| # Pill Detection > isolate-objects |
| https://universe.roboflow.com/mohamed-attia-e2mor/pill-detection-llp4r |
|
|
| Provided by a Roboflow user |
| License: Public Domain |
|
|
| ## Background Information |
| This dataset was curated and annotated by [Mohamed Attia](https://www.linkedin.com/in/mohamed-attia-aa274a193/). |
|
|
| The original dataset *(v1)* is composed of 451 images of various pills that are present on a large variety of surfaces and objects. |
|  |
|
|
| 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](https://blog.roboflow.com/a-primer-on-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 |
| * Preprocessing: Auto-Orient, all classes remapped (Modify Classes) to "pill", [Isolate Objects](https://blog.roboflow.com/isolate-objects/) |
| * The Isolate Objects preprocessing step was added to convert this 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 (classification dataset available here: https://universe.roboflow.com/mohamed-attia-e2mor/pill-classification) |
|
|
| Mohamed Attia - [LinkedIn](https://www.linkedin.com/in/mohamed-attia-aa274a193/) |
