fix

app.py

@@ -12,6 +12,7 @@ print(f'TensorFlow {tf.__version__}')
 
 print(f'Load classifier from {config.classifier_path}')
 classifier = load_classifier(config)
+classifier.summary()
 
 print('Load detector.')
 detector = load_detector(config)

inference.py

@@ -26,8 +26,8 @@ def classify_action(classifier, frames, id_to_name):
   actions = []
   frames = np.array(frames)
   frames = tf.expand_dims(frames, 0)
-  output = classifier(frames)
-  confidences = tf.nn.softmax(output).numpy()[0]
+  y = classifier(frames)
+  confidences = tf.squeeze(y).numpy()
   for (class_id, confidence) in enumerate(confidences):
     other_class_id = 2
     if confidence > 0.3 and class_id != other_class_id:

model.py

@@ -31,10 +31,10 @@ def build_movinet(output_size, config: Config):
   return model
 
 def build_classifier_head(input_size, config: Config):
-  inputs = keras.Input(shape=(input_size,))
-  classifier = AttentionDenseClassifierHead(2, config.num_classes)(inputs)
-  model = keras.Model(inputs=inputs, outputs=classifier)
-  return model
+  # inputs = keras.Input(shape=(input_size,))
+  # classifier = AttentionDenseClassifierHead(2, config.num_classes)(inputs)
+  # model = keras.Model(inputs=inputs, outputs=classifier)
+  return keras.layers.Dense(config.num_classes, activation='softmax')
 
 def build_model(movinet, classifier_head):
   return keras.models.Sequential([movinet, classifier_head])