Pill Detection Image 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 Annotated 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) - 451 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) - 1,083 images

  • Preprocessing: Auto-Orient, Resize (Stretch to 416x416), all classes remapped (Modify Classes) to "pill"
  • Augmentations:
    90° Rotate: Clockwise, Counter-Clockwise, Upside Down
    Crop: 0% Minimum Zoom, 77% Maximum Zoom
    Rotation: Between -45° and +45°
    Shear: ±15° Horizontal, ±15° Vertical
    Hue: Between -22° and +22°
    Saturation: Between -27% and +27%
    Brightness: Between -33% and +33%
    Exposure: Between -25% and +25%
    Blur: Up to 3px
    Noise: Up to 5% of pixels
    Cutout: 3 boxes with 10% size each
    Mosaic: Applied
    Bounding Box: Brightness: Between -25% and +25%
  • Training Metrics: Trained from the COCO Checkpoint in Public Models ("transfer learning") on Roboflow
    • mAP = 91.4%, precision = 61.1%, recall = 93.9%

Version 3 (v3) - 1,083 images

  • Preprocessing: Auto-Orient, Resize (Stretch to 416x416), all classes remapped (Modify Classes) to "pill"
  • Augmentations:
    90° Rotate: Clockwise, Counter-Clockwise, Upside Down
    Crop: 0% Minimum Zoom, 77% Maximum Zoom
    Rotation: Between -45° and +45°
    Shear: ±15° Horizontal, ±15° Vertical
    Hue: Between -22° and +22°
    Saturation: Between -27% and +27%
    Brightness: Between -33% and +33%
    Exposure: Between -25% and +25%
    Blur: Up to 3px
    Noise: Up to 5% of pixels
    Cutout: 3 boxes with 10% size each
    Mosaic: Applied
    Bounding Box: Brightness: Between -25% and +25%
  • Training Metrics: Trained from "scratch" (no transfer learning employed) on Roboflow
    • mAP = 84.3%, precision = 53.2%, recall = 86.7%

Version 4 (v4) - 451 images

  • Preprocessing: Auto-Orient, Resize (Stretch to 416x416), all classes remapped (Modify Classes) to "pill"
  • Augmentations: No augmentations applied
  • Training Metrics: This version of the dataset was not trained

Version 5 (v5) - 496 images

Mohamed Attia - LinkedIn

Maintainer

mohamed-attia-e2mor

Last Updated

5 months ago

Project Type

Object Detection

Subject

pills

Classes

Cipro 500, Ibuphil 600 mg, Ibuphil Cold 400-60, Xyzall 5mg, blue, pink, red, white

License

Public Domain