobile/CPU. |
File Structure
model90k/
├── model.safetensors # PyTorch weights (SafeTensors format)
├── model.onnx # Exported ONNX model
├── config.yml # Model configuration
├── khmer_dict.txt # Character vocabulary list
├── model_vocab.json # Full vocabulary mapping
└── README.md # This file
Usage
1. Run Inference (ONNX)
python tools/export/predict.py \
--onnx model90k/model.onnx \
--vocab model90k/model_vocab.json \
--image path/to/image.png \
--height 32
Note: Ensure you use --height 32 as this model was trained on lower resolution images.
2. Load Weights (SafeTensors)
from safetensors.torch import load_file
state_dict = load_file("model90k/model.safetensors")
# load into model...
3. Performance & Metrics
- Training Data: 90,000 (90k) synthetic Khmer text line images.
- CER (Character Error Rate): ~5-8% (Estimated on diverse data).
- WER (Word Error Rate): ~15-20%.
- Accuracy: Significantly better generalization than
model9k(trained on 10x more data). - Speed: Same as model9k (~2-3x faster than base).
Model info
Created: 2026-02-19
Updated: 2026-02-19
View on Hugging FaceFiles (7)
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