soybeans-noted-augumented-cut

The dataset contains 20,539 images of grains annotated with bounding boxes in YOLOv8 format. These images have been pre-processed and augmented to enhance model training for grain classification and defect detection. The following pre-processing steps were applied to each image: Auto-orientation of pixel data (with EXIF-orientation stripping) Resize to 600x600 pixels (stretching) Grayscale conversion (CRT phosphor) Auto-contrast via histogram equalization Additionally, the following augmentation techniques were applied to create three versions of each source image: 50% probability of horizontal flip 50% probability of vertical flip Random rotation between -15 and +15 degrees Random brightness adjustment between -15% and +15% This dataset was created to support computer vision models by providing a diverse range of augmented data for better model generalization and accuracy. The images are in JPG format and are annotated to identify grain defects such as moldy, burnt, pecky, scorched, greenish, and good grains. Format: YOLOv8 bounding box annotations. Image Size: Resized to 600x600 pixels. Number of Images: 20,539 images (with augmentations generating additional versions of each source image).本数据集包含20539张谷物图像，所有图像均采用YOLOv8格式的边界框进行标注。为提升谷物分类与缺陷检测的模型训练效果，已对这批图像完成预处理与数据增强操作。 针对每张图像执行以下预处理步骤： - 像素数据自动定向（剥离EXIF方向信息） - 调整至600×600像素尺寸（拉伸处理） - 采用CRT荧光粉模式完成灰度转换 - 通过直方图均衡化实现自动对比度调整 此外，通过以下数据增强技术为每张源图像生成三个变体版本： - 水平翻转概率为50% - 垂直翻转概率为50% - 随机旋转角度范围为-15°至+15° - 亮度随机调整幅度为-15%至+15% 本数据集旨在为计算机视觉模型提供多样化的增强训练数据，助力提升模型的泛化能力与预测准确率。本次数据集的图像均采用JPG格式存储，标注内容涵盖霉变、焦糊、虫蛀、烤伤、发绿以及正常谷物等谷物缺陷类型。 相关参数说明如下： 标注格式：YOLOv8边界框标注 图像尺寸：调整至600×600像素 图像总数：20539张（通过数据增强为每张源图像生成额外变体）