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In file data.py , the shapes of proj_labdel and proj_weight are (out_height, out_width, self.num_class, 2) initially. After proj_label = np.expand_dims(proj_label, axis=0) and proj_weight = np.expand_dims(proj_weight, axis=0) , it should be (1, out_height, out_width, self.num_class, 2) .
In the evaluation part of file solver.py , the shape of the ouptput of proj_regression_loss layer is (1, out_height, out_width, 20) . You directly feed proj_label , proj_weight and that output to function smoothl1_metric. Then you traverse the data through size = label.shape[0]. I wonder that you might have flatted the data somewhere, or the value of size should be 1.
In file
data.py
, the shapes ofproj_labdel
andproj_weight
are(out_height, out_width, self.num_class, 2)
initially. Afterproj_label = np.expand_dims(proj_label, axis=0)
andproj_weight = np.expand_dims(proj_weight, axis=0)
, it should be(1, out_height, out_width, self.num_class, 2)
.In the evaluation part of file
solver.py
, the shape of the ouptput ofproj_regression_loss
layer is(1, out_height, out_width, 20)
. You directly feedproj_label
,proj_weight
and that output to functionsmoothl1_metric
. Then you traverse the data throughsize = label.shape[0]
. I wonder that you might have flatted the data somewhere, or the value of size should be 1.Could you please explain this to me? @YunzhuLi
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