Update app.py

app.py

@@ -10,13 +10,41 @@ from diffusers import AutoPipelineForInpainting, AutoencoderKL
 # -----------------------------
 # Pure-CPU helpers (no CUDA here)
 # -----------------------------
-def squarify_image(img, color="white"):
+from PIL import Image, ImageChops
+
+def autocrop_content(img: Image.Image, bg_color=(255, 255, 255), tol=12) -> Image.Image:
+    """
+    Trim uniform white (or near-white) margins before we center/pad.
+    Works for RGB and RGBA. `tol` is tolerance for "how white".
+    """
+    if img.mode in ("RGBA", "LA"):
+        # If we have transparency, use alpha channel bbox
+        alpha = img.split()[-1]
+        bbox = alpha.getbbox()
+        return img.crop(bbox) if bbox else img
+
+    # RGB: compare to a solid background
+    bg = Image.new(img.mode, img.size, bg_color)
+    diff = ImageChops.difference(img, bg).convert("L")
+    # Binarize with tolerance to catch JPEG off-white backgrounds
+    mask = diff.point(lambda p: 255 if p > tol else 0, mode="1")
+    bbox = mask.getbbox()
+    return img.crop(bbox) if bbox else img
+
+def squarify_image(img: Image.Image, color="white") -> Image.Image:
+    """
+    1) Trim outer white margins.
+    2) Pad to square, centered.
+    """
+    img = autocrop_content(img, bg_color=(255, 255, 255), tol=12)
+
     w, h = img.size
     size = max(w, h)
-    bg = Image.new(mode="RGB", size=(size, size), color=color)
+    bg = Image.new("RGB", (size, size), color=color)
     bg.paste(img, ((size - w) // 2, (size - h) // 2))
     return bg
 
+
 def divisible_by_8(image: Image.Image) -> Image.Image:
     w, h = image.size
     new_w = max(8, (w // 8) * 8)