Yolov5_seg Computer Vision Project

Segmentation yolov5

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Horizontal
Vertical
Description

Here are a few use cases for this project:

  1. Hardware Manufacturing Quality Control: The model can be used to help hardware manufacturing companies efficiently sort and identify screws during production and post-production stages. Using "Yolov5_seg", they can ensure the right type of screws are packaged and shipped - eliminating human error.

  2. Automated Assembly Lines: The model can support automated assembly lines, especially those involving machines that need to pick up and use specific types of screws. It could distinguish between vertical and horizontal screws, assisting in more precise and efficient production processes.

  3. Inventory Management in Construction and Engineering Fields: This model can facilitate automatic counting and classification of screws, aiding in maintaining an accurate inventory. Stored images of screws can be used to identify type and calculate quantities, helping to prevent supply shortages or overstocking.

  4. Education and Training Tools: Computer vision models such as "Yolov5_seg" can be used in educational resources or training tools to help students or new workers learn to identify different classes of screws easily.

  5. Recycling Processes: The model could be used to sort screws during the disassembly of discarded appliances or machinery, supporting recycling processes by identifying types of screws and segregating them for reuse or proper disposal.

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Cite This Project

LICENSE
CC BY 4.0

If you use this dataset in a research paper, please cite it using the following BibTeX:

                        @misc{
                            yolov5_seg-tm3yy_dataset,
                            title = { Yolov5_seg Dataset },
                            type = { Open Source Dataset },
                            author = { Segmentation yolov5 },
                            howpublished = { \url{ https://universe.roboflow.com/segmentation-yolov5/yolov5_seg-tm3yy } },
                            url = { https://universe.roboflow.com/segmentation-yolov5/yolov5_seg-tm3yy },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { sep },
                            note = { visited on 2024-11-22 },
                            }
                        
                    

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