Update app.py

app.py

@@ -96,7 +96,7 @@ def test(gpu_id, net, img_list, group_size, img_size):
         #    print(img_list[i].shape,pred_mask[i].shape)
         #pred_mask=[crf_refine(img_list[i],pred_mask[i]) for i in range(5)]
         print(pred_mask[0].shape)
-        result = [torch.cat([torch.from_numpy(img_resize[i]),torch.from_numpy(pred_mask[i]).unsqueeze(2).repeat(1,1,3)],dim=1).numpy() for i in range(5)]
+        result = [torch.cat([torch.from_numpy(img_resize[i]),torch.from_numpy(pred_mask[i]).unsqueeze(2).repeat(1,1,3)],dim=0).numpy() for i in range(5)]
         #w, h = 224,224#Image.open(image_list[i][j]).size
         #result = result.resize((w, h), Image.BILINEAR)
         #result.convert('L').save('0.png')
@@ -123,7 +123,7 @@ def sepia(img1,img2,img3,img4,img5):
   result_list=test(device,net,img_list,5,224)
   #result_list=[result_list[i].resize((w_list[i], h_list[i]), Image.BILINEAR) for i in range(5)]
   img1,img2,img3,img4,img5=result_list#test('cpu',net,img_list,5,224)
-  return np.concatenate([img1,img2,img3,img4,img5],axis=0)
+  return np.concatenate([img1,img2,img3,img4,img5],axis=1)
 
 #gr.Image(shape=(224, 2))
 #demo = gr.Interface(sepia, inputs=["image","image","image","image","image"], outputs=["image","image","image","image","image"])#gr.Interface(sepia, gr.Image(shape=(200, 200)), "image")