Instructions to use pillIdentifierAI/pillIdentifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pillIdentifierAI/pillIdentifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="pillIdentifierAI/pillIdentifier") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("pillIdentifierAI/pillIdentifier") model = AutoModelForImageClassification.from_pretrained("pillIdentifierAI/pillIdentifier") - Notebooks
- Google Colab
- Kaggle
This model is part of a school project. Utilizing the google/vit-base-patch16-224 vision transformer for image classification, this pre-trained model is further tuned utilizing images of pills and tablets. As pills and tablets have three main features, color, shape, and imprint, the model aims to identify images of pill and tablets by automatically extracting features. The dataset utilized is from the U.S. Department of Health's Computational Photography Project for Pill Identification (C3PI).
DISCLAIMER: The accuracy of this model is currently low (<20%). Further training is currently ongoing to improve the accuracy.
Version 2: This version tries to train the pretrained model with only 20 of the most common pills. Unfortunately, the accuract of the model is still currently low (<30%).
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