cstr / tesseract-lstm-GGUF

Tesseract LSTM OCR — GGUF models for CrispEmbed

Tesseract's LSTM line-recognition engine converted to GGUF format for CrispEmbed inference. Supports 12 languages with models ranging from 250 KB to 3.2 MB.

These are the neural network weights from tessdata_best (float64 source), converted with full precision then quantized. The LSTM recognizes pre-cropped text line images — pair with a text detector (DBNet, Surya) for full-page OCR.

Models

Quantization quality

Tested with crispembed-diff per-layer parity harness against F16 Python reference:

Usage

CLI

crispembed -m tesseract-eng-q8_0.gguf --ocr image.png

C API

#include "tesseract_lstm.h"

tesseract_lstm_context *ctx = tesseract_lstm_init("tesseract-eng-q8_0.gguf", 4);
const char *text = tesseract_lstm_recognize(ctx, gray_pixels, width, height, NULL);
printf("%s\n", text);
tesseract_lstm_free(ctx);

Unified OCR API (auto-detects architecture)

void *ctx = crispembed_math_ocr_init("tesseract-eng-q8_0.gguf", 4);
const char *text = crispembed_math_ocr_recognize(ctx, pixels, w, h, channels, NULL);
crispembed_math_ocr_free(ctx);

Architecture

The VGSL (Variable-size Graph Specification Language) network:

Input (grayscale, height-normalized)
  -> Convolve 3x3 stacking (no weights, just neighborhood concat)
  -> FullyConnected + tanh (9 -> 16 features)
  -> MaxPool 3x3
  -> XYTranspose + SummLSTM (summarize height dimension)
  -> LSTM forward (96 or 64 units)
  -> LSTM reverse (96 or 64 units)
  -> LSTM forward (192-512 units)
  -> Softmax output
  -> CTC greedy decode

Spaces are not produced by the LSTM — Tesseract adds them via its DAWG language model (word segmentation), which is not part of this engine. Use the output as character-level recognition and add word boundaries via the text detector's bounding boxes.

Conversion

Convert any of the 126 Tesseract languages from .traineddata :

python models/convert-tesseract-to-gguf.py \
    --model eng.traineddata --output tesseract-eng-f16.gguf --fp16

# Then quantize:
crispembed-quantize tesseract-eng-f16.gguf tesseract-eng-q8_0.gguf q8_0
crispembed-quantize tesseract-eng-f16.gguf tesseract-eng-q4_k.gguf q4_k

Supports both tessdata_best (float64, recommended) and tessdata_fast (int8).

Source

Weights from tesseract-ocr/tessdata_best (Apache-2.0 license). Converted with CrispEmbed's convert-tesseract-to-gguf.py .