Update app.py

app.py

@@ -2,56 +2,57 @@ import gradio as gr
 from PIL import Image
 import numpy as np
 
-def brightness_to_opacity_overlay(fg_img, bg_img, invert_opacity=False):
-    if fg_img is None or bg_img is None:
+def brightness_to_opacity_overlay(mask_img, bg_img, invert_opacity=False):
+    if mask_img is None or bg_img is None:
         return None
 
-    # Convert images
-    fg = fg_img.convert("RGB")
+    # Convert images and resize mask to match background
+    mask = mask_img.convert("RGB")
     bg = bg_img.convert("RGBA")
+    mask = mask.resize(bg.size)
 
-    # Resize fg to match bg
-    fg = fg.resize(bg.size)
+    # Convert mask to brightness-based alpha
+    mask_np = np.array(mask).astype(np.float32)
+    brightness = np.dot(mask_np[..., :3], [0.299, 0.587, 0.114])
+    alpha = (255 - brightness if invert_opacity else brightness).clip(0, 255)
+    alpha = alpha / 255.0  # normalize to 0-1
 
-    # Convert to brightness
-    fg_np = np.array(fg).astype(np.float32)
-    luminance = np.dot(fg_np[..., :3], [0.299, 0.587, 0.114])
-    if invert_opacity:
-        luminance = 255 - luminance
-    alpha = (luminance / 255.0).clip(0, 1)
+    # Normalize mask RGB
+    rgb = mask_np / 255.0
 
-    # Make white RGB with computed alpha
-    overlay_rgb = np.ones_like(fg_np) * 255
-    overlay_rgba = np.dstack((overlay_rgb, alpha * 255)).astype(np.uint8)
+    # Combine original RGB with generated alpha
+    overlay_rgba = np.dstack((rgb, alpha))  # shape: (H, W, 4)
 
-    # Convert both to float for blending
-    overlay = overlay_rgba.astype(np.float32) / 255.0
+    # Convert background to float32
     bg_np = np.array(bg).astype(np.float32) / 255.0
 
-    # Premultiplied alpha blend
-    fg_a = overlay[..., 3:4]
-    bg_a = bg_np[..., 3:4]
-    out_a = fg_a + bg_a * (1 - fg_a)
-    out_rgb = (overlay[..., :3] * fg_a + bg_np[..., :3] * bg_a * (1 - fg_a)) / np.maximum(out_a, 1e-6)
+    # Extract alphas
+    alpha_fg = overlay_rgba[..., 3:4]
+    alpha_bg = bg_np[..., 3:4]
 
-    # Final image
-    result_np = np.dstack((out_rgb, out_a)).clip(0, 1) * 255
-    result_img = Image.fromarray(result_np.astype(np.uint8), mode="RGBA")
-    return result_img
+    # Premultiplied blend
+    out_alpha = alpha_fg + alpha_bg * (1 - alpha_fg)
+    out_rgb = (overlay_rgba[..., :3] * alpha_fg + bg_np[..., :3] * alpha_bg * (1 - alpha_fg)) / np.maximum(out_alpha, 1e-6)
+
+    # Compose final image
+    out_img = np.dstack((out_rgb, out_alpha)).clip(0, 1) * 255
+    final = Image.fromarray(out_img.astype(np.uint8), mode="RGBA")
+
+    return final
 
 # Gradio UI
 iface = gr.Interface(
     fn=brightness_to_opacity_overlay,
     inputs=[
-        gr.Image(type="pil", label="Alpha From Brightness (Foreground)"),
-        gr.Image(type="pil", label="Background Image (May Have Transparency)"),
+        gr.Image(type="pil", label="Mask Image (Color OK)"),
+        gr.Image(type="pil", label="Background Image (Supports Alpha)"),
         gr.Checkbox(label="Invert Brightness", value=False)
     ],
-    outputs=gr.Image(type="pil", label="Composite Output"),
-    title="⚡ Accurate Brightness-to-Alpha Overlay",
+    outputs=gr.Image(type="pil", label="Composite Result"),
+    title="✨ Brightness-to-Alpha with Color Mask",
     description=(
-        "This tool uses brightness as alpha, resizes to match background, "
-        "and blends correctly — even with transparent backgrounds."
+        "Uses the brightness of a colored image as opacity, preserves color, "
+        "and overlays it onto a background image (even with alpha transparency)."
     )
 )