Coffee Bean Dataset Resized

Description: This dataset is a resized version of the original Coffee Bean Dataset Resized Version 1, offering high-quality images of roasted coffee beans, meticulously captured to aid in various machine learning and image recognition tasks. Dataset Details: Roasting Levels: The dataset includes coffee beans roasted at four distinct levels: Green (Unroasted) Coffee Beans: Laos Typica Bolaven (Coffea arabica) Lightly Roasted Beans: Laos Typica Bolaven (Coffea arabica) Medium Roasted Beans: Doi Chaang (Coffea arabica) Dark Roasted Beans: Brazil Cerrado (Coffea arabica) Photography Details: The images were captured using an iPhone 12 Mini, equipped with a 12-megapixel back camera, featuring Ultra-wide and WideCamera capabilities. The camera setup was designed to ensure a plane parallel to the object’s path during image capture, guaranteeing consistency and clarity. Photographs were taken under various lighting conditions, including both LED light from a lightbox and natural light, to simulate different real-world environments and enhance the dataset’s versatility. Download Dataset Image Specifications: Format: PNG Resolution: Each image measures 3024×3032 pixels, ensuring high-resolution details suitable for detailed analysis and machine learning tasks. Quantity: The dataset comprises a total of 4800 images, divided evenly across the four roasting levels, with 1200 images per level. Additional Features: Noise Enhancement: To simulate real-world scenarios, images include enhanced noise by placing each variety of coffee beans in a container. This feature aims to improve the robustness of machine learning models trained using this dataset. Diverse Settings: The dataset includes images captured in a variety of settings, providing a broad spectrum of inputs to validate and train image recognition systems effectively. Applications: This comprehensive dataset is ideal for: Machine Learning: Training models for image classification, object detection, and other AI tasks. Quality Control: Automated inspection systems in coffee production and roasting facilities. Research: Studies related to food processing, quality analysis, and agricultural research. Educational Purposes: Teaching materials for courses on machine learning, image processing, and computer vision. This dataset is sourced from Kaggle.