pallet detection Computer Vision Project
Here are a few use cases for this project:
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Warehouse Management: The model can help automate the detection and counting of pallets in a warehouse. This could facilitate inventory management and space utilization.
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Logistics and Supply Chain: With the ability to identify pallets, the model could improve efficiency in loading and unloading procedures in transports, presenting real-time data on the number of pallets in transit.
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Safety Regulations: The model can help ensure safety regulations are being adhered to by detecting and alerting when pallets are stacked improperly or exceeding safe heights.
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Waste Management: The model could be used to identify wooden pallets at recycling facilities or landfills to enhance sorting and recycling efforts.
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Retail Stores: The model can play a pivotal role in managing back-of-store operations - tracking the arrival, usage, and emptying of pallets.
Trained Model API
This project has a trained model available that you can try in your browser and use to get predictions via our Hosted Inference API and other deployment methods.
YOLOv8
This project has a YOLOv8 model checkpoint available for inference with Roboflow Deploy. YOLOv8 is a new state-of-the-art real-time object detection model.
Cite This Project
If you use this dataset in a research paper, please cite it using the following BibTeX:
@misc{
pallet-detection-ith6b_dataset,
title = { pallet detection Dataset },
type = { Open Source Dataset },
author = { sundharesan-kumaresan },
howpublished = { \url{ https://universe.roboflow.com/sundharesan-kumaresan/pallet-detection-ith6b } },
url = { https://universe.roboflow.com/sundharesan-kumaresan/pallet-detection-ith6b },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2023 },
month = { may },
note = { visited on 2024-04-28 },
}
Connect Your Model With Program Logic
Find utilities and guides to help you start using the pallet detection project in your project.