Comments (5)
1 Could you please help me check the range of data = np.load(os.path.join(preprocesspath, pid+'_clean.npy'))
2 Sometimes the shape of data is smaller than bgx+CROPSIZE, bgy+CROPSIZE, bgz+CROPSIZE
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oh, the range of data is enough for cropsize, i didn't realize numpy is ok when out of range.
but , i still don't understand why you use 2-cropdatatmp to fill the cropdata, and i think cropdatatmp=np.array(data[0,bgx:crdx+cropsize/2,bgy:crdy+cropsize/2,bgz:crdz+cropsize/2) may be better
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I mean the min value and max value for the range.
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x : 117 378
y: 160 392
z: 168 400
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I think it should be np.array(cropdatatmp), not np.array(2-cropdatatmp)
It should not affect the GBT results because tree classifier is not affected by input range. Maybe you can get better results after changing it.
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Related Issues (20)
- AttributeError: 'str' object has no attribute 'shape' HOT 2
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- Preprocessing HOT 1
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- Reducing training image size HOT 3
- .
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- Pretrained weights gets changed after importing weights from Pytorch to ONNX. HOT 1
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- question about fuction and parameter HOT 3
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- FROC curve
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