To build this dataset, we first summarize a label system from ImageNet and OpenImage.
py Creates image dataset for different objects. This dataset serves as a benchmark for face photos and is inclusive of various real-world imaging conditions like noise, lighting, pose, and appearance. In addition, it is the best in terms of the ratio of speed to accuracy in the entire range of accuracy and speed from 15 FPS to 1774 FPS. The dataset has several features, such as object segmentation t to an object or not, IoU or Jaccard Index is used. You can find the code in the entire code here in my GITHUB repo. Object detection dataset github This large-scale and densely annotated dataset contains 655,451 object instances for 15 categories across 2,806 high-resolution images.
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