Update app.py
Browse files
app.py
CHANGED
@@ -86,7 +86,7 @@ def test(gpu_id, net, img_list, group_size, img_size):
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group_img[i]=img_transform(Image.fromarray(img_list[i]))
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_,pred_mask=net(group_img*1)
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pred_mask=(pred_mask.detach().squeeze()*255).numpy().astype(np.uint8)
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-
pred_mask=[crf_refine(((group_img[i]-group_img[i].min())/(group_img[i].max()-group_img[i].min())*255).permute(1,2,0).numpy().astype(np.uint8),pred_mask[i]) for i in range(5)]
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print(pred_mask[0].shape)
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result = [Image.fromarray((torch.from_numpy(pred_mask[i]).unsqueeze(2).repeat(1,1,3)).numpy()) for i in range(5)]
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#w, h = 224,224#Image.open(image_list[i][j]).size
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group_img[i]=img_transform(Image.fromarray(img_list[i]))
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_,pred_mask=net(group_img*1)
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pred_mask=(pred_mask.detach().squeeze()*255).numpy().astype(np.uint8)
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+
pred_mask=[crf_refine(((group_img[i]-group_img[i].min())/(group_img[i].max()-group_img[i].min())*255).permute(1,2,0).contiguous().numpy().astype(np.uint8),pred_mask[i]) for i in range(5)]
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print(pred_mask[0].shape)
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result = [Image.fromarray((torch.from_numpy(pred_mask[i]).unsqueeze(2).repeat(1,1,3)).numpy()) for i in range(5)]
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#w, h = 224,224#Image.open(image_list[i][j]).size
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