Delete unnecessary type hints

app/app.py

@@ -18,19 +18,19 @@ def describe_service():
 
 
 @st.experimental_memo
-def call_model(uploaded_file):
+def call_model(uploaded_file: io.BytesIO) -> Image.Image:
     return model.run_model(uploaded_file, st.session_state["model"])
 
 
 def process_image():
-    uploaded_file: io.BytesIO = st.file_uploader(
+    uploaded_file = st.file_uploader(
         label="Choose a file (you can upload new files without refreshing the page)",
         type=["png", "jpg", "jpeg"],
     )
     if uploaded_file:
-        placeholder: st.delta_generator.DeltaGenerator = st.empty()
+        placeholder = st.empty()
         placeholder.info("The image is being processed. It may take some time. Wait, please...")
-        image: Image.Image = call_model(uploaded_file)
+        image = call_model(uploaded_file)
         placeholder.empty()
         placeholder.image(image)
         with open("user_data/output.jpg", "rb") as file:

app/model.py

@@ -11,24 +11,22 @@ def create_model() -> keras.Model:
 
 
 def run_model(image_bytes: io.BytesIO, model: keras.Model) -> Image.Image:
-    image1: Image.Image = Image.open(image_bytes)
-    width: int
-    height: int
-    width, height = image1.size
-    image2: Image.Image = image1.resize((960, 640))
-    image_array1: np.ndarray = keras.utils.img_to_array(image2)
-    image_array2: np.ndarray = image_array1.astype("float32") / 255.0
-    image_array3: np.ndarray = np.expand_dims(image_array2, axis=0)
-    output: np.ndarray = model.predict(image_array3)
-    output_image_array1: np.ndarray = output[0] * 255.0
-    output_image_array2: np.ndarray = output_image_array1.clip(0, 255)
-    output_image_array3: np.ndarray = output_image_array2.reshape(
-        (np.shape(output_image_array2)[0], np.shape(output_image_array2)[1], 3)
+    image = Image.open(image_bytes)
+    width, height = image.size
+    image = image.resize((960, 640))
+    image_array = keras.utils.img_to_array(image)
+    image_array = image_array.astype("float32") / 255.0
+    image_array = np.expand_dims(image_array, axis=0)
+    output = model.predict(image_array)
+    output_image_array = output[0] * 255.0
+    output_image_array = output_image_array.clip(0, 255)
+    output_image_array = output_image_array.reshape(
+        (np.shape(output_image_array)[0], np.shape(output_image_array)[1], 3)
     )
-    output_image_array5: np.ndarray = output_image_array3.astype(np.uint8)
-    output_image1: Image.Image = Image.fromarray(output_image_array5)
-    output_image2: Image.Image = output_image1.resize((width, height))
+    output_image_array = output_image_array.astype(np.uint8)
+    output_image = Image.fromarray(output_image_array)
+    output_image = output_image.resize((width, height))
     if not os.path.exists("user_data"):
         os.makedirs("user_data")
-    output_image2.save("user_data/output.jpg")
-    return output_image2
+    output_image.save("user_data/output.jpg")
+    return output_image

test/test_model.py

@@ -1,27 +1,21 @@
 from PIL import Image
-from tensorflow import keras
 import io
 import os
 from ..app import model
 
-model_instance: keras.Model = model.create_model()
+model_instance = model.create_model()
 
 
-def template(filename: str) -> tuple[int, int, Image.Image]:
-    image: Image.Image = Image.open(filename)
-    width: int
-    height: int
+def template(filename: str):
+    image = Image.open(filename)
     width, height = image.size
-    image_bytes: io.BytesIO = io.BytesIO()
+    image_bytes = io.BytesIO()
     image.save(image_bytes, format=image.format)
-    output_image: Image.Image = model.run_model(image_bytes, model_instance)
+    output_image = model.run_model(image_bytes, model_instance)
     return width, height, output_image
 
 
 def test_image_jpg():
-    width: int
-    height: int
-    output_image: Image.Image
     width, height, output_image = template(os.path.join(os.getcwd(), "test/test_images/test1.jpg"))
 
     assert width == output_image.size[0]
@@ -29,9 +23,6 @@ def test_image_jpg():
 
 
 def test_image_png():
-    width: int
-    height: int
-    output_image: Image.Image
     width, height, output_image = template(os.path.join(os.getcwd(), "test/test_images/test2.png"))
 
     assert width == output_image.size[0]
@@ -39,9 +30,6 @@ def test_image_png():
 
 
 def test_image_jpeg():
-    width: int
-    height: int
-    output_image: Image.Image
     width, height, output_image = template(os.path.join(os.getcwd(), "test/test_images/test3.jpeg"))
 
     assert width == output_image.size[0]