Smart system for precise pill bottle measurement

Overview
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Industry
Healthcare
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Provided services
Data science, Backend development
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Type of the project
ML-powered algorithm
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Duration
January 2022 — September 2022
About the project
Our partner needed an MVP that could count the number of pills inside a bottle with an embedded camera within the bottle cap, letting users track and detect any misuse of medicine. The machine learning (ML) algorithm would also need to connect to both the camera inside the pill bottle’s cap and our partner’s mobile app.
To begin, our data science engineers researched stereo vision, monocular depth estimation, and volumetric calculations. They used their findings to build custom datasets, a semantic segmentation model, and depth estimation models to train the algorithm to measure a variety of pill shapes and sizes. After calibrating our partner’s cameras, our team fine-tuned the algorithm by modeling various scenes to generate depth maps and accurately estimate bottle depth, even when relying on sparse reference data. And in the end, we delivered a smart, accurate, ML-powered algorithm that our partners could use to make administering medicine safer.
Project outcomes
- An MVP and machine learning algorithm that accurately measures pill amounts, regardless of pill type and bottle conditions.
- A scalable final product that integrates directly into our partner’s product ecosystem and mobile app.
Stack
- — Backend
- Python
- Flask
- PyTorch
- OpenCV
- NumPy
- Torchvision
- PIL
- Matplotlib
- Docker
Key features
Let’s talk
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Visit our HQ in
Cyprus, Nicosia, Griva Digeni, 81-83 Jacovides Tower, 1st floor
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We’ve received your message and will get back to you shortly.
Contact us directly via
Visit our HQ in
Cyprus, Nicosia, Griva Digeni, 81-83 Jacovides Tower, 1st floor
Meet our representatives in
The UK, Spain, Bulgaria, Poland, and over 15 other European countries