MangoImageBD: An Extensive Image Dataset of Common and Popular Mango Varieties in Bangladesh for Identification and Classification

Type of data: 504 x 1120 px mango images. Data format: JPEG. Contents of the dataset: Images (original, processed, and augmented) of common and popular varieties of mangoes in Bangladesh. Number of classes: Fifteen (15) common and popular varieties of mangoes in Bangladesh - (1) Amrapali, (2) Ashshina Classic, (3) Ashshina Zhinuk, (4) Banana Mango, (5) Bari-4, (6) Bari-11, (7) Fazli Classic, (8) Fazli Shurmai, (9) Gourmoti, (10) Harivanga, (11) Himsagor, (12) Katimon, (13) Langra, (14) Rupali, and (15) Shada. Number of images: Total number of images in the dataset: 28,515. (1) Total original (raw) images of mango cultivars (MangoOriginal) = 5,703, (2) Total processed images with a blend of both real and virtual backgrounds (MangoRealVirtual) = 5,703, and (3) Total augmented images (MangoAugmented)= 17,109. Distribution of instances: (1) Original (raw) images in each class of the mango cultivars (MangoOriginal): Amrapali = 135, Ashshina Classic = 571, Ashshina Zhinuk = 1,286, Banana Mango = 83, Bari-4 = 74, Bari-11 = 1,244, Fazli Classic = 171, Fazli Shurmai = 247, Gourmoti = 630, Harivanga = 265, Himsagor = 106, Katimon = 424, Langra = 120, Rupali = 184, and Shada = 163. (2) Processed images with a blend of both real and virtual backgrounds for each class of the mango cultivars (MangoRealVirtual): Amrapali = 135, Ashshina Classic = 571, Ashshina Zhinuk = 1,286, Banana Mango = 83, Bari-4 = 74, Bari-11 = 1,244, Fazli Classic = 171, Fazli Shurmai = 247, Gourmoti = 630, Harivanga = 265, Himsagor = 106, Katimon = 424, Langra = 120, Rupali = 184, and Shada = 163. (3) Augmented images for each class of the mango cultivars (MangoAugmented): Amrapali = 405, Ashshina Classic = 1,713, Ashshina Zhinuk = 3,858, Banana Mango = 249, Bari-4 = 222, Bari-11 = 3,732, Fazli Classic = 513, Fazli Shurmai = 741, Gourmoti = 1,890, Harivanga = 795, Himsagor = 318, Katimon = 1,272, Langra = 360, Rupali = 552, and Shada = 489. Dataset size: Total size of the dataset = 1.35 GB and the compressed ZIP file size = 1.16 GB. Data acquisition process: Images of various mango varieties are captured through high-definition smartphone cameras focusing from different angles. Data source location: Local wholesale and retail fruit markets located in six geographically distributed districts of Bangladesh, namely Chapai Nawabganj, Dhaka, Panchagarh, Rajshahi, Rangpur, and Satkhira which are renowned for diverse mango cultivation and availability. Where applicable: Training and evaluating machine learning and deep learning models to identify and classify mango varieties in Bangladesh which can be useful in smart horticulture, precision farming, supply chain automation, ecology and ecosystem health monitoring, and biodiversity and conservation efforts.数据类型：分辨率为504×1120像素的芒果图像。 数据格式：JPEG。 数据集内容：涵盖孟加拉国常见热门芒果品种的原始图像、处理后图像与增强图像。 类别数量：数据集包含孟加拉国15种常见热门芒果品种，分别为：1. 阿姆拉帕利（Amrapali）、2. 阿希娜经典（Ashshina Classic）、3. 阿希娜珠努克（Ashshina Zhinuk）、4. 香蕉芒（Banana Mango）、5. 巴里-4（Bari-4）、6. 巴里-11（Bari-11）、7. 法兹利经典（Fazli Classic）、8. 法兹利舒迈（Fazli Shurmai）、9. 古尔莫蒂（Gourmoti）、10. 哈里万加（Harivanga）、11. 希姆萨戈尔（Himsagor）、12. 卡蒂蒙（Katimon）、13. 朗格拉（Langra）、14. 鲁帕利（Rupali）、15. 沙达（Shada）。 图像总量：数据集总图像数为28515张，其中： (1) 芒果品种原始（原生）图像集（MangoOriginal）共计5703张； (2) 虚实背景融合处理后的芒果图像集（MangoRealVirtual）共计5703张； (3) 芒果增强图像集（MangoAugmented）共计17109张。 样本分布情况： (1) 各芒果品种的原始（原生）图像集（MangoOriginal）样本量：阿姆拉帕利（Amrapali）135张、阿希娜经典（Ashshina Classic）571张、阿希娜珠努克（Ashshina Zhinuk）1286张、香蕉芒（Banana Mango）83张、巴里-4（Bari-4）74张、巴里-11（Bari-11）1244张、法兹利经典（Fazli Classic）171张、法兹利舒迈（Fazli Shurmai）247张、古尔莫蒂（Gourmoti）630张、哈里万加（Harivanga）265张、希姆萨戈尔（Himsagor）106张、卡蒂蒙（Katimon）424张、朗格拉（Langra）120张、鲁帕利（Rupali）184张、沙达（Shada）163张。 (2) 各芒果品种的虚实背景融合处理图像集（MangoRealVirtual）样本量：阿姆拉帕利（Amrapali）135张、阿希娜经典（Ashshina Classic）571张、阿希娜珠努克（Ashshina Zhinuk）1286张、香蕉芒（Banana Mango）83张、巴里-4（Bari-4）74张、巴里-11（Bari-11）1244张、法兹利经典（Fazli Classic）171张、法兹利舒迈（Fazli Shurmai）247张、古尔莫蒂（Gourmoti）630张、哈里万加（Harivanga）265张、希姆萨戈尔（Himsagor）106张、卡蒂蒙（Katimon）424张、朗格拉（Langra）120张、鲁帕利（Rupali）184张、沙达（Shada）163张。 (3) 各芒果品种的增强图像集（MangoAugmented）样本量：阿姆拉帕利（Amrapali）405张、阿希娜经典（Ashshina Classic）1713张、阿希娜珠努克（Ashshina Zhinuk）3858张、香蕉芒（Banana Mango）249张、巴里-4（Bari-4）222张、巴里-11（Bari-11）3732张、法兹利经典（Fazli Classic）513张、法兹利舒迈（Fazli Shurmai）741张、古尔莫蒂（Gourmoti）1890张、哈里万加（Harivanga）795张、希姆萨戈尔（Himsagor）318张、卡蒂蒙（Katimon）1272张、朗格拉（Langra）360张、鲁帕利（Rupali）552张、沙达（Shada）489张。 数据集规模：数据集总容量为1.35GB，压缩ZIP包容量为1.16GB。 数据采集流程：采用高清智能手机摄像头，从不同角度拍摄各芒果品种的图像。 数据来源地：采集自孟加拉国6个地理分布各异的地区的本地果蔬批发市场与零售市场，分别为恰帕伊·纳瓦布甘杰（Chapai Nawabganj）、达卡（Dhaka）、潘查加尔（Panchagarh）、拉杰沙希（Rajshahi）、朗布尔（Rangpur）与萨特基拉（Satkhira），这些地区以多样的芒果种植与丰产闻名。 适用场景：可用于训练与评估机器学习、深度学习模型，以识别并分类孟加拉国芒果品种，可应用于智能园艺、精准农业、供应链自动化、生态与生态系统健康监测以及生物多样性保护等领域。