Commit e374d77

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Update evaluate.py

fix a bug

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Lines changed: 3 additions & 3 deletions

Original file line number	Diff line number	Diff line change
`@@ -132,6 +132,7 @@ def predict_sliding(net, image, tile_size, classes, flip_evaluation, recurrence)`
`132`	`132`	`return full_probs`
`133`	`133`
`134`	`134`	`def predict_whole(net, image, tile_size, recurrence):`
	`135`	`+ image = torch.from_numpy(image)`
`135`	`136`	`interp = nn.Upsample(size=tile_size, mode='bilinear', align_corners=True)`
`136`	`137`	`prediction = net(image.cuda())`
`137`	`138`	`if isinstance(prediction, list):`
`@@ -152,10 +153,9 @@ def predict_multiscale(net, image, tile_size, scales, classes, flip_evaluation,`
`152`	`153`	`scale = float(scale)`
`153`	`154`	`print("Predicting image scaled by %f" % scale)`
`154`	`155`	`scale_image = ndimage.zoom(image, (1.0, 1.0, scale, scale), order=1, prefilter=False)`
`155`		`- scale_image = torch.from_numpy(scale_image)`
`156`	`156`	`scaled_probs = predict_whole(net, scale_image, tile_size, recurrence)`
`157`		`- if flip_evaluation == 'True':`
`158`		`- flip_scaled_probs = predict_whole_img(net, scale_image[:,:,:,::-1].copy(), tile_size, recurrence)`
	`157`	`+ if flip_evaluation == True:`
	`158`	`+ flip_scaled_probs = predict_whole(net, scale_image[:,:,:,::-1].copy(), tile_size, recurrence)`
`159`	`159`	`scaled_probs = 0.5 * (scaled_probs + flip_scaled_probs[:,::-1,:])`
`160`	`160`	`full_probs += scaled_probs`
`161`	`161`	`full_probs /= len(scales)`

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