Update inference_img.py

inference_img.py

@@ -28,13 +28,13 @@ try:
     model = Model()
     model.load_model(args.modelDir, -1)
     print("Loaded RIFE_HDv3 model.")
-    print("Checkpoint reached!")
+    print("Checkpoint reached RIFE!")
 except:
     from train_log.IFNet_HDv3 import Model
     model = Model()
     model.load_model(args.modelDir, -1)
     print("Loaded IFNet_HDv3 model.")
-    print("Checkpoint reached!")
+    print("Checkpoint reached IFNet!")
 
 model.eval()
 model.device()
@@ -95,7 +95,7 @@ else:
 if not os.path.exists('output'):
     os.mkdir('output')
 
-print("Checkpoint reached!")
+print("Checkpoint reached! output folder ok")
 
 for i in range(len(img_list)):
     if args.img[0].endswith('.exr') and args.img[1].endswith('.exr'):
@@ -103,10 +103,14 @@ for i in range(len(img_list)):
         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("Saving to:", os.path.abspath(save_path))
+
     else:
         cv2.imwrite('output/img{}.png'.format(i), (img_list[i][0] * 255).byte().cpu().numpy().transpose(1, 2, 0)[:h, :w])
         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("Saving to:", os.path.abspath(save_path))
+
 
 print("Checkpoint reached!")