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Fruits-360 dataset

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DataCite Commons2025-05-13 更新2025-05-17 收录
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https://data.mendeley.com/datasets/rp73yg93n8/6
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Fruits-360: A dataset of images containing fruits, vegetables, nuts and seeds Version: 2025.04.21.0 The following fruits, vegetables, nuts and seeds are included: Apples (different varieties: Crimson Snow, Golden, Golden-Red, Granny Smith, Pink Lady, Red, Red Delicious), Apricot, Avocado, Avocado ripe, Banana (Yellow, Red, Lady Finger), Beans, Beetroot Red, Blackberry, Blueberry, Cabbage, Caju seed, Cactus fruit, Cantaloupe (2 varieties), Carambula, Carrot, Cauliflower, Cherimoya, Cherry (different varieties, Rainier), Cherry Wax (Yellow, Red, Black), Chestnut, Clementine, Cocos, Corn (with husk), Cucumber (ripened, regular), Dates, Eggplant, Fig, Ginger Root, Goosberry, Granadilla, Grape (Blue, Pink, White (different varieties)), Grapefruit (Pink, White), Guava, Hazelnut, Huckleberry, Kiwi, Kaki, Kohlrabi, Kumsquats, Lemon (normal, Meyer), Lime, Lychee, Mandarine, Mango (Green, Red), Mangostan, Maracuja, Melon Piel de Sapo, Mulberry, Nectarine (Regular, Flat), Nut (Forest, Pecan), Onion (Red, White), Orange, Papaya, Passion fruit, Peach (different varieties), Pepino, Pear (different varieties, Abate, Forelle, Kaiser, Monster, Red, Stone, Williams), Pepper (Red, Green, Orange, Yellow), Physalis (normal, with Husk), Pineapple (normal, Mini), Pistachio, Pitahaya Red, Plum (different varieties), Pomegranate, Pomelo Sweetie, Potato (Red, Sweet, White), Quince, Rambutan, Raspberry, Redcurrant, Salak, Strawberry (normal, Wedge), Tamarillo, Tangelo, Tomato (different varieties, Maroon, Cherry Red, Yellow, not ripened, Heart), Walnut, Watermelon, Zucchini (green and dark). Dataset properties Total number of images: 132739. Training set size: 99508 images. Test set size: 33231 images. Number of classes: 194 (fruits, vegetables, nuts and seeds). Image size: 100x100 pixels. Filename format: image_index_100.jpg (e.g. 32_100.jpg) or r_image_index_100.jpg (e.g. r_32_100.jpg) or r2_image_index_100.jpg or r3_image_index_100.jpg. "r" stands for rotated fruit. "r2" means that the fruit was rotated around the 3rd axis. "100" comes from image size (100x100 pixels). Different varieties of the same fruit (apple for instance) are stored as belonging to different classes. Repository structure Folders Training and Test contain images for training and testing purposes. Alternate download The Fruits-360 dataset can be downloaded from: https://www.kaggle.com/moltean/fruits https://github.com/fruits-360 How to cite Mihai Oltean, Fruits-360 dataset, 2017-. License: C BY-SA 4.0 Copyright (c) 2017-, Mihai Oltean You are free to: Share and Adapt. Under the following terms: Attribution — You must give appropriate credit and ShareAlike.

水果360(Fruits-360):一款涵盖水果、蔬菜、坚果与籽类图像的数据集 版本:2025.04.21.0 本数据集包含以下品类的图像:苹果(多个品种:深红雪、金冠、金红、格兰尼史密斯、粉红佳人、红苹果、蛇果)、杏、牛油果、成熟牛油果、香蕉(黄皮、红皮、手指香蕉)、菜豆、红甜菜、黑莓、蓝莓、卷心菜、腰果籽、仙人掌果、甜瓜(2个品种)、杨桃、胡萝卜、花椰菜、番荔枝、樱桃(多个品种:雷尼尔)、蜡质樱桃(黄、红、黑)、板栗、克莱门氏小柑橘、椰子、带苞玉米、成熟黄瓜、普通黄瓜、椰枣、茄子、无花果、生姜、醋栗、西番莲果、葡萄(蓝、粉、白(多个品种))、西柚(粉、白)、番石榴、榛子、越橘、猕猴桃、柿子、苤蓝、金柑、柠檬(普通、迈耶柠檬)、青柠、荔枝、蜜橘、芒果(青、红)、山竹、紫果西番莲、蛤蟆皮甜瓜、桑葚、油桃(普通、扁形)、坚果(森林坚果、碧根果)、洋葱(红、白)、橙子、木瓜、百香果、桃子(多个品种)、香瓜茄、梨(多个品种:阿巴特、弗洛尔、凯撒、梦得、红梨、斯通、威廉姆斯)、辣椒(红、绿、橙、黄)、酸浆(普通型、带宿存花萼)、菠萝(普通、迷你)、开心果、红火龙果、李子(多个品种)、石榴、蜜柚、土豆(红皮、甜薯、白皮)、榅桲、红毛丹、树莓、红醋栗、蛇皮果、草莓(普通、楔形切块)、树番茄、橘柚、番茄(多个品种:褐果、樱桃红、黄果、未成熟、心形)、核桃、西瓜、西葫芦(绿、深绿)。 数据集属性 总图像数量:132739张 训练集规模:99508张图像 测试集规模:33231张图像 类别总数:194类(涵盖水果、蔬菜、坚果与籽类) 图像尺寸:100×100像素 文件名格式:image_index_100.jpg(例如32_100.jpg)或r_image_index_100.jpg(例如r_32_100.jpg),亦支持r2_image_index_100.jpg或r3_image_index_100.jpg格式。其中“r”代表水果已进行旋转操作,“r2”表示水果绕第三轴旋转,“100”取自图像尺寸(100×100像素)。 同一水果的不同品种(例如苹果)将被划分为独立类别存储。 仓库结构 Training与Test文件夹分别存放训练与测试用图像。 备用下载渠道 水果360数据集可从以下地址获取: https://www.kaggle.com/moltean/fruits https://github.com/fruits-360 引用方式 Mihai Oltean, Fruits-360 dataset, 2017-. 许可证:知识共享署名-相同方式共享4.0(C BY-SA 4.0) 版权所有 © 2017-, Mihai Oltean 您可自由进行分享与改编,但需遵循以下条款:署名——您必须给出恰当的署名标注,并采用相同方式共享协议。
提供机构:
Mendeley Data
创建时间:
2025-04-25
搜集汇总
数据集介绍
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背景与挑战
背景概述
Fruits-360数据集是一个包含194类水果、蔬菜、坚果和种子的图像数据集,总计132,739张100x100像素的图像,分为训练集和测试集。数据集结构清晰,支持多种下载方式,适用于图像处理和机器学习任务。
以上内容由遇见数据集搜集并总结生成
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