added dce-net

enhance_me/zero_dce/models/dce_net.py

@@ -0,0 +1,31 @@
+import tensorflow as tf
+from tensorflow.keras import layers, Input, Model
+
+
+def build_dce_net() -> Model:
+    input_image = Input(shape=[None, None, 3])
+    conv1 = layers.Conv2D(
+        32, (3, 3), strides=(1, 1), activation="relu", padding="same"
+    )(input_image)
+    conv2 = layers.Conv2D(
+        32, (3, 3), strides=(1, 1), activation="relu", padding="same"
+    )(conv1)
+    conv3 = layers.Conv2D(
+        32, (3, 3), strides=(1, 1), activation="relu", padding="same"
+    )(conv2)
+    conv4 = layers.Conv2D(
+        32, (3, 3), strides=(1, 1), activation="relu", padding="same"
+    )(conv3)
+    int_con1 = layers.Concatenate(axis=-1)([conv4, conv3])
+    conv5 = layers.Conv2D(
+        32, (3, 3), strides=(1, 1), activation="relu", padding="same"
+    )(int_con1)
+    int_con2 = layers.Concatenate(axis=-1)([conv5, conv2])
+    conv6 = layers.Conv2D(
+        32, (3, 3), strides=(1, 1), activation="relu", padding="same"
+    )(int_con2)
+    int_con3 = layers.Concatenate(axis=-1)([conv6, conv1])
+    x_r = layers.Conv2D(24, (3, 3), strides=(1, 1), activation="tanh", padding="same")(
+        int_con3
+    )
+    return Model(inputs=input_image, outputs=x_r)