| --- |
| license: apache-2.0 |
| tags: |
| - gguf |
| - ocr |
| - scene-text |
| - parseq |
| - crispembed |
| base_model: baudm/parseq |
| --- |
| |
| # PARSeq — Scene Text Recognition (GGUF) |
|
|
| GGUF conversions of [PARSeq](https://github.com/baudm/parseq) (ECCV 2022) for use with [CrispEmbed](https://github.com/CrispStrobe/CrispEmbed). |
|
|
| PARSeq is a scene text recognition model that reads text from natural images (signs, labels, documents). It recognizes 94 printable ASCII characters (digits, letters, punctuation). |
|
|
| ## Architecture |
|
|
| - **Encoder**: 12-layer pre-LN ViT (patch 4×8, input 32×128 RGB, 128 tokens, GELU FFN) |
| - **Decoder**: 1-layer two-stream Transformer (XLNet-style position queries + context self-attention, then cross-attention to encoder memory) |
| - **Head**: Linear → 95 classes (94 printable ASCII chars + EOS) |
| - **Inference**: Autoregressive greedy decode (max 25 characters) |
|
|
| ## Variants |
|
|
| | File | Variant | Params | Size | Notes | |
| |------|---------|--------|------|-------| |
| | `parseq-f32.gguf` | Base | 24M | 91 MB | Full precision | |
| | `parseq-q8_0.gguf` | Base | 24M | 24 MB | Best quantized | |
| | `parseq-q4_k.gguf` | Base | 24M | 13 MB | Smallest base | |
| | `parseq-tiny-f16.gguf` | Tiny | 6M | 12 MB | Half precision | |
| | `parseq-tiny-q8_0.gguf` | Tiny | 6M | 6 MB | Smallest overall | |
|
|
| All quantization levels produce identical output on test images. |
|
|
| ## Usage |
|
|
| ```bash |
| # CLI |
| crispembed -m parseq-q8_0.gguf --ocr image.png |
| |
| # Auto-download |
| crispembed -m parseq --auto-download --ocr image.png |
| ``` |
|
|
| ```python |
| from crispembed import CrispMathOcr |
| ocr = CrispMathOcr("parseq-q8_0.gguf") |
| text = ocr.recognize("sign.png") |
| ``` |
|
|
| ## Benchmark (94-char, PARSeq-base) |
|
|
| | Dataset | Accuracy | |
| |---------|----------| |
| | IIIT5k | 99.1% | |
| | SVT | 97.9% | |
| | IC13-1015 | 98.1% | |
| | IC15-2077 | 89.2% | |
| | SVTP | 96.9% | |
| | CUTE80 | 98.6% | |
|
|
| ## Source |
|
|
| - Paper: [Scene Text Recognition with Permuted Autoregressive Sequence Models](https://arxiv.org/abs/2207.06966) (ECCV 2022) |
| - Code: [baudm/parseq](https://github.com/baudm/parseq) (Apache-2.0) |
| - Converted with `models/convert-parseq-to-gguf.py` from CrispEmbed |
|
|
