Update app.py

app.py

@@ -3,10 +3,13 @@ from PIL import Image
 import numpy as np
 import pandas as pd
 
-
 # Simple app: convert user input into ASCII codes and binary labels
 
 def string_to_binary_labels(s: str) -> list[int]:
+    """
+    Convert a string into a flat list of binary labels (0 or 1) representing
+    each character's 8-bit ASCII code.
+    """
     bits: list[int] = []
     for char in s:
         ascii_code = ord(char)
@@ -14,15 +17,27 @@ def string_to_binary_labels(s: str) -> list[int]:
         bits.extend(char_bits)
     return bits
 
-def image_to_binary_labels(img: Image.Image, max_pixels: int = 256) -> list[int]:
+def image_to_binary_labels_rgb(img: Image.Image, max_pixels: int = 256) -> list[int]:
+    """
+    Convert an RGB image to binary labels (0/1).
+    Store full RGB values (24 bits per pixel).
+    """
     img = img.convert("RGB")
     img.thumbnail((int(np.sqrt(max_pixels)), int(np.sqrt(max_pixels))))
     img_array = np.array(img)
-    flat = img_array.flatten()
-    binarized = [(pixel >> bit) & 1 for pixel in flat for bit in range(7, -1, -1)]
-    return binarized
+    flat_pixels = img_array.reshape(-1, 3)
+
+    bits = []
+    for pixel in flat_pixels:
+        for channel in pixel:  # R, G, B
+            channel_bits = [(channel >> bit) & 1 for bit in range(7, -1, -1)]
+            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)))
@@ -36,14 +51,19 @@ def binary_labels_to_image(binary_labels: list[int], width: int = None, height:
     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.
+    """
     total_pixels = len(binary_labels) // 24
     if width is None or height is None:
         side = int(np.ceil(np.sqrt(total_pixels)))
         width = height = side
+
     needed_pixels = width * height
     needed_bits = needed_pixels * 24
     if len(binary_labels) < needed_bits:
         binary_labels += [0] * (needed_bits - len(binary_labels))
+
     pixels = []
     for i in range(0, needed_bits, 24):
         r_bits = binary_labels[i:i+8]
@@ -53,10 +73,12 @@ def binary_labels_to_rgb_image(binary_labels: list[int], width: int = None, heig
         g = sum(b << (7-j) for j, b in enumerate(g_bits))
         b = sum(b << (7-j) for j, b in enumerate(b_bits))
         pixels.append((r, g, b))
+
     array = np.array(pixels, dtype=np.uint8).reshape((height, width, 3))
     img = Image.fromarray(array, mode='RGB')
     return img
 
+# Predefined headers for the 32 mutation sites
 mutation_site_headers = [
     3244, 3297, 3350, 3399, 3455, 3509, 3562, 3614,
     3665, 3720, 3773, 3824, 3879, 3933, 3985, 4039,
@@ -66,6 +88,7 @@ mutation_site_headers = [
 
 st.title("ASCII & Binary Label Converter")
 
+# Create tabs
 tab1, tab2 = st.tabs(["Text to Binary Labels", "Image to Binary Labels"])
 
 with tab1:
@@ -115,9 +138,9 @@ 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=2056, value=1024, 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(img, max_pixels=max_pixels)
+        binary_labels = image_to_binary_labels_rgb(img, max_pixels=max_pixels)
 
         st.subheader("Binary Labels from Image")
         num_groups = (len(binary_labels) + 31) // 32