Update model initialization and add print statements for parameter counts

app.py

@@ -26,11 +26,19 @@ css = """
 """
 DEVICE = 'cuda' if torch.cuda.is_available() else 'cpu'
 model = NewCRFDepth(version='large07', inv_depth=False,
-                    max_depth=10).to(DEVICE).eval()
+                    max_depth=10, pretrained=None).to(DEVICE).eval()
+model.train()
+num_params = sum([np.prod(p.size()) for p in model.parameters()])
+print("== Total number of parameters: {}".format(num_params))
+num_params_update = sum([np.prod(p.shape)
+                        for p in model.parameters() if p.requires_grad])
+print("== Total number of learning parameters: {}".format(num_params_update))
+
 model = torch.nn.DataParallel(model)
 checkpoint = torch.load('checkpoints/nyu_L.pth',
                         map_location=torch.device(DEVICE))
 model.load_state_dict(checkpoint['model'])
+print("== Loaded checkpoint '{}'".format('checkpoints/nyu_L.pth'))
 
 title = "# IEBins: Iterative Elastic Bins for Monocular Depth Estimation"
 description = """Demo for **IEBins: Iterative Elastic Bins for Monocular Depth Estimation**.