Update app.py

app.py

@@ -34,22 +34,6 @@ def image_to_binary_labels_rgb(img: Image.Image, max_pixels: int = 256) -> list[
             bits.extend(channel_bits)
     return bits
 
-def binary_labels_to_image(binary_labels: list[int], width: int = None, height: int = None) -> Image.Image:
-    """
-    Convert binary labels (0/1) into a grayscale image.
-    """
-    total_pixels = len(binary_labels)
-    if width is None or height is None:
-        side = int(np.ceil(np.sqrt(total_pixels)))
-        width = height = side
-    needed_pixels = width * height
-    if total_pixels < needed_pixels:
-        binary_labels += [0] * (needed_pixels - total_pixels)
-    array = np.array(binary_labels, dtype=np.uint8) * 255
-    image_array = array.reshape((height, width))
-    img = Image.fromarray(image_array, mode='L')
-    return img
-
 def binary_labels_to_rgb_image(binary_labels: list[int], width: int = None, height: int = None) -> Image.Image:
     """
     Convert binary labels (0/1) into an RGB image.
@@ -138,7 +122,7 @@ with tab2:
         img = Image.open(uploaded_file)
         st.image(img, caption="Uploaded Image", use_column_width=True)
 
-        max_pixels = st.slider("Max number of pixels to encode", min_value=32, max_value=10240, value=256, step=32)
+        max_pixels = st.slider("Max number of pixels to encode", min_value=32, max_value=1024, value=256, step=32)
 
         binary_labels = image_to_binary_labels_rgb(img, max_pixels=max_pixels)
 
@@ -158,6 +142,10 @@ with tab2:
         df = pd.DataFrame(table_data, columns=[str(h) for h in mutation_site_headers] + ["Edited Sites"])
         st.dataframe(df)
 
+        st.subheader("Reconstructed RGB Image")
+        reconstructed_img = binary_labels_to_rgb_image(binary_labels)
+        st.image(reconstructed_img, caption="Reconstructed Image", use_column_width=True)
+
         st.download_button(
             label="Download Image Binary Labels as CSV",
             data=','.join(str(b) for b in binary_labels),
@@ -165,14 +153,4 @@ with tab2:
             mime="text/csv"
         )
 
-        st.subheader("Reconstruct Image from Binary Labels")
-        option = st.radio("Choose Reconstruction Mode", ["Grayscale", "True Color (RGB)"])
-
-        if st.button("Reconstruct Image"):
-            if option == "Grayscale":
-                reconstructed_img = binary_labels_to_image(binary_labels)
-            else:
-                reconstructed_img = binary_labels_to_rgb_image(binary_labels)
-            st.image(reconstructed_img, caption="Reconstructed Image", use_column_width=True)
-
-# Future: integrate DNA editor mapping for each mutation site here
+# Future: integrate DNA editor mapping for each mutation site here