油罐识别模型训练数据集
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油罐识别模型训练数据集以高分卫星影像作为数据源,裁切出含有油罐的目标区域,用图片随机旋转、随机颜色等方式对数据集进行数据增强。用标注工具对图片进行水平矩形框标注,得到该数据集。该数据集作为深度学习识别模型训练样本集,用于提高自动化识别精度和稳定性,用于能源统计、期货交易、环境监测等领域。
The training dataset for oil tank recognition models uses high-resolution satellite imagery as the data source. First, target regions containing oil tanks are cropped out. Subsequently, data augmentation is conducted on the dataset via techniques including random image rotation and random color adjustment. Finally, the dataset is obtained by annotating the images with horizontal bounding boxes using professional annotation tools. This dataset serves as a training sample set for deep learning recognition models to improve the accuracy and stability of automated recognition, and is applicable to fields such as energy statistics, futures trading, and environmental monitoring.




