Update inference_img.py

inference_img.py

@@ -30,16 +30,17 @@ import warnings
         model = Model()
         model.load_model(args.modelDir, -1)
         print("Loaded RIFE_HDv3 model.")
+        print("Checkpoint reached!")
     except:
         from train_log.IFNet_HDv3 import Model
         model = Model()
         model.load_model(args.modelDir, -1)
         print("Loaded IFNet_HDv3 model.")
+        print("Checkpoint reached!")
     
     model.eval()
     model.device()
 
-    
     if args.img[0].endswith('.exr') and args.img[1].endswith('.exr'):
         img0 = cv2.imread(args.img[0], cv2.IMREAD_COLOR | cv2.IMREAD_ANYDEPTH)
         img1 = cv2.imread(args.img[1], cv2.IMREAD_COLOR | cv2.IMREAD_ANYDEPTH)
@@ -59,7 +60,6 @@ import warnings
     img0 = F.pad(img0, padding)
     img1 = F.pad(img1, padding)
     
-    
     if args.ratio:
         img_list = [img0]
         img0_ratio = 0.0
@@ -97,6 +97,9 @@ import warnings
     
     if not os.path.exists('output'):
         os.mkdir('output')
+        
+    print("Checkpoint reached!")
+
     for i in range(len(img_list)):
         if args.img[0].endswith('.exr') and args.img[1].endswith('.exr'):
             cv2.imwrite('output/img{}.exr'.format(i), (img_list[i][0]).cpu().numpy().transpose(1, 2, 0)[:h, :w], [cv2.IMWRITE_EXR_TYPE, cv2.IMWRITE_EXR_TYPE_HALF])
@@ -113,5 +116,6 @@ import warnings
             save_path = 'output/img{}.png'.format(i)
             success = cv2.imwrite(save_path, (img_list[i][0] * 255).byte().cpu().numpy().transpose(1, 2, 0)[:h, :w])
             print(f"Saving to {save_path} → success: {success}")
-
+            
+    print("Checkpoint reached!")