LightPipes Computer Vision Project

Public

Updated 3 years ago

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Classes (5)
DE-9 Plug Hole
Light Pipe Fillled
Light Pipe Hole
Plug Hole
QR Code
Description

Here are a few use cases for this project:

  1. Manufacturing Quality Control: LightPipes can be utilized in factories to automate the quality control process for products that contain light pipes, plug holes, and other components. By accurately identifying these features, the model can help in detecting manufacturing defects, misalignments, or inconsistencies in real-time.

  2. Smart Inventory Management: Manufacturers can use LightPipes to track and categorize various components in their inventory. The model can identify QR codes and light pipe classes, allowing for efficient organization of stock and simplifying the process of reordering necessary parts.

  3. Customized Product Design: LightPipes can assist engineers and designers in creating custom electronic devices and products. By recognizing specific components and their respective dimensions, the model enables designers to ensure compatibility and functionality of their designs without requiring extensive knowledge of each individual part.

  4. Robotics and Assembly Automation: LightPipes can be integrated into robotic assembly systems, guiding robots to pick and place the correct components in designated locations. By accurately identifying the components like light pipe holes, DE-9 plug holes, and QR codes, robots can assemble products with enhanced speed and precision.

  5. Electronics Repair and Troubleshooting: LightPipes can be employed as a diagnostic tool for technicians and engineers working on electronics repair. By identifying specific light pipe production classes and components, the model can help technicians in pinpointing issues, suggesting appropriate replacement parts, and streamlining the repair process.

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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{
                            lightpipes-n6sah_dataset,
                            title = { LightPipes Dataset },
                            type = { Open Source Dataset },
                            author = { Public },
                            howpublished = { \url{ https://universe.roboflow.com/public-oo1zk/lightpipes-n6sah } },
                            url = { https://universe.roboflow.com/public-oo1zk/lightpipes-n6sah },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2022 },
                            month = { mar },
                            note = { visited on 2024-12-21 },
                            }
                        
                    

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