Update app.py

app.py

@@ -28,16 +28,13 @@ def yolov8_img_inference(
 ):
     model = YOLO(model_path)
     model.conf = conf_threshold
-    model.iou= iou_threshold
-    # model.overrides['agnostic_nms'] = False  # NMS class-agnostic
-    # model.overrides['max_det'] = 1000 
-    # image = read_image(image)
-    results = model.predict(image, imgz=image_size, return_outputs=True)
+    model.iou = iou_threshold
+    results = model.predict(image, imgsz=image_size, return_outputs=True)
     object_prediction_list = []
     for _, image_results in enumerate(results):
         if len(image_results)!=0:
-            image_prediction_in_xyxy_format = image_results['det']
-            for pred in image_prediction_in_xyxy_format:
+            image_predictions_in_xyxy_format = image_results['det']
+            for pred in image_predictions_in_xyxy_format:
                 x1, y1, x2, y2 = (
                     int(pred[0]),
                     int(pred[1]),
@@ -55,9 +52,11 @@ def yolov8_img_inference(
                     category_name=category_name,
                 )
                 object_prediction_list.append(object_prediction)
+
     image = read_image(image)
     output_image = visualize_object_predictions(image=image, object_prediction_list=object_prediction_list)
     return output_image['image']
+        
 
 inputs_image = [
     gr.inputs.Image(type="filepath", label="Input Image"),