YOLO-ARENA with YOLOv10

app.py

@@ -8,37 +8,27 @@ from inference import get_model
 MARKDOWN = """
 <h1 style='text-align: center'>YOLO-ARENA 🏟️</h1>
 
-Welcome to YOLO-Arena! This demo showcases the performance of various YOLO models:
+Welcome to YOLO-Arena! This demo showcases the performance of various YOLO models 
+pre-trained on the COCO dataset.
 
 - YOLOv8 [[code](https://github.com/ultralytics/ultralytics)]
 - YOLOv9 [[code](https://github.com/WongKinYiu/yolov9)]
 - YOLOv10 [[code](https://github.com/THU-MIG/yolov10)]
-- YOLO-NAS [[code](https://github.com/Deci-AI/super-gradients/blob/master/YOLONAS.md)]
 
 Powered by Roboflow [Inference](https://github.com/roboflow/inference) and 
-[Supervision](https://github.com/roboflow/supervision).
+[Supervision](https://github.com/roboflow/supervision). 🔥
 """
 
 IMAGE_EXAMPLES = [
-    ['https://media.roboflow.com/dog.jpeg', 0.4]
+    ['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],
 ]
 
-YOLO_V8_MODEL = get_model(model_id="yolov8m-640")
-YOLO_NAS_MODEL = get_model(model_id="coco/15")
+YOLO_V8_MODEL = get_model(model_id="coco/8")
 YOLO_V9_MODEL = get_model(model_id="coco/17")
 YOLO_V10_MODEL = get_model(model_id="coco/22")
 
-YOLO_NAS_TO_COCO_CLASS_ID_MAPPING = {
-    49: 0, 9: 1, 18: 2, 44: 3, 0: 4, 16: 5, 73: 6, 74: 7, 11: 8, 72: 9, 31: 10, 63: 11,
-    48: 12, 8: 13, 10: 14, 20: 15, 28: 16, 37: 17, 56: 18, 25: 19, 30: 20, 6: 21,
-    79: 22, 34: 23, 2: 24, 76: 25, 36: 26, 68: 27, 64: 28, 33: 29, 59: 30, 60: 31,
-    62: 32, 40: 33, 4: 34, 5: 35, 58: 36, 65: 37, 67: 38, 13: 39, 78: 40, 26: 41,
-    32: 42, 41: 43, 61: 44, 14: 45, 3: 46, 1: 47, 54: 48, 46: 49, 15: 50, 19: 51,
-    38: 52, 50: 53, 29: 54, 17: 55, 22: 56, 24: 57, 51: 58, 7: 59, 27: 60, 70: 61,
-    75: 62, 42: 63, 45: 64, 53: 65, 39: 66, 21: 67, 43: 68, 47: 69, 69: 70, 57: 71,
-    52: 72, 12: 73, 23: 74, 77: 75, 55: 76, 66: 77, 35: 78, 71: 79
-}
-
 LABEL_ANNOTATORS = sv.LabelAnnotator(text_color=sv.Color.black())
 BOUNDING_BOX_ANNOTATORS = sv.BoundingBoxAnnotator()
 
@@ -82,15 +72,9 @@ def process_image(
     input_image: np.ndarray,
     confidence_threshold: float,
     iou_threshold: float
-) -> Tuple[np.ndarray, np.ndarray, np.ndarray, np.ndarray]:
+) -> Tuple[np.ndarray, np.ndarray, np.ndarray]:
     yolo_v8_annotated_image = detect_and_annotate(
         YOLO_V8_MODEL, input_image, confidence_threshold, iou_threshold)
-    yolo_nas_annotated_image = detect_and_annotate(
-        YOLO_NAS_MODEL,
-        input_image,
-        confidence_threshold,
-        iou_threshold,
-        YOLO_NAS_TO_COCO_CLASS_ID_MAPPING)
     yolo_v9_annotated_image = detect_and_annotate(
         YOLO_V9_MODEL, input_image, confidence_threshold, iou_threshold)
     yolo_10_annotated_image = detect_and_annotate(
@@ -98,7 +82,6 @@ def process_image(
 
     return (
         yolo_v8_annotated_image,
-        yolo_nas_annotated_image,
         yolo_v9_annotated_image,
         yolo_10_annotated_image
     )
@@ -142,25 +125,19 @@ with gr.Blocks() as demo:
             type='numpy',
             label='Input'
         )
-        with gr.Column():
-            with gr.Row():
-                yolo_v8_output_image_component = gr.Image(
-                    type='numpy',
-                    label='YOLOv8m @ 640x640'
-                )
-                yolo_nas_output_image_component = gr.Image(
-                    type='numpy',
-                    label='YOLO-NAS M @ 640x640'
-                )
-            with gr.Row():
-                yolo_v9_output_image_component = gr.Image(
-                    type='numpy',
-                    label='YOLOv9c @ 640x640'
-                )
-                yolo_v10_output_image_component = gr.Image(
-                    type='numpy',
-                    label='YOLOv10m @ 640x640'
-                )
+        yolo_v8_output_image_component = gr.Image(
+            type='numpy',
+            label='YOLOv8'
+        )
+    with gr.Row():
+        yolo_v9_output_image_component = gr.Image(
+            type='numpy',
+            label='YOLOv9'
+        )
+        yolo_v10_output_image_component = gr.Image(
+            type='numpy',
+            label='YOLOv10'
+            )
     submit_button_component = gr.Button(
         value='Submit',
         scale=1,
@@ -176,7 +153,6 @@ with gr.Blocks() as demo:
         ],
         outputs=[
             yolo_v8_output_image_component,
-            yolo_nas_output_image_component,
             yolo_v9_output_image_component,
             yolo_v10_output_image_component
         ]
@@ -191,7 +167,6 @@ with gr.Blocks() as demo:
         ],
         outputs=[
             yolo_v8_output_image_component,
-            yolo_nas_output_image_component,
             yolo_v9_output_image_component,
             yolo_v10_output_image_component
         ]