Update README.md

README.md

@@ -26,21 +26,38 @@ Fine-tuned checkpoint of [`diffusers/stable-diffusion-xl-1.0-inpainting-0.1`](ht
 
 ```python
 import torch
+from PIL import Image
 from diffusers import StableDiffusionXLInpaintPipeline
 
 pipe = StableDiffusionXLInpaintPipeline.from_pretrained(
     "esalahterus/refo", torch_dtype=torch.bfloat16
 ).to("cuda")
 
+source_image = Image.open("path/to/your_image.jpg").convert("RGB")
+mask_image = Image.open("path/to/your_mask.png").convert("L")  # white = area to edit, black = area to keep
+
 result = pipe(
     prompt="a high quality photo background, a quiet beach at sunset, photorealistic, detailed, no people, no text",
     negative_prompt="low quality, blurry foreground, distorted subject, watermark, text",
-    image=source_image,      # source photo
-    mask_image=mask_image,   # white = background area to edit, black = subject to preserve
+    image=source_image,
+    mask_image=mask_image,
     num_inference_steps=30,
     guidance_scale=7.5,
-    strength=1.0,             # important: use exactly 1.0 — values like 0.99 only blend lightly instead of fully regenerating the masked area
+    strength=1.0,  # important: use exactly 1.0 — values like 0.99 only blend lightly instead of fully regenerating the masked area
+    generator=torch.Generator(device="cuda").manual_seed(0),  # optional, for reproducible results
 ).images[0]
+
+result.save("output.png")
+```
+
+No mask image? You can auto-generate a foreground mask with [`rembg`](https://github.com/danielgatis/rembg):
+
+```python
+from rembg import remove, new_session
+
+session = new_session("u2net")
+fg_mask = remove(source_image, session=session, only_mask=True).convert("L")
+mask_image = Image.eval(fg_mask, lambda x: 255 - x)  # invert so white = background
 ```
 
 ## Intended Use