Synthetic Fruit Computer Vision Project

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About this dataset

This dataset contains 6,000 example images generated with the process described in Roboflow's How to Create a Synthetic Dataset tutorial.

The images are composed of a background (randomly selected from Google's Open Images dataset) and a number of fruits (from Horea94's Fruit Classification Dataset) superimposed on top with a random orientation, scale, and color transformation. All images are 416x550 to simulate a smartphone aspect ratio.

To generate your own images, follow our tutorial or download the code.

Example Image

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{ synthetic-fruit_dataset,
    title = { Synthetic Fruit Dataset },
    type = { Open Source Dataset },
    author = { Brad Dwyer },
    howpublished = { \url{ } },
    url = { },
    journal = { Roboflow Universe },
    publisher = { Roboflow },
    year = { 2021 },
    month = { aug },
    note = { visited on 2023-01-31 },


Brad Dwyer


Brad Dwyer

Last Updated

a year ago

Project Type

Object Detection




Apple, Apricot, Avocado, Banana, Beetroot, Blueberry, Cactus, Cantaloupe, Carambula, Cauliflower, Cherry, Chestnut, Clementine, Cocos, Dates, Eggplant, Ginger, Granadilla, Grape, Grapefruit, Guava, Hazelnut, Huckleberry, Kaki, Kiwi, Kohlrabi, Kumquats, Lemon, Limes, Lychee, Mandarine, Mango, Mangostan, Maracuja, Melon, Mulberry, Nectarine, Nut, Onion, Orange, Papaya, Passion, Peach, Pear, Pepino, Pepper, Physalis, Pineapple, Pitahaya, Plum, Pomegranate, Pomelo, Potato, Quince, Rambutan, Raspberry, Redcurrant, Salak, Strawberry, Tamarillo, Tangelo, Tomato, Walnut


CC BY 4.0