Show runtime counter in logs.

app.py

@@ -20,7 +20,8 @@ from io import BytesIO
 torch.set_float32_matmul_precision('high')
 torch.jit.script = lambda f: f
 
-device = "cuda" if torch.cuda.is_available() else "cpu"
+device = "cuda" if torch.cuda.is_available() else "CPU"
+counter_runtime = 0
 
 
 def array_to_pil_image(image: np.ndarray, size: Tuple[int, int] = (1024, 1024)) -> Image.Image:
@@ -67,7 +68,8 @@ def predict(image, resolution, weights_file):
     global birefnet
     # Load BiRefNet with chosen weights
     _weights_file = '/'.join(('zhengpeng7', usage_to_weights_file[weights_file] if weights_file is not None else usage_to_weights_file['General']))
-    print('Using weights:', _weights_file)
+    counter_runtime += 1
+    print('Using weights: {} in runtime {}'.format(_weights_file, counter_runtime))
     birefnet = AutoModelForImageSegmentation.from_pretrained(_weights_file, trust_remote_code=True)
     birefnet.to(device)
     birefnet.eval()