added confidence .40 for detection

QA_bot.py

@@ -43,8 +43,9 @@ def tyre_synap_bot(filter_agent,image_file_path):
         with st.chat_message("assistant"):
             message_placeholder = st.empty()
             full_response = ""
-            if ('Segmentation image' in ai_response['output']) or ('predicted_image' in ai_response['output']):
+            if os.path.isfile('final_mask.png'):
                 display_mask_image('final_mask.png')
+            # if ('Segmentation image' in ai_response['output']) or ('Predicted_image' in ai_response['output']):
             
             for chunk in re.split(r'(\s+)', response):
                 full_response += chunk + " "

tool_utils/yolo_world.py

@@ -69,7 +69,7 @@ class YoloWorld:
         scores = []
 
         self.model.set_classes(object_prompts)
-        results = self.model.predict(image_path)
+        results = self.model.predict(image_path,conf=0.40)
         for result in results:
             for i,box in enumerate(result.boxes):
                 x1, y1, x2, y2 = np.array(box.xyxy.cpu(), dtype=np.int32).squeeze()
@@ -91,7 +91,7 @@ class YoloWorld:
         predicted_data = self.format_detections(bounding_boxes,labels)
         # save image 
         cv2.imwrite('final_mask.png', cv2.cvtColor(detected_image,cv2.COLOR_BGR2RGB))
-        return "Predicted image : final_mask.png . \nDetails :\n{}".format(predicted_data)
+        return "Predicted image : final_mask.png .\nDetails :\n{}".format(predicted_data)
                 
 if __name__ == "__main__":
     yolo = YoloWorld()