metadata
license: mit
base_model:
- microsoft/trocr-base-printed
tags:
- computer-vision
- ocr
- trocr
- pill
- medical
- pytorch
Fine-tuned TrOCR for Pill Imprint OCR
Model Summary
This is a fine-tuned TrOCR model for reading pill imprints (letters/numbers) from pill images. It is used as part of a pill identification pipeline where OCR output is matched against a pill database.
Intended Use
- Extract imprint text from pill images to support database-backed pill identification.
- Research and demo usage.
Not Intended Use
- Not a medical device.
- Not for clinical decision making.
Training Data
Fine-tuned on pill images with imprint labels (RxNav-style pill images). Data includes varied lighting, blur, and embossing conditions.
Evaluation
Evaluated primarily by end-to-end retrieval performance (top-k matching in a pill database) and qualitative OCR correctness on benchmark images.
Limitations
- Performance degrades on low-resolution, blurred, or overexposed images.
- Embossed/low-contrast digits may be dropped or partially recognized.
- Some imprints are inherently ambiguous; downstream ranking should return top-k candidates.
How to Use
from transformers import TrOCRProcessor, VisionEncoderDecoderModel
processor = TrOCRProcessor.from_pretrained("YOUR_NAME/YOUR_REPO")
model = VisionEncoderDecoderModel.from_pretrained("YOUR_NAME/YOUR_REPO")