sparksWLL
Results
4
issues of
sparksWLL
对于问题fieldD = np.array([[4,4,5],[1,2,3],[10,9,5],[0,0,1],[0,0,0],[1,1,1],[1,1,1],[0,1,0]]) chorm = np.array([[1,0,1,1,1,0,0,0,1,1,1,0,1], [0,1,0,0,1,1,0,1,0,1,1,1,1], [0,0,0,1,1,1,0,0,0,0,1,0,1]]) phen = ea.bs2ri(chorm,fieldD) 《Geatpy数据结构》文档出给出的结果是Phen = 7.6 5 11.51612903 3.4 8 6.87096774 1.6 7 5.32258065 而我代码运行的结果是 [[7.6 6. 4.41935484] [3.4 8. 3.64516129] [1.6...
Will the code for BoxSup be released?
所给权重的评价结果 指标（IoU 阈值为 0.5-0.95） 边界框 分割掩码 AP 0.475 0.440 AR 0.581 0.517 但是不得不说效果很流批
训练coco数据集时说，val_annotation_path为验证图片的标签文件。标签文件是指的是instances_train2017.json和instances_val2017.json吗