refactoring

src/app.py

@@ -10,10 +10,69 @@ from visuals import (
     show_docstring,
 )
 
-# TODO: refactor all the new code of professional mode
+
+def get_placeholder_params(image):
+    return {
+        "image_width": image.shape[1],
+        "image_height": image.shape[0],
+        "image_half_width": int(image.shape[1] / 2),
+        "image_half_height": int(image.shape[0] / 2),
+    }
+
+
+def select_transformations(augmentations: dict, interface_type: str) -> list:
+    # in the Simple mode you can choose only one transform
+    if interface_type == "Simple":
+        transform_names = [
+            st.sidebar.selectbox(
+                "Select a transformation:", sorted(list(augmentations.keys()))
+            )
+        ]
+    # in the professional mode you can choose several transforms
+    elif interface_type == "Professional":
+        transform_names = [
+            st.sidebar.selectbox(
+                "Select transformation №1:", sorted(list(augmentations.keys()))
+            )
+        ]
+        while transform_names[-1] != "None":
+            transform_names.append(
+                st.sidebar.selectbox(
+                    f"Select transformation №{len(transform_names) + 1}:",
+                    ["None"] + sorted(list(augmentations.keys())),
+                )
+            )
+        transform_names = transform_names[:-1]
+    return transform_names
+
+
+def get_transormations_params(transform_names: list) -> list:
+    transforms = []
+    for i, transform_name in enumerate(transform_names):
+        # select the params values
+        st.sidebar.subheader("Params of the " + transform_name)
+        param_values = show_transform_control(augmentations[transform_name], i)
+        transforms.append(getattr(A, transform_name)(**param_values))
+    return transforms
+
+
+def show_random_params(data: dict, interface_type: str = "Professional"):
+    """Shows random params used for transformation (from A.ReplayCompose)"""
+    if interface_type == "Professional":
+        st.subheader("Random params used")
+        random_values = {}
+        for applied_params in data["replay"]["transforms"]:
+            random_values[
+                applied_params["__class_fullname__"].split(".")[-1]
+            ] = applied_params["params"]
+        st.write(random_values)
+
+
+# TODO: refactor all the new code
 
 # get CLI params: the path to images and image width
 path_to_images, width_original = get_arguments()
+
 if not os.path.isdir(path_to_images):
     st.title("There is no directory: " + path_to_images)
 else:
@@ -24,52 +83,24 @@ else:
 
     # select image
     status, image = select_image(path_to_images, interface_type)
-    if status == 0:
+    if status == 1:
         st.title("Can't load image")
     if status == 2:
         st.title("Please, upload the image")
     else:
-        placeholder_params = {
-            "image_width": image.shape[1],
-            "image_height": image.shape[0],
-            "image_half_width": int(image.shape[1] / 2),
-            "image_half_height": int(image.shape[0] / 2),
-        }
+        # image was loaded successfully
+        placeholder_params = get_placeholder_params(image)
 
         # load the config
         augmentations = load_augmentations_config(
             placeholder_params, "configs/augmentations.json"
         )
 
-        # select a transformation
-        if interface_type == "Simple":
-            transform_names = [
-                st.sidebar.selectbox(
-                    "Select a transformation:", sorted(list(augmentations.keys()))
-                )
-            ]
-        # in the professional mode you can choose several transforms
-        elif interface_type == "Professional":
-            transform_names = [
-                st.sidebar.selectbox(
-                    "Select transformation №1:", sorted(list(augmentations.keys()))
-                )
-            ]
-            while transform_names[-1] != "None":
-                transform_names.append(
-                    st.sidebar.selectbox(
-                        f"Select transformation №{len(transform_names) + 1}:",
-                        ["None"] + sorted(list(augmentations.keys())),
-                    )
-                )
-            transform_names = transform_names[:-1]
+        # get list of transformations names
+        transform_names = select_transformations(augmentations, interface_type)
 
-        transforms = []
-        for i, transform_name in enumerate(transform_names):
-            # select the params values
-            st.sidebar.subheader("Params of the " + transform_name)
-            param_values = show_transform_control(augmentations[transform_name], i)
-            transforms.append(getattr(A, transform_name)(**param_values))
+        # get parameters for each transform
+        transforms = get_transormations_params(transform_names)
 
         try:
             # apply the transformation to the image
@@ -82,6 +113,7 @@ else:
             Check transforms that change the shape of image."
             )
 
+        # proced only if everything is ok
         if error == 0:
             augmented_image = data["image"]
             # show title
@@ -98,14 +130,7 @@ else:
             )
 
             # random values used to get transformations
-            if interface_type == "Professional":
-                st.subheader("Random params used")
-                random_values = {}
-                for applied_params in data["replay"]["transforms"]:
-                    random_values[
-                        applied_params["__class_fullname__"].split(".")[-1]
-                    ] = applied_params["params"]
-                st.write(random_values)
+            show_random_params(data, interface_type)
 
             # print additional info
             for transform in transforms:

src/visuals.py

@@ -10,9 +10,20 @@ def show_logo():
 
 
 def select_image(path_to_images: str, interface_type: str = "Simple"):
+    """ Show interface to choose the image, and load it
+    Args:
+        path_to_images (dict): path ot folder with images
+        interface_type (dict): mode of the interface used
+    Returns:
+        (status, image)
+        status (int):
+            0 - if everything is ok
+            1 - if there is error during loading of image file
+            2 - if user hasn't uploaded photo yet
+    """
     image_names_list = get_images_list(path_to_images)
     if len(image_names_list) < 1:
-        return 0, 0
+        return 1, 0
     else:
         if interface_type == "Professional":
             image_name = st.sidebar.selectbox(
@@ -26,13 +37,13 @@ def select_image(path_to_images: str, interface_type: str = "Simple"):
                 image = load_image(image_name, path_to_images)
                 return 1, image
             except cv2.error:
-                return 0, 0
+                return 1, 0
         else:
             try:
                 image = upload_image()
-                return 1, image
+                return 0, image
             except cv2.error:
-                return 0, 0
+                return 1, 0
             except AttributeError:
                 return 2, 0