Upload utils.py

utils.py

@@ -0,0 +1,36 @@
+import tensorflow as tf
+from tensorflow.keras import layers
+import cv2
+import numpy as np
+
+def create_model():
+    baseModel =  tf.keras.applications.efficientnet.EfficientNetB0(include_top=False, weights='imagenet')
+    baseModel.trainable = False
+
+    inputs = layers.Input(shape=(224, 224, 3), name="input_layer")
+
+    x = baseModel(inputs)
+    x = layers.AveragePooling2D()(x)
+    x = layers.Flatten(name='Flatten')(x)
+    x = layers.Dense(units=128, activation='relu')(x)
+    x = layers.Dropout(rate=0.5)(x)
+    outputs = layers.Dense(units=1, activation='sigmoid')(x)
+
+    model = tf.keras.Model(inputs, outputs)
+    
+    initial_learning_rate = 0.001
+
+    model.compile(loss='binary_crossentropy',
+                  optimizer=tf.keras.optimizers.Adam(learning_rate=initial_learning_rate),
+                  metrics = ['AUC'])
+    
+    return model
+
+def get_optimal_font_scale(text, width):
+    for scale in np.arange(1,0.1,-0.2):
+        scale = round(scale,2)
+        textSize = cv2.getTextSize(text, fontFace=cv2.FONT_HERSHEY_SIMPLEX, fontScale=scale, thickness=1)
+        new_width = textSize[0][0]
+        if (new_width <= width):
+            return scale
+    return 0.1