Edit Project

Damaged Container OJN

Object Detection

385 images

Damaged Container OJN Computer Vision Project

school

Updated a year ago

Fork Project

142

views

downloads

Metrics

mAP is equal to the average of the Average Precision metric across all classes in a model. Learn more

mAP

58.2%

Precision measures how often your model's predictions are correct. Learn more

Precision

85.9%

Recall measures what percentage of relevant labels were successfully identified. Learn more

Recall

53.3%

Try This Model

Drop an image or

browse your device

A description for this project has not been published yet.

Use This Trained Model

Try it in your browser, or deploy via our Hosted Inference API and other deployment methods.

Try In Browser Deploy Model

Cite This Project

LICENSE

MIT

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

                        
        highlighted
        
            
        
     
@misc{
                            damaged-container-ojn_dataset,
                            title = { Damaged Container OJN Dataset },
                            type = { Open Source Dataset },
                            author = { school },
                            howpublished = { \url{ https://universe.roboflow.com/school-q74ji/damaged-container-ojn } },
                            url = { https://universe.roboflow.com/school-q74ji/damaged-container-ojn },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { oct },
                            note = { visited on 2025-03-26 },
                            }