dev1

Marine-litter

Object Detection

Marine-litter Computer Vision Project

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80 images
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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.

YOLOv5

This project has a YOLOv5 model checkpoint available for inference with Roboflow Deploy. YOLOv5 is a proven and tested, production ready, state-of-the-art real-time object detection model.

Cite This Project

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

@misc{
                            marine-litter-kaumx_dataset,
                            title = { Marine-litter Dataset },
                            type = { Open Source Dataset },
                            author = { dev1 },
                            howpublished = { \url{ https://universe.roboflow.com/dev1/marine-litter-kaumx } },
                            url = { https://universe.roboflow.com/dev1/marine-litter-kaumx },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2024 },
                            month = { feb },
                            note = { visited on 2024-05-05 },
                            }
                        

Connect Your Model With Program Logic

Find utilities and guides to help you start using the Marine-litter project in your project.

Source

dev1

Last Updated

2 months ago

Project Type

Object Detection

Subject

Marine-litter-recognition

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Views in previous 30 days: 0

Downloads: 0

Downloads in previous 30 days: 0

License

Public Domain

Classes

* 50% probability of horizontal flip * Auto-orientation of pixel data (with EXIF-orientation stripping) * Equal probability of one of the following 90-degree rotations: none, clockwise, counter-clockwise, upside-down * Random rotation of between -15 and +15 degrees * Resize to 416x416 (Stretch) * Salt and pepper noise was applied to 5 percent of pixels * annotate, and create datasets * collaborate with your team on computer vision projects * collect & organize images * export, train, and deploy computer vision models * understand unstructured image data * use active learning to improve your dataset over time 20 21 22 23 24 25 26 27 28 ============================== Bicchieri di plastica Bottiglia di plastica Bottiglia di vetro Busta di plastica Filo di nylon Imballaggio plastica It includes 111 images. Lattina Litter are annotated in YOLO v5 PyTorch format. Mascherina Metallo Mozziconi Plastica generica Polistirolo Posate di plastica Roboflow is an end-to-end computer vision platform that helps you Scarpe Sughero Tappo di plastica Tetrapak The following augmentation was applied to create 3 versions of each source image: The following pre-processing was applied to each image: This dataset was exported via roboflow This dataset was exported via roboflow.com on August 16, 2022 at 7:10 AM GMT marine litter - v1 2022-08-16 12:37pm