Indotto Object Detection Dataset and Pre-Trained Model by Amer SPA

Images

2968 images

Explore Dataset

Here are a few use cases for this project:

Industrial Assembly Aid: Assist assembly line workers to quickly identify parts of indotto, indotto_buta, etc., ensuring they are using the correct components during assembly procedures.
Inventory Management: Automate inventory counting and sorting system in warehouses where these parts are stored, thereby eliminating human error and saving considerable time.
Quality Assurance: Inspect and identify different indotti types in production lines to ensure compliance with quality standards, potentially identifying defective or incorrect parts before they cause further problems down the line.
Supply Chain Management: For smooth operation of logistics, this model can be embedded into systems to classify and keep track of different indotti parts as they move through the supply chain.
E-commerce Solutions: Improve online shopping experiences by auto-tagging product images, allowing customers to easily find and identify the type of indotto or indotto_buta parts they need.

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.

Cite This Project

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

@misc{
                            indotto_dataset,
                            title = { Indotto Dataset },
                            type = { Open Source Dataset },
                            author = { Amer SPA },
                            howpublished = { \url{ https://universe.roboflow.com/amer-spa/indotto } },
                            url = { https://universe.roboflow.com/amer-spa/indotto },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2022 },
                            month = { oct },
                            note = { visited on 2024-04-26 },
                            }