updated roboflow model to improve accuracy

app.py

@@ -39,7 +39,7 @@ from PIL import Image
 import os
 from sklearn.model_selection import train_test_split
 from sklearn.preprocessing import MinMaxScaler
-from inference_sdk import InferenceHTTPClient
+from inference_sdk import InferenceHTTPClient, InferenceConfiguration
 
 # Initialize Flask app
 app = Flask(__name__)
@@ -264,7 +264,11 @@ def fetchImage():
     print(file_name)
 
     # Set confidence threshold to 50%
-    result = CLIENT.infer(file_name, model_id="car-damage-detection-krsix/1")
+    custom_configuration = InferenceConfiguration(confidence_threshold=0.8)
+    with CLIENT.use_configuration(custom_configuration):
+        result = CLIENT.infer(
+            file_name, model_id="car-damage-detection-krsix/1")
+    print(result)
     threshold = 0.3  # Adjust this as needed
     filtered_labels = [item["class"]
                        for item in result["predictions"] if item["confidence"] >= threshold]