Refactor depth prediction and post-processing in app.py

app.py

@@ -93,11 +93,15 @@ with gr.Blocks(css=css) as demo:
         # image = torch.from_numpy(image).unsqueeze(0)
         image = torch.autograd.Variable(image.unsqueeze(0))
 
-        depth = predict_depth(model, image)
-        depth = F.interpolate(depth[None], (h, w),
-                              mode='bilinear', align_corners=False)[0, 0]
+        pred_depths_r_list, _, _ = predict_depth(model, image)
+        image_flipped = flip_lr(image)
+        pred_depths_r_list_flipped, _, _ = model(image_flipped)
+        pred_depth = post_process_depth(
+            pred_depths_r_list[-1], pred_depths_r_list_flipped[-1])
 
-        raw_depth = Image.fromarray(depth.cpu().numpy().astype('uint16'))
+        pred_depth = pred_depth.cpu().numpy().squeeze()
+
+        raw_depth = Image.fromarray(pred_depth.cpu().numpy().astype('uint16'))
         tmp = tempfile.NamedTemporaryFile(suffix='.png', delete=False)
         raw_depth.save(tmp.name)