YOLO 格式的火灾检测-该数据集由人工注释，并使用不同的数据增强技术对数据进行增强

Fire_detection_dataset - v1 v1 ============================== This dataset was exported via roboflow.ai on June 13, 2021 at 3:22 PM GMT It includes 270 images. Fire are annotated in YOLO v5 PyTorch format. The following pre-processing was applied to each image: * Auto-orientation of pixel data (with EXIF-orientation stripping) * Resize to 416x416 (Stretch) The following augmentation was applied to create 3 versions of each source image: * 50% probability of horizontal flip * 50% probability of vertical flip * Equal probability of one of the following 90-degree rotations: none, clockwise, counter-clockwise * Randomly crop between 0 and 20 percent of the image * Random shear of between -15° to +15° horizontally and -15° to +15° vertically * Random exposure adjustment of between -25 and +25 percent * Random Gaussian blur of between 0 and 10 pixels * Salt and pepper noise was applied to 5 percent of pixels