Update README.md

README.md

@@ -18,6 +18,18 @@ This model is designed to classify grapevine leaves as either "healthy" or affec
 - **Model Architecture**: Convolutional Neural Network (CNN)
 - **Input**: Images of grape leaves
 - **Output**: Binary classification indicating whether the leaf is healthy or affected by Esca
+- **focal_loss function**: 
+```
+def focal_loss(gamma=2., alpha=0.25):
+    def focal_loss_fixed(y_true, y_pred):
+        y_true = tf.cast(y_true, tf.float32)
+        y_pred = tf.clip_by_value(y_pred, tf.keras.backend.epsilon(), 1 - tf.keras.backend.epsilon())
+        alpha_t = y_true * alpha + (tf.ones_like(y_true) - y_true) * (1 - alpha)
+        p_t = y_true * y_pred + (tf.ones_like(y_true) - y_true) * (tf.ones_like(y_true) - y_pred)
+        focal_loss_value = -alpha_t * tf.math.pow((tf.ones_like(y_true) - p_t), gamma) * tf.math.log(p_t)
+        return tf.reduce_mean(focal_loss_value)
+    return focal_loss_fixed
+```
 
 ## Dataset