Pill Classification Classification Dataset and Pre-Trained Model by Mohamed Attia

Images

496 images

Explore Dataset

Background Information

This dataset was curated and annotated by Mohamed Attia.

The original dataset (v1) is composed of 451 images of various pills that are present on a large variety of surfaces and objects. Example of an Image from the Dataset

The dataset is available under the Public License.

Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

Dataset Versions

Version 1 (v1) - 496 images

Preprocessing: Auto-Orient and Resize (Stretch to 416x416)
Augmentations: No augmentations applied
Training Metrics: This version of the dataset was not trained

Version 2 (v2) - 1,190 images

Preprocessing: Auto-Orient, Resize (Stretch to 416x416), all classes remapped (Modify Classes) to "pill"
Augmentations: Outputs per training example: 3 90° Rotate: Clockwise, Counter-Clockwise, Upside Down Shear: ±5° Horizontal, ±5° Vertical Hue: Between -25° and +25° Saturation: Between -10% and +10% Brightness: Between -10% and +10% Exposure: Between -10% and +10% Noise: Up to 2% of pixels Cutout: 5 boxes with 5% size each
Trained from the COCO Checkpoint in Public Models ("transfer learning") on Roboflow

NOTE:

The Isolate Objects preprocessing step was added to convert the original object detection project into a suitable format for export in OpenAI's CLIP annotation format so that it could be used as a classifcation model in this project.

Mohamed Attia - LinkedIn

Trained Model API

This project has a trained model available that you can try in your browser and use to get predictions via our Hosted Inference API and other deployment methods.

Cite This Project

If you use this dataset in a research paper, please cite it using the following BibTeX:

@misc{
                            pill-classification_dataset,
                            title = { Pill Classification Dataset },
                            type = { Open Source Dataset },
                            author = { Mohamed Attia },
                            howpublished = { \url{ https://universe.roboflow.com/mohamed-attia-e2mor/pill-classification } },
                            url = { https://universe.roboflow.com/mohamed-attia-e2mor/pill-classification },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2022 },
                            month = { jun },
                            note = { visited on 2024-04-25 },
                            }