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keremberke/garbage-object-detection

Roboflow Dataset Page https://universe.roboflow.com/material-identification/garbage-classification-3/dataset/2 Dataset Labels ['biodegradable', 'cardboard', 'glass', 'metal', 'paper', 'plastic'] Citation @misc{ garbage-classification-3_dataset, title = { GARBAGE CLASSIFICATION 3 Dataset }, type = { Open Source Dataset }, author = { Material Identification }, howpublished = { \\url{… See the full description on the dataset page: https://huggingface.co/datasets/keremberke/garbage-object-detection.

sourceHugging Faceupdated 4y agoView on Hugging Face
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Dataset Card

Roboflow Dataset Page

https://universe.roboflow.com/material-identification/garbage-classification-3/dataset/2

Dataset Labels

['biodegradable', 'cardboard', 'glass', 'metal', 'paper', 'plastic']

Citation

@misc{ garbage-classification-3_dataset,
    title = { GARBAGE CLASSIFICATION 3 Dataset },
    type = { Open Source Dataset },
    author = { Material Identification },
    howpublished = { \\url{ https://universe.roboflow.com/material-identification/garbage-classification-3 } },
    url = { https://universe.roboflow.com/material-identification/garbage-classification-3 },
    journal = { Roboflow Universe },
    publisher = { Roboflow },
    year = { 2022 },
    month = { mar },
    note = { visited on 2023-01-02 },
}

License

CC BY 4.0

Dataset Summary

This dataset was exported via roboflow.com on July 27, 2022 at 5:44 AM GMT

Roboflow is an end-to-end computer vision platform that helps you

  • —collaborate with your team on computer vision projects
  • —collect & organize images
  • —understand unstructured image data
  • —annotate, and create datasets
  • —export, train, and deploy computer vision models
  • —use active learning to improve your dataset over time

It includes 10464 images. GARBAGE-GARBAGE-CLASSIFICATION are annotated in COCO format.

The following pre-processing was applied to each image:

  • —Auto-orientation of pixel data (with EXIF-orientation stripping)
  • —Resize to 416x416 (Stretch)

The following augmentation was applied to create 1 versions of each source image:

  • —50% probability of horizontal flip
  • —50% probability of vertical flip
  • —Equal probability of one of the following 90-degree rotations: none, clockwise, counter-clockwise, upside-down