allow to set different confidence thresholds per model

app.py

@@ -52,9 +52,9 @@ Powered by Roboflow [Inference](https://github.com/roboflow/inference) and
 """
 
 IMAGE_EXAMPLES = [
-    ['https://media.roboflow.com/supervision/image-examples/people-walking.png', 0.4],
-    ['https://media.roboflow.com/supervision/image-examples/vehicles.png', 0.4],
-    ['https://media.roboflow.com/supervision/image-examples/basketball-1.png', 0.4],
+    ['https://media.roboflow.com/supervision/image-examples/people-walking.png', 0.3, 0.3, 0.1],
+    ['https://media.roboflow.com/supervision/image-examples/vehicles.png', 0.3, 0.3, 0.1],
+    ['https://media.roboflow.com/supervision/image-examples/basketball-1.png', 0.3, 0.3, 0.1],
 ]
 
 YOLO_V8_MODEL = get_model(model_id="coco/8")
@@ -102,15 +102,17 @@ def detect_and_annotate(
 
 def process_image(
     input_image: np.ndarray,
-    confidence_threshold: float,
+    yolo_v8_confidence_threshold: float,
+    yolo_v9_confidence_threshold: float,
+    yolo_v10_confidence_threshold: float,
     iou_threshold: float
 ) -> Tuple[np.ndarray, np.ndarray, np.ndarray]:
     yolo_v8_annotated_image = detect_and_annotate(
-        YOLO_V8_MODEL, input_image, confidence_threshold, iou_threshold)
+        YOLO_V8_MODEL, input_image, yolo_v8_confidence_threshold, iou_threshold)
     yolo_v9_annotated_image = detect_and_annotate(
-        YOLO_V9_MODEL, input_image, confidence_threshold, iou_threshold)
+        YOLO_V9_MODEL, input_image, yolo_v9_confidence_threshold, iou_threshold)
     yolo_10_annotated_image = detect_and_annotate(
-        YOLO_V10_MODEL, input_image, confidence_threshold, iou_threshold)
+        YOLO_V10_MODEL, input_image, yolo_v10_confidence_threshold, iou_threshold)
 
     return (
         yolo_v8_annotated_image,
@@ -119,12 +121,38 @@ def process_image(
     )
 
 
-confidence_threshold_component = gr.Slider(
+yolo_v8_confidence_threshold_component = gr.Slider(
+    minimum=0,
+    maximum=1.0,
+    value=0.3,
+    step=0.01,
+    label="YOLOv8 Confidence Threshold",
+    info=(
+        "The confidence threshold for the YOLO model. Lower the threshold to "
+        "reduce false negatives, enhancing the model's sensitivity to detect "
+        "sought-after objects. Conversely, increase the threshold to minimize false "
+        "positives, preventing the model from identifying objects it shouldn't."
+    ))
+
+yolo_v9_confidence_threshold_component = gr.Slider(
+    minimum=0,
+    maximum=1.0,
+    value=0.3,
+    step=0.01,
+    label="YOLOv9 Confidence Threshold",
+    info=(
+        "The confidence threshold for the YOLO model. Lower the threshold to "
+        "reduce false negatives, enhancing the model's sensitivity to detect "
+        "sought-after objects. Conversely, increase the threshold to minimize false "
+        "positives, preventing the model from identifying objects it shouldn't."
+    ))
+
+yolo_v10_confidence_threshold_component = gr.Slider(
     minimum=0,
     maximum=1.0,
     value=0.3,
     step=0.01,
-    label="Confidence Threshold",
+    label="YOLOv10 Confidence Threshold",
     info=(
         "The confidence threshold for the YOLO model. Lower the threshold to "
         "reduce false negatives, enhancing the model's sensitivity to detect "
@@ -150,7 +178,10 @@ iou_threshold_component = gr.Slider(
 with gr.Blocks() as demo:
     gr.Markdown(MARKDOWN)
     with gr.Accordion("Configuration", open=False):
-        confidence_threshold_component.render()
+        with gr.Row():
+            yolo_v8_confidence_threshold_component.render()
+            yolo_v9_confidence_threshold_component.render()
+            yolo_v10_confidence_threshold_component.render()
         iou_threshold_component.render()
     with gr.Row():
         input_image_component = gr.Image(
@@ -180,7 +211,9 @@ with gr.Blocks() as demo:
         examples=IMAGE_EXAMPLES,
         inputs=[
             input_image_component,
-            confidence_threshold_component,
+            yolo_v8_confidence_threshold_component,
+            yolo_v9_confidence_threshold_component,
+            yolo_v10_confidence_threshold_component,
             iou_threshold_component
         ],
         outputs=[
@@ -194,7 +227,9 @@ with gr.Blocks() as demo:
         fn=process_image,
         inputs=[
             input_image_component,
-            confidence_threshold_component,
+            yolo_v8_confidence_threshold_component,
+            yolo_v9_confidence_threshold_component,
+            yolo_v10_confidence_threshold_component,
             iou_threshold_component
         ],
         outputs=[