Food Waste Detection

Object Detection

Roboflow Universe Food Food Waste Detection

Food Waste Detection Computer Vision Project


2716 images
Explore Dataset


Food waste detection dataset.

Labelling instruction:

  1. Label Every Object of Interest in Every Image
  2. Label the Entirety of an Object
  3. Label Occluded Objects, as if they were fully visible (It is a common misconception that boxes cannot overlap.)
  4. Create Tight Bounding Boxes. The edges of bounding boxes should touch the outermost pixels of the object that is being labeled.
  5. Create Specific Label Names (e.g. white pawn, black pawn, green apple, red apple). We can regroup them later into the same class within roboflow preprocessing step .
  6. Maintain Clear Labeling Instructions

Cite this Project

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

@misc{ food-waste-detection-jghxg_dataset,
    title = { Food Waste Detection Dataset },
    type = { Open Source Dataset },
    author = { Food },
    howpublished = { \url{ } },
    url = { },
    journal = { Roboflow Universe },
    publisher = { Roboflow },
    year = { 2022 },
    month = { oct },
    note = { visited on 2023-12-06 },

Find utilities and guides to help you start using the Food Waste Detection project in your project.



Last Updated

a year ago

Project Type

Object Detection




Apple, Apple-core, Apple-peel, Banana, Bone, Bone-fish, Bread, Bun, Chicken-skin, Congee, Cucumber, Drink, Egg-hard, Egg-scramble, Egg-shell, Egg-steam, Egg-yolk, Fish, Meat, Mushroom, Mussel, Mussel-shell, Noodle, Orange, Orange-peel, Other-waste, Pancake, Pasta, Pear, Pear-core, Pear-peel, Potato, Rice, Shrimp, Shrimp-shell, Tofu, Tomato, Vegetable, Vegetable-root

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