Update README.md

README.md

@@ -108,7 +108,7 @@ def prepare_masked_image(
         mask_norm = np.stack([mask_norm] * 3, axis=-1)
 
     # Combine: keep original pixels where mask=0, use noisy_bg where mask=1
-    combined = ((1 - mask_norm) * foreground_np + mask_norm * noisy_bg).astype(np.uint8)
+    combined = ((1 - mask_norm) * noisy_bg + mask_norm * foreground_np).astype(np.uint8)
 
     return Image.fromarray(combined)
 
@@ -116,8 +116,8 @@ def prepare_masked_image(
 def main():
     """Entry point for running the FluxFill pipeline."""
     # Load input image and its corresponding mask
-    fg_mask = load_image("https://huggingface.co/rkv1990/FLUX.1-Fill-dev-outpainting/resolve/main/beauty-products-mask.png")
-    input_image= load_image("https://huggingface.co/rkv1990/FLUX.1-Fill-dev-outpainting/resolve/main/beauty-products.png")
+    fg_mask = load_image("https://huggingface.co/rkv1990/FLUX.1-Fill-dev-outpainting/resolve/main/beauty-products-mask.png").convert("L")
+    input_image= load_image("https://huggingface.co/rkv1990/FLUX.1-Fill-dev-outpainting/resolve/main/beauty-products.png").convert("RGB")
 
     masked_image = prepare_masked_image(foreground=input_image, mask=fg_mask)
 
@@ -129,7 +129,7 @@ def main():
 
     # Run the pipeline
     output = pipe(
-        prompt="a white paper cup",
+        prompt="A mist-covered forest at dawn, with pale golden light filtering through ancient, twisted trees. Soft fog swirls around delicate wildflowers glowing faintly with bioluminescence.",
         image=masked_image,
         mask_image=fg_mask,
         height=1024,