Thermal-Images-of-Bread-Contamination-Labeled

This dataset consists of thermal images of bread slices, both contaminated and uncontaminated, designed for training and evaluating computer vision models for contamination detection. Commercial white bread was used, with slices standardized for size (10x10x1 cm) and moisture content (35 ± 2%). Four common food processing contaminants (deionized water, refined vegetable oil, food-grade machinery grease, and a diluted cleaning agent) were applied at two different levels, with 50 bread slices prepared for each contaminant and 50 uncontaminated controls. Contaminant application was carefully controlled using micropipettes and spatulas, with triplicate runs for each scenario. Thermal images were captured using a FLIR One Pro camera (160x120 resolution, 70 mK sensitivity) within a custom-built, light- and temperature-controlled enclosure. A hot-air blower provided a heat stimulus (35°C airflow for 2 or 3 seconds) at a 45° angle, and a conveyor system with a non-reflective black surface ensured consistent imaging. A total of 650 thermal images were acquired. Preprocessing and augmentation were performed using Roboflow software. Preprocessing steps included auto-orientation, cropping, resizing to 640x640, auto-contrast adjustment, and grayscale conversion. Augmentation techniques included flipping and exposure adjustments. The final dataset comprises 1342 training images, 56 validation images, and 28 test images along with their labels.

本数据集包含受污染与未受污染的面包切片热成像图像，旨在用于训练与评估用于污染物检测的计算机视觉模型。实验采用商用白面包，面包切片尺寸统一为10×10×1厘米，含水率控制在35±2%。四种常见食品加工污染物（去离子水、精制植物油、食品级机械润滑脂及稀释清洁剂）以两种不同施加量进行处理，每种污染物对应50片面包切片，另设50片未受污染的对照切片。污染物的施加过程通过微量移液器与刮铲严格管控，每种实验场景均开展三次重复实验。热成像图像采集采用FLIR One Pro相机（分辨率160×120，灵敏度70 mK），采集环境为定制搭建的光照与温度可控封闭舱。采用热风鼓风机以45°角提供热刺激（35℃气流，持续2或3秒），搭配带有非反射黑色表面的传送带系统，以确保成像一致性。最终共采集得到650张热成像图像。后续使用Roboflow软件完成图像预处理与数据增强操作。预处理步骤涵盖自动方向校正、裁剪、尺寸调整至640×640、自动对比度调整以及灰度转换。数据增强技术则包含图像翻转与曝光度调整。最终数据集共包含1342张训练图像、56张验证图像与28张测试图像，且均附带对应标注标签。