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README.md

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+---
+license: mit
+language:
+- en
+tags:
+- scene-text-recognition
+- ocr
+- vision-transformer
+- mae
+- image-to-text
+- pytorch
+library_name: pytorch
+---
+
+# STR-Lite
+
+STR-Lite is an ultra-lightweight scene text recognition model that combines **Masked Autoencoder (MAE) pretraining** with an **autoregressive decoder** for text generation. With only **6M parameters**, it achieves competitive accuracy while remaining highly efficient for real-world deployment.
+
+- **GitHub:** [balaboom123/STR-Lite](https://github.com/balaboom123/STR-Lite)
+- **Author:** Kuanwei Chen
+- **License:** MIT
+
+## Model Architecture
+
+| Component | Details |
+| --------- | ------- |
+| Backbone | ViT-Tiny (embed=192, depth=12, heads=12) |
+| Decoder | 1-layer autoregressive transformer (embed=192, heads=12) |
+| Input size | 32 × 128 (H × W) |
+| Patch size | 4 × 8 |
+| Parameters | ~6M |
+| Precision | bfloat16 |
+
+## Training
+
+**Stage 1 — MAE Pretraining**
+- Dataset: U14M-Unlabeled
+- Epochs: 40
+
+**Stage 2 — Fine-tuning**
+- Dataset: U14M-L-Filtered
+- Epochs: 20, Batch: 256, LR: 1e-3, Weight decay: 0.01
+
+## Checkpoints
+
+| Model | Description | Epochs | Acc | Download |
+| ----- | ----------- | :----: | :-: | :------: |
+| MAE ViT-Tiny | Pretrained encoder only | 40 | — | [pretrain/checkpoint-last.pth](https://huggingface.co/balaboom123/STRLite/resolve/main/pretrain/checkpoint-last.pth) |
+| STRLite | Full fine-tuned model | 20 | 93.82% | [finetune/checkpoint-best.pth](https://huggingface.co/balaboom123/STRLite/resolve/main/finetune/checkpoint-best.pth) |
+
+## Results
+
+**Common STR Benchmarks**
+
+| Subset | w/ pretrain | w/o pretrain |
+| ------ | :---------: | :----------: |
+| CUTE80 | 95.83 | 94.79 |
+| IC13 | 96.85 | 96.50 |
+| IC15 | 86.80 | 86.25 |
+| IIIT5k | 96.97 | 96.47 |
+| SVT | 95.36 | 94.90 |
+| SVTP | 92.40 | 89.77 |
+| **Weighted avg.** | **93.82** | **93.12** |
+
+**U14M Benchmarks**
+
+| Subset | w/ pretrain | w/o pretrain |
+| --------------- | :---------: | :----------: |
+| artistic | 67.78 | 62.11 |
+| contextless | 78.95 | 77.43 |
+| curve | 82.19 | 78.97 |
+| general | 81.07 | 79.96 |
+| multi oriented | 82.91 | 78.57 |
+| multi words | 76.72 | 74.31 |
+| salient | 78.17 | 75.33 |
+| **Weighted avg.** | **81.03** | **79.88** |
+
+## Usage
+
+**Download and evaluate:**
+
+```bash
+git clone https://github.com/balaboom123/STR-Lite
+cd STR-Lite
+
+# Download checkpoint
+from huggingface_hub import hf_hub_download
+path = hf_hub_download("balaboom123/STRLite", "finetune/checkpoint-best.pth")
+
+# Evaluate
+python eval.py \
+  resume=$path \
+  test_data_path='[/path/to/lmdb_test]'
+```
+
+**Fine-tune from MAE pretrained weights:**
+
+```bash
+path = hf_hub_download("balaboom123/STRLite", "pretrain/checkpoint-last.pth")
+
+python main_finetune.py \
+  train_data_path='[/path/to/lmdb_train]' \
+  val_data_path='[/path/to/lmdb_val]' \
+  pretrained_mae=$path
+```
+
+See the [GitHub repo](https://github.com/balaboom123/STR-Lite) for full installation and dataset preparation instructions.