Boxes on a Conveyer Belt Object Detection Dataset and Pre-Trained Model by Mohamed Traore

Images

33 images

Explore Dataset

Use Cases:

This dataset can be used to track boxes on an assembly or manufacturing line, or as a starter-dataset for package detection and "defect" detection use cases for boxes.

For the defect detection use case, one can Clone the images from this project to a new one, and add more examples (labels) of boxes with defects, such as: damaged corners, unsealed boxes, and more. This defect detection model can be built as a single object-detection model, or broken into a "two pass detection" model (identify the box and the defects with object detection --> send the cropped detections of the defects to a classification model to confirm the classification of the defect, and the severity)
Two Pass detection starter-code
Converting an Object Detection Dataset to Classification with Isolate Objects
Roboflow: Single Label Classification | Roboflow: Multi-Label Classification
Roboflow: Dataset Types | Adding Data: Classification
Formats | Multi-Label Classification Format | OpenAI CLIP Classification Format

Classes:

box

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{
                            boxes-on-a-conveyer-belt_dataset,
                            title = { Boxes on a Conveyer Belt Dataset },
                            type = { Open Source Dataset },
                            author = { Mohamed Traore },
                            howpublished = { \url{ https://universe.roboflow.com/mohamed-traore-2ekkp/boxes-on-a-conveyer-belt } },
                            url = { https://universe.roboflow.com/mohamed-traore-2ekkp/boxes-on-a-conveyer-belt },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2022 },
                            month = { nov },
                            note = { visited on 2024-04-19 },
                            }