Use global variable for top k

app.py

@@ -34,6 +34,8 @@ height, width = patch_size * patch_height_nums, patch_size * patch_width_nums
 # DINOV2
 model = torch.hub.load(DINOV2_REPO, DINOV2_MODEL)
 
+# faiss
+K= 5
 
 def read_image(image_path: str) -> np.ndarray:
     image = cv2.imread(image_path, cv2.IMREAD_COLOR)
@@ -104,8 +106,7 @@ def instance_recognition(
     image_embedding = infer(image)
 
     # search
-    k = 5
-    distances, indices = index.search(image_embedding, k)
+    distances, indices = index.search(image_embedding, K)
 
     res = []
     for i in indices[0]:
@@ -134,10 +135,10 @@ with gr.Blocks() as demo:
 
         with gr.Row():
             output_images = [
-                gr.Image(label=f"Similar {i + 1}") for i in range(5)
+                gr.Image(label=f"Similar {i + 1}") for i in range(K)
             ]
             distances = [
-                gr.Text(label=f"Similar {i + 1} Distances") for i in range(5)
+                gr.Text(label=f"Similar {i + 1} Distances") for i in range(K)
             ]
 
         infer_btn.click(