Update app.py

app.py

@@ -8,7 +8,7 @@ DECODE_DICT = {i:char for i, char in enumerate(CHARS)}
 
 interpreter = tf.lite.Interpreter(model_path='detection.tflite')
 interpreter.allocate_tensors()
-recog_interpreter = tf.lite.Interpreter(model_path='recognition2.tflite')
+recog_interpreter = tf.lite.Interpreter(model_path='recognition.tflite')
 recog_input_details = recog_interpreter.get_input_details()
 recog_output_details = recog_interpreter.get_output_details()
 recog_interpreter.resize_tensor_input(recog_input_details[0]['index'], (1, 24, 94, 3))
@@ -62,7 +62,7 @@ def greet(image):
     text = None
     # For index and confidence value of the first class [0]
     for i, confidence in enumerate(output_data[0]):
-        if confidence > .3:
+        if confidence > .1:
             text, crop = execute_text_recognition_tflite(
                 boxes[0][i], image,
                 recog_interpreter, recog_input_details, recog_output_details,