CAPSULE
SOFTGEL
SENSUM SODF DATASET
Given the unavailability of real-world pharmaceutical inspection-domain datasets, we have created the Sensum Solid Oral Dosage Forms (SensumSODF) dataset intended for research and evaluation purposes.
- The dataset consists of two main types of solid oral dosage forms:
- capsule; non-translucent hard-shelled capsules with print, which are normally used for dry, powdered ingredients
- softgel; translucent soft-shelled capsules, which are primarily used for oils and active ingredients which are dissolved or suspended in oil
The dataset consists of 836 defect-free and 153 defective examples of non-translucent hard-shelled capsules with a size of 192 × 320 pixels, and 846 defect-free and 345 defective examples of translucent soft-shelled capsules with a size of 144 × 144 pixels. Defective examples exhibit diverse defects such as cracks, dents, smudges, impurities, and air bubbles. Defective regions range from small to large structures and are hand-annotated by a pharmaceutical product inspection domain-expert. Annotations coarsely indicate the defective area on a given example, yet to some extent also include minor defect-free areas.
Please fill out the download request form in English before downloading the Sensum SODF dataset. In order to assess compliance with the license your request will be verified and you will receive the download link via email within a couple of days:
ATTRIBUTION
If you use this dataset in your scientific work, please cite our paper:
Domen Rački, Dejan Tomaževič, Danijel Skočaj:
Detection of surface defects on pharmaceutical solid oral dosage forms with convolutional neural networks;
In: Neural Computing and Applications, August 2021.
@article{Racki2021NCAA, author = {Ra{\v{c}}ki, Domen and Toma{\v{z}}evi{\v{c}}, Dejan and Sko{\v{c}}aj, Danijel}, title = {Detection of surface defects on pharmaceutical solid oral dosage forms with convolutional neural networks}, journal = {Neural Computing and Applications}, year = {2021}, month = {August}, day = {17}, issn = {1433-3058}, doi = {10.1007/s00521-021-06397-6} }
LICENSE
The data is released under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License (CC BY-NC-SA 4.0). For using the data in a way that falls under the commercial use clause of the license, please contact us.