Update files

app.py

@@ -29,7 +29,7 @@ def get_model():
     detection_model = AutoDetectionModel.from_pretrained(
         model_type='yolov8',
         model_path=yolov8_model_path,
-        confidence_threshold=0.8,
+        confidence_threshold=postprocess_match_threshold,
         device="cpu",
     )
     return detection_model
@@ -152,8 +152,8 @@ if submit:
 
 st.write('##')
 
-col1, col2, col3 = st.columns([1, 3, 1])
-with col2:
+col1, col2, col3 = st.columns([3, 1, 1], gap='medium')
+with col1:
     st.markdown(f"#### Object Detection Result")
     with st.container(border = True):
         static_component = image_comparison(

utils.py

@@ -14,7 +14,6 @@ def sahi_yolov8m_inference(
     overlap_height_ratio,
     overlap_width_ratio,
     image_size,
-    postprocess_match_threshold,
 ):
     # sliced inference
     detection_model.image_size = image_size
@@ -25,7 +24,6 @@ def sahi_yolov8m_inference(
         slice_width=slice_width,
         overlap_height_ratio=overlap_height_ratio,
         overlap_width_ratio=overlap_width_ratio,
-        postprocess_match_threshold=postprocess_match_threshold,
     )
     visual_result = sahi.utils.cv.visualize_object_predictions(
         image=numpy.array(image),