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1 0.484802740234375 0.801756626953125 0.519224658203125 0.816407228515625 0.5536438359375 0.801756626953125 0.56252602734375 0.77050843359375 0.545871232421875 0.757812048828125 0.5147835625 0.755860240234375 0.4892438359375 0.768554216796875 0.483693150390625 0.78320241015625 0.484802740234375 0.801756626953125
1 0.357115068359375 0.80468674609375 0.397087671875 0.80468674609375 0.422624658203125 0.78808674609375 0.422624658203125 0.76074216796875 0.395975341796875 0.745118072265625 0.420402740234375 0.727539759765625 0.42706575390625 0.7099614453125 0.41263013671875 0.673828916015625 0.379320548828125 0.669922890625 0.356002740234375 0.680665060546875 0.347120548828125 0.71191325390625 0.369328767578125 0.745118072265625 0.342679451171875 0.76074216796875 0.33046575390625 0.7812506015625 0.3393479453125 0.80078072265625 0.357115068359375 0.80468674609375
1 0.3082602734375 0.835937349609375 0.28827397265625 0.859375904296875 0.301597259765625 0.8925783125 0.388202740234375 0.914062650390625 0.428175341796875 0.919922890625 0.449271232421875 0.893554216796875 0.441498630859375 0.865233734375 0.3926438359375 0.863281927734375 0.343789041015625 0.832031326171875 0.3082602734375 0.835937349609375
1 0.2971561640625 0.619139759765625 0.226093150390625 0.595703615234375 0.1572520546875 0.603515662109375 0.1261643828125 0.636718072265625 0.12727397265625 0.668944578125 0.143928767578125 0.68554698828125 0.217210958984375 0.677734939453125 0.270506849609375 0.701171083984375 0.302706849609375 0.688477109375 0.313810958984375 0.657226505859375 0.2971561640625 0.619139759765625
1 0.1050684921875 0.754881927734375 0.121723287109375 0.78320241015625 0.17057808203125 0.785156626953125 0.18279178125 0.776366265625 0.19167397265625 0.749024095703125 0.1683561640625 0.70898554296875 0.119501369140625 0.697265060546875 0.10617808203125 0.720703615234375 0.1050684921875 0.754881927734375
1 0.420402740234375 0.420898794921875 0.40596986328125 0.44921927734375 0.44594246484375 0.4960939765625 0.48813424609375 0.490233734375 0.502567123046875 0.463867470703125 0.522553423828125 0.4521493984375 0.53143835546875 0.387696384765625 0.505898630859375 0.375 0.474810958984375 0.3789060234375 0.420402740234375 0.420898794921875
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医学图像分割数据集:肿瘤语义分割(2类)【数据集+标签文件】
共2000个文件
txt:2000个
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图像分辨率为:512*512,可用于细粒度分割 数据格式:jpg mask标签格式:png 标签信息:0 没有肿瘤、1为肿瘤。【具体的标签类别可以在classes txt文本中查看】 标注为yolov5的txt格式。 数据集介绍:分为训练集、验证集、测试集 训练集:images图片目录+masks模板目录,4159张图片和4159个对应的mask图像 验证集:images图片目录+masks模板目录,444张图片和444个对应的mask图像 测试集:images图片目录+masks模板目录,160张图片和160个对应的mask图像 网络分割可以参考:https://blog.csdn.net/qq_44886601/category_12102735.html yolov5的分割实战:https://blog.csdn.net/qq_44886601/article/details/139504744
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医学图像分割数据集:肿瘤语义分割(2类)【数据集+标签文件】 (2000个子文件)
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