Cereal box identification in store shelves using computer vision and a single train image per model.

Last update: Jan 21, 2022

Overview

Product Recognition on Store Shelves

Description

You can read the task description here.

Report

You can read and download our report here.

Step A - Multiple Product Detection

See the results in this jupyter notebook. Or download and run it!

Step B - Multiple Instance Detection

See the results in this jupyter notebook. Or download and run it!

Step C - Whole shelve challenge

See the results in this jupyter notebook. Or download and run it!

Packages versions

cv2: 4.4.0

numpy: 1.19.2

matplotlib: 3.3.2

Extra

(Optional) If you want to visualize additional information such as plots of intermediate steps of the whole process, then download and run this jupyter notebook.

Team

Owner

Nicholas Baraghini

MSC Automation Engineer Student presso l'Università di Bologna | 🐉Dragon Rider | Curious Learner

GitHub Repository

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Cereal box identification in store shelves using computer vision and a single train image per model.

Related tags

Overview

Product Recognition on Store Shelves

Description

Report

Step A - Multiple Product Detection

Step B - Multiple Instance Detection

Step C - Whole shelve challenge

Packages versions

Extra

Team

Owner

Nicholas Baraghini

A Transformer-Based Siamese Network for Change Detection

Pytorch implementation of the popular Improv RNN model originally proposed by the Magenta team.

Probabilistic-Monocular-3D-Human-Pose-Estimation-with-Normalizing-Flows

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