Smart Facility

Inventory Basic Dataset

An open-source synthetic vision dataset for smart inventory applications.

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The Smart Facility: Inventory Basic Dataset is a synthetic, open-source dataset for smart inventory applications. It features 30 videos of photorealistic shelves stocked with items. Items vary in identity, number, and orientation. Each video contains items in the same nominal locations with the same average number of items visible (fill factor), but the item orientations and their individual visibility varies by frame. Each video is accompanied by pixel-perfect labels and annotations. This dataset can be used to develop computer vision algorithms to detect the presence, location, and identity of items from the perspective of a fixed camera.


<li>30 videos, 100 frames each</li>
<li>1024px x 768px resolution</li>
<li> 38 body care assets</li>
<li>Variable shelf fill factor (10% to 100%)</li>
<li> Randomized item orientations and item visibility</li>
<li> Segmentation masks and rich annotations per item and item kind</li>
<li>Variety of camera positions</li>


Each video is accompanied by a rich set of pixel-perfect labels and annotations, including:
<li>Shelf fill factor %</li>
<li>Camera location</li>
<li>Segmentation masks</li>
<li>Bounding boxes</li>
For the full description of labels and metadata, check out the <a href="" target="_blank">README</a>.


1024 x 728 mp4 videos (100 frames each)
Total dataset size: 2GB
Zipped file size: 350MB


This dataset is licensed under a <a href="" target="_blank">Creative Commons Attribution 4.0 International License</a>.
Both academic and commercial applications are allowed.


<li>Github <a href="" target="_blank">README</a>: full dataset and annotation descriptions</li>
<li>Demo <a href="" target="_blank">Jupyter notebook</a></li>

Questions? We’re happy to chat asynchronously via email or hop on a call. Just send us a note at (this goes to all of the Infinity AI founders).

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