test_model.py: reformat

test_model.py

@@ -17,10 +17,8 @@ device = 'cuda'
 wandb.init(project="crestereo", entity="cpt-captain")
 
 
-
 # Ref: https://github.com/megvii-research/CREStereo/blob/master/test.py
 def inference(left, right, model, n_iter=20):
-
     print("Model Forwarding...")
     imgL = left.transpose(2, 0, 1)
     imgR = right.transpose(2, 0, 1)
@@ -53,7 +51,6 @@ def inference(left, right, model, n_iter=20):
 
 
 def inference_ctd(left, right, gt_disp, mask, model, epoch, n_iter=20):
-
     print("Model Forwarding...")
     # print(left.shape)
     left = left.cpu().detach().numpy()
@@ -111,13 +108,12 @@ def inference_ctd(left, right, gt_disp, mask, model, epoch, n_iter=20):
             caption=f"Pred. Disp. Dw2 It {i}\n{pred_disp_dw2.min():.{2}f}/{pred_disp_dw2.max():.{2}f}",
         )
 
-
     log['input_left'] = wandb.Image(left.astype('uint8'), caption="Input Left")
-    log['input_right'] = wandb.Image(right.cpu().detach().numpy().transpose(1,2,0).astype('uint8'), caption="Input Right")
+    log['input_right'] = wandb.Image(right.cpu().detach().numpy().transpose(1, 2, 0).astype('uint8'),
+                                     caption="Input Right")
 
     log['gt_disp'] = wandb.Image(gt_disp, caption=f"GT Disparity\n{gt_disp.min():.{2}f}/{gt_disp.max():.{2}f}")
 
-
     disp_error = gt_disp - disp
     log['disp_error'] = wandb.Image(
         normalize_and_colormap(disp_error),
@@ -178,7 +174,6 @@ def do_infer(left_img, right_img, gt_disp, model):
     })
 
 
-
 if __name__ == '__main__':
     # model_path = "models/crestereo_eth3d.pth"
     model_path = "train_log/models/latest.pth"
@@ -233,7 +228,8 @@ if __name__ == '__main__':
         # cv2.waitKey(0)
 
     else:
-            dataset = CTDDataset('/media/Data1/connecting_the_dots_data/ctd_data/', data_type=data_type, pattern_path=reference_pattern_path, augment=augment)
+        dataset = CTDDataset('/media/Data1/connecting_the_dots_data/ctd_data/', data_type=data_type,
+                             pattern_path=reference_pattern_path, augment=augment)
         dataloader = DataLoader(dataset, args.batch_size, shuffle=True,
                                 num_workers=0, drop_last=False, persistent_workers=False, pin_memory=True)
         for batch in dataloader:
@@ -245,4 +241,3 @@ if __name__ == '__main__':
                 imgR = right.cpu().detach().numpy()
                 gt_disp = disparity
                 do_infer(left_img, right_img, gt_disp, model)
-