Added more Models

app.py

@@ -45,6 +45,9 @@ MODELS = {
     "Pelvis X-ray Detection (YOLO11m)": YOLO("https://huggingface.co/mbar0075/YOLO-Application-Toolkit/resolve/main/yolo11m_pelvis_xray.pt"),
     "Road Signs Detection (YOLO11m)": YOLO("https://huggingface.co/mbar0075/YOLO-Application-Toolkit/resolve/main/yolo11m_road_signs.pt"),
     "Pizza Toppings Detection (YOLO11m)": YOLO("https://huggingface.co/mbar0075/YOLO-Application-Toolkit/resolve/main/yolo11m_pizza.pt"),
+    "Pelvis X-ray Segmentation (YOLO11s)": YOLO("https://huggingface.co/mbar0075/YOLO-Application-Toolkit/resolve/main/yolo11s_seg_pelvis_xray.pt"),
+    "Teeth X-ray Segmentation (YOLO11s)": YOLO("https://huggingface.co/mbar0075/YOLO-Application-Toolkit/resolve/main/yolo11s_seg_teeth_xray.pt"),
+    "Football Players Detection (YOLO11s)": YOLO("https://huggingface.co/mbar0075/YOLO-Application-Toolkit/resolve/main/yolo11s_football_players.pt"),
 }
 
 
@@ -65,6 +68,9 @@ EXAMPLE_DICT = {
     "Pelvis X-ray Detection (YOLO11m)": example_dir + "12.jpg",
     "Road Signs Detection (YOLO11m)": example_dir + "13.jpg",
     "Pizza Toppings Detection (YOLO11m)": example_dir + "10.jpg",
+    "Pelvis X-ray Segmentation (YOLO11s)": example_dir + "12.jpg",
+    "Teeth X-ray Segmentation (YOLO11s)": example_dir + "14.jpg",
+    "Football Players Detection (YOLO11s)": example_dir + "15.jpg",
 }
 
 LABEL_ANNOTATORS = sv.LabelAnnotator()
@@ -112,7 +118,7 @@ yolo_11s_confidence_threshold_component = gr.Slider(
     maximum=1.0,
     value=0.3,
     step=0.01,
-    label="YOLO11m Confidence Threshold",
+    label="YOLO Confidence Threshold",
     info=(
         "The confidence threshold for the YOLO model. Lower the threshold to "
         "reduce false negatives, enhancing the model's sensitivity to detect "
@@ -161,7 +167,7 @@ with gr.Blocks() as demo:
 
     with gr.Row():
         image_input_component = gr.Image(type='pil', label='Input Image')
-        yolo_11s_output_component = gr.Image(type='pil', label='YOLO11m Output')
+        yolo_11s_output_component = gr.Image(type='pil', label='YOLO Output')
 
     submit_button = gr.Button(value='Submit', scale=1, variant='primary')