FeliBreed – A Multi-Breed Cat Image Dataset

FeliBreed – A Multi-Breed Cat Image Dataset We present the FeliBreed dataset, a carefully curated collection of 300 real-world cat images from a variety of breeds. This dataset is designed to support robust image analysis, especially in tasks related to cat breed classification. Each image has been sourced from real-life settings, captured through fieldwork with cameras, ensuring the data is authentic and representative of different environments. Breakdown of the Dataset: • Tabby Cat: 28 images • Mixed Breed: 41 images • Local: 59 images • Bengal Cat: 14 images • Persian: 158 images Key Features: • Real-World Images: All images are sourced from real-life settings, making the dataset highly applicable for model training and validation. • Multi-Breed Representation: The dataset includes multiple breeds, ensuring diversity in the training data and improving the generalization of models. • High-Quality Data: The images are captured using professional cameras during fieldwork, guaranteeing high resolution and accuracy for image classification tasks. FeliBreed is an excellent resource for researchers and developers working on cat breed recognition and image classification tasks. By leveraging this dataset, machine learning models can achieve improved accuracy and robustness when deployed in real-world applications.FeliBreed数据集：多品种猫咪图像数据集 本研究发布FeliBreed数据集，该数据集经精心甄选，包含300张来自多个品种的真实场景猫咪图像。本数据集旨在支撑鲁棒性图像分析任务，尤其适用于猫咪品种分类相关研究。所有图像均采集自真实生活场景，通过专业相机实地拍摄获取，确保数据真实可靠且能代表不同环境下的猫咪样貌。 数据集构成： • 虎斑猫：28张 • 混种猫：41张 • 本土猫：59张 • 孟加拉豹猫：14张 • 波斯猫：158张 核心特性： • 真实场景图像：所有图像均采集自真实生活场景，可广泛应用于模型训练与验证任务。 • 多品种覆盖：数据集涵盖多个猫咪品种，确保训练数据的多样性，有效提升模型的泛化能力。 • 高质量数据：图像均通过专业相机实地拍摄获取，具备高分辨率特性，可为图像分类任务提供精准的数据支撑。 FeliBreed数据集是从事猫咪品种识别与图像分类任务的研究人员与开发者的优质资源。借助该数据集，机器学习模型在实际应用部署时可获得更高的准确率与鲁棒性。