Update TFliteDemo constructor parameters and model.tflite file

app.py

@@ -69,7 +69,7 @@ def load_dict(dict_path='label.names'):
 
 
 class TFliteDemo:
-    def __init__(self, model_path, blank=68, conf_mode="mean"):
+    def __init__(self, model_path, blank=0, conf_mode="min"):
         self.blank = blank
         self.conf_mode = conf_mode
         self.interpreter = tf.lite.Interpreter(model_path=model_path)
@@ -91,14 +91,15 @@ class TFliteDemo:
                 raise ValueError('img is None')
             image = img.copy()
         image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
-        image = center_fit(image, 128, 64, top_left=True)
-        image = np.reshape(image, (1, *image.shape, 1)).astype(np.uint8)
+        image = center_fit(image, 192, 96, top_left=True)
+        image = np.reshape(image, (1, *image.shape, 1)).astype(np.float32) / 255.0
         return image
 
     def get_confidence(self, pred, mode="mean"):
         _argmax = np.argmax(pred, axis=-1)
         _idx = _argmax != pred.shape[-1] - 1
-        conf = pred[_idx, _argmax[_idx]] / 255.0
+        conf = pred[_idx, _argmax[_idx]]
+        conf = np.exp(conf)
         return np.min(conf) if mode == "min" else np.mean(conf)
 
     def postprocess(self, pred):
@@ -125,7 +126,7 @@ if __name__ == '__main__':
     </div>
     '''
     # init model
-    demo = TFliteDemo(os.path.join(os.path.dirname(__file__), 'model.tflite'))
+    demo = TFliteDemo(os.path.join(os.path.dirname(__file__), 'f32_ctr_later_s2.tflite'))
     interface = gr.Interface(
         fn=inference,
         inputs="image",

model.tflite → f32_ctr_later_s2.tflite

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:36adbb170eb545434a5b9216c05f20c311a8357955208b75216928e1bfc38c24
-size 82744
+oid sha256:881ba76cb7ae1c74736f61daea24c61f98b6ef23e147e4eefab32e00e5340d08
+size 89392

label.names

@@ -1,4 +1,4 @@
-0
+
 1
 2
 3
@@ -8,6 +8,7 @@
 7
 8
 9
+0
 가
 나
 다
@@ -64,5 +65,4 @@
 전남
 경북
 경남
-제주
- 
+제주