Update app.py

app.py

@@ -19,7 +19,7 @@ To run the application:
 2. Run the script using the Streamlit command:
 ```bash
 streamlit run app.py
-```
+
 '''
 
 import streamlit as st
@@ -30,18 +30,44 @@ import io
 import os
 
 def zoom_at(img, x, y, zoom):
+    '''
+    Zoom into an image at a specific location.
+
+    Parameters:
+    ----------
+    img : PIL.Image
+        Input image.
+
+    x : int
+        X-coordinate of the zoom center.
+
+    y : int
+        Y-coordinate of the zoom center.
+
+    zoom : float
+        Zoom factor.
+
+    Returns:
+    -------
+    PIL.Image
+        Zoomed image.
+
+    Examples:
+    --------
+    >>> img = Image.open('image.jpg')
+    >>> zoomed_img = zoom_at(img, x=100, y=100, zoom=2.0)
+    '''
     w, h = img.size
     zoom2 = zoom * 2
     img = img.crop((x - w / zoom2, y - h / zoom2,
                     x + w / zoom2, y + h / zoom2))
     return img.resize((w, h), Image.LANCZOS)
 
-st.set_page_config(page_title="Cell Explorer", layout="wide")
-st.title("CLL Explorer - Annotate: Upload, Process, and Save Images")
+st.set_page_config(page_title="CLL Explorer", layout="wide")
+st.title("CLL Explorer - Malaria Cell Detection")
 
 st.markdown("""
 ### About This Application
-This tool assists researchers in analyzing microscope images of blood cells for malaria detection:
 - **Upload** microscope images.
 - **Adjust** image view with zoom and enhancement controls.
 - **Detect** and measure cells automatically.
@@ -51,78 +77,68 @@ This tool assists researchers in analyzing microscope images of blood cells for
 uploaded_files = st.file_uploader("Upload Images", accept_multiple_files=True, type=["jpg", "png"])
 
 if uploaded_files:
-    img_index = st.selectbox("Select Image", range(len(uploaded_files)), format_func=lambda x: uploaded_files[x].name)
+    img_index = st.selectbox(
+        "Select Image",
+        range(len(uploaded_files)),
+        format_func=lambda x: uploaded_files[x].name
+    )
     img_data = uploaded_files[img_index].read()
     img = Image.open(io.BytesIO(img_data)).resize((500, 500))
 
-    # Display the original image first
+    # Display Processed Image first
+    st.subheader("Processed Image")
+    x = st.slider("X Coordinate", 0, 500, 250)
+    y = st.slider("Y Coordinate", 0, 500, 250)
+    zoom = st.slider("Zoom", 1, 10, 5)
+
+    with st.expander("Enhancement Settings", expanded=True):
+        contrast = st.slider("Contrast", 0.0, 5.0, 1.0)
+        brightness = st.slider("Brightness", 0.0, 5.0, 1.0)
+        sharpness = st.slider("Sharpness", 0.0, 2.0, 1.0)
+
+    def apply_enhancements(image):
+        zoomed = zoom_at(image, x, y, zoom)
+        enhanced_contrast = ImageEnhance.Contrast(zoomed).enhance(contrast)
+        enhanced_bright = ImageEnhance.Brightness(enhanced_contrast).enhance(brightness)
+        enhanced_sharp = ImageEnhance.Sharpness(enhanced_bright).enhance(sharpness)
+        return enhanced_sharp
+
+    processed_img = apply_enhancements(img)
+    st.image(processed_img, caption="Processed Image")
+
+    # Show Original Image next
     st.subheader("Original Image")
-    st.image(img, caption="Original Image", use_column_width=True)
-
-    # Arrange layout for processed image and controls
-    processed_col, controls_col = st.columns([3, 2])
-
-    with processed_col:
-        st.subheader("Processed Image")
-        img_zoomed = zoom_at(img, 250, 250, 5)
-        img_contrast = ImageEnhance.Contrast(img_zoomed).enhance(1.0)
-        img_bright = ImageEnhance.Brightness(img_contrast).enhance(1.0)
-        img_sharp = ImageEnhance.Sharpness(img_bright).enhance(1.0)
-        st.image(img_sharp, use_column_width=True)
-
-    with controls_col:
-        st.subheader("Image Controls")
-        x = st.slider("X Coordinate", 0, 500, 250)
-        y = st.slider("Y Coordinate", 0, 500, 250)
-        zoom = st.slider("Zoom", 1, 10, 5)
-
-        with st.expander("Enhancement Settings"):
-            contrast = st.slider("Contrast", 0.0, 5.0, 1.0)
-            brightness = st.slider("Brightness", 0.0, 5.0, 1.0)
-            sharpness = st.slider("Sharpness", 0.0, 2.0, 1.0)
-
-        if st.button("Apply Adjustments"):
-            img_zoomed = zoom_at(img, x, y, zoom)
-            img_contrast = ImageEnhance.Contrast(img_zoomed).enhance(contrast)
-            img_bright = ImageEnhance.Brightness(img_contrast).enhance(brightness)
-            img_sharp = ImageEnhance.Sharpness(img_bright).enhance(sharpness)
-            st.image(img_sharp, use_column_width=True, caption="Processed Image")
-
-    actions_col, save_col = st.columns([2, 3])
-
-    with actions_col:
-        save_image = st.checkbox("Save Image")
-        if save_image:
-            img_sharp.save("image-processed.jpg")
-            st.success("Image saved as `image-processed.jpg`")
-
-        with st.expander("Save Options"):
-            description = st.text_area("Describe the image", "")
-            if st.button("Save Description"):
-                with open("saved_image_description.txt", "w") as f:
-                    f.write(description)
-                st.success("Description saved as `saved_image_description.txt`")
-
-            if st.button("Save Image Parameters"):
-                params = {
-                    "coordinates_x": x,
-                    "coordinates_y": y,
-                    "zoom": zoom,
-                    "contrast": contrast,
-                    "brightness": brightness,
-                    "sharpness": sharpness
-                }
-                with open("saved_image_parameters.json", "w") as f:
-                    f.write(pd.DataFrame([params]).to_json(orient="records"))
-                st.success("Image parameters saved as `saved_image_parameters.json`")
-
-            if st.button("Rename Files"):
-                file_ext = str(np.random.randint(100))
-                os.rename("image-processed.jpg", f"img_processed{file_ext}.jpg")
-                os.rename("saved_image_parameters.json", f"saved_image_parameters{file_ext}.json")
-                os.rename("saved_image_description.txt", f"saved_image_description{file_ext}.txt")
-                st.success("Files renamed successfully")
-
-    # Display Original Image Below Processed Image
-    st.markdown("### Original Image")
-    st.image(img, use_column_width=True)
+    st.image(img, caption="Original Image")
+
+    # Save Options
+    save_image = st.checkbox("Save Processed Image")
+    if save_image:
+        processed_img.save("image-processed.jpg")
+        st.success("Image saved as `image-processed.jpg`")
+
+    with st.expander("Save Options"):
+        description = st.text_area("Describe the image", "")
+        if st.button("Save Description"):
+            with open("saved_image_description.txt", "w") as f:
+                f.write(description)
+            st.success("Description saved as `saved_image_description.txt`")
+
+        if st.button("Save Image Parameters"):
+            params = {
+                "coordinates_x": x,
+                "coordinates_y": y,
+                "zoom": zoom,
+                "contrast": contrast,
+                "brightness": brightness,
+                "sharpness": sharpness
+            }
+            with open("saved_image_parameters.json", "w") as f:
+                f.write(pd.DataFrame([params]).to_json(orient="records"))
+            st.success("Image parameters saved as `saved_image_parameters.json`")
+
+        if st.button("Rename Files"):
+            file_ext = str(np.random.randint(100))
+            os.rename("image-processed.jpg", f"img_processed{file_ext}.jpg")
+            os.rename("saved_image_parameters.json", f"saved_image_parameters{file_ext}.json")
+            os.rename("saved_image_description.txt", f"saved_image_description{file_ext}.txt")
+            st.success("Files renamed successfully")