Planogram
E-commerce
Overview
Planogram compliance for detecting missing or misplaced items. A retail store frequently has to cope up with demand & much larger stores need to employ staff just to check up on inventory, products placed on the shelves & get items in place misplaced by customers, a very frequent occurrence & annoyance for storekeepers. With that taken into account, we have a solution to get instant updates on if a shelf is empty, the item is missing & our end-to-end system gets real-time updates from inventory linked to the database & assigns someone instantly to fix the situation.
Technology
- Computer Vision
- Deep Learning
- Machine Learning
Language
- Python
Key Technical Challenges:
- Having varying products on the shelves, we had to make sure we make generalized model
- Data provided to us did not cover all the use cases & we had to get new data & annotate them in order.
- Establishing a streamline pipeline with a Deep learning model was a bit difficult.
Business + Technical Points:
- Needed real-time updates & notifications from the store
- Role-based access to the system & Modification of positioning of shelves should not affect the detection
- Surveillance quality was good but modernization may happen in future, the system should cope with it.
- Resource consumption in terms of model should be optimal & should be scalable when need arises for expansion.
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