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moonstripe/
chickenscratch-ocr

Name: chickenscratch-ocr
Availability: InStock

safetensors

vision-encoder-decoder

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Chickenscratch OCR

Fine-tuned TrOCR model for personal handwriting recognition.

Model Details

Base Model: microsoft/trocr-base-handwritten
Training Data: ~1,300 labeled handwritten lines from reMarkable tablet notes
Performance: CER 24%, WER 51%
Training: 15 epochs on Apple M4 Max

Usage

python

from transformers import TrOCRProcessor, VisionEncoderDecoderModel
from PIL import Image

processor = TrOCRProcessor.from_pretrained("moonstripe/chickenscratch-ocr")
model = VisionEncoderDecoderModel.from_pretrained("moonstripe/chickenscratch-ocr")

# Load a handwritten line image
image = Image.open("line.png").convert("RGB")

# Process and predict
pixel_values = processor(images=image, return_tensors="pt").pixel_values
generated_ids = model.generate(pixel_values)
text = processor.batch_decode(generated_ids, skip_special_tokens=True)[0]
print(text)

Training

This model was trained using the chickenscratch-ocr pipeline, which provides:

Data collection from reMarkable tablet
Web UI for labeling handwritten lines
Fine-tuning script with Apple Silicon MPS support

Limitations

Optimized for a specific person's handwriting
Best results on single text lines (not full pages)
May struggle with unusual symbols or very messy writing