update app.py and add resnet50 model

app.py

@@ -9,7 +9,8 @@ import keras
 from keras import Sequential
 from keras.layers import Flatten, Dense
 
-model_weights_path = (Path.cwd() / "pace_model_weights.h5").resolve()
+pace_model_weights_path = (Path.cwd() / "models" / "pace_model_weights.h5").resolve()
+resnet50_tf_model_weights_path = (Path.cwd() / "models" / "resnet50_weights_tf_dim_ordering_tf_kernels_notop.h5")
 height, width, channels = (224, 224, 3)
 
 class PaceModel:
@@ -20,29 +21,30 @@ class PaceModel:
         self.channels = channels
         self.class_names = ["Fast", "Medium", "Slow"]
 
-        self.create_pretrained()
+        self.create_base_model()
         self.create_architecture()
     
-    def create_pretrained(self):
-        self.pretrained_model = tf.keras.applications.ResNet50(
+    def create_base_model(self):
+        self.base_model = tf.keras.applications.ResNet50(
             include_top=False,
             input_shape=(self.height, self.width, self.channels),
             pooling="avg",
             classes=211,
             weights="imagenet"
         )
+        self.base_model.load_weights(resnet50_tf_model_weights_path)
 
-        for layer in self.pretrained_model.layers:
+        for layer in self.base_model.layers:
             layer.trainable = False
     
     def create_architecture(self):
-        self.resnet_model.add(self.pretrained_model)
+        self.resnet_model.add(self.base_model)
         self.resnet_model.add(Flatten())
         self.resnet_model.add(Dense(1024, activation="relu"))
         self.resnet_model.add(Dense(256, activation="relu"))
         self.resnet_model.add(Dense(3, activation="softmax"))
 
-        self.resnet_model.load_weights(model_weights_path)
+        self.resnet_model.load_weights(pace_model_weights_path)
             
     def predict(self, input_image: np.ndarray):
         resized_image = cv2.resize(input_image, (self.height, self.width))

models/resnet50_weights_tf_dim_ordering_tf_kernels_notop.h5

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:66c8b43daff3fcc15bc4f30e3d2a167e21a14d9c9598a5394e5516471f4af504
+size 94765736