Update app.py

app.py

@@ -12,7 +12,7 @@ import spaces
 import torch
 from PIL import Image
 from io import BytesIO
-from diffusers import AutoencoderKL, DiffusionPipeline, AutoPipelineForImage2Image
+from diffusers import AutoencoderKL, DiffusionPipeline, AutoPipelineForImage2Image, AutoPipelineForInpainting
 
 DESCRIPTION = "# Run any LoRA or SD Model"
 if not torch.cuda.is_available():
@@ -25,7 +25,8 @@ USE_TORCH_COMPILE = os.getenv("USE_TORCH_COMPILE") == "1"
 ENABLE_CPU_OFFLOAD = os.getenv("ENABLE_CPU_OFFLOAD") == "1"
 ENABLE_USE_LORA = os.getenv("ENABLE_USE_LORA", "1") == "1"
 ENABLE_USE_VAE = os.getenv("ENABLE_USE_VAE", "1") == "1"
-ENABLE_USE_IMG2IMG = os.getenv("ENABLE_USE_VAE", "1") == "1"
+ENABLE_USE_IMG2IMG = os.getenv("ENABLE_USE_IMG2IMG", "1") == "1"
+ENABLE_USE_INPAINTING = os.getenv("ENABLE_USE_INPAINTING", "1") == "1"
 
 device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
 
@@ -57,7 +58,10 @@ def generate(
     lora = '',
     lora_scale: float = 0.7,
     use_img2img: bool = False,
+    use_inpainting: bool = False,
     url = '',
+    img_url = '',
+    mask_url = '',
 ):
     if torch.cuda.is_available():
             
@@ -74,11 +78,17 @@ def generate(
             if use_vae:  
                 vae = AutoencoderKL.from_pretrained(vaecall, torch_dtype=torch.float16)
                 pipe = AutoPipelineForImage2Image.from_pretrained(model, vae=vae, torch_dtype=torch.float16)
-                    
+                
+        if use_inpainting:
+            pipe = AutoPipelineForInpainting.from_pretrained("diffusers/stable-diffusion-xl-1.0-inpainting-0.1", torch_dtype=torch.float16)
+            
             response = requests.get(url)
             init_image = Image.open(BytesIO(response.content)).convert("RGB")
             init_image = init_image.resize((width, height))
 
+            img_url = download_image(img_url)
+            mask_image = download_image(mask_url)
+
         if use_lora:
             pipe.load_lora_weights(lora)
             pipe.fuse_lora(lora_scale)
@@ -101,20 +111,21 @@ def generate(
     if not use_negative_prompt_2:
         negative_prompt_2 = None  # type: ignore
 
-    if not use_img2img:
-        return pipe(
+    if use_inpainting:
+        images = pipe(
             prompt=prompt,
+            image=img_url,
+            mask_image=mask_url,
+            strength=strength_img2img,
             negative_prompt=negative_prompt,
             prompt_2=prompt_2,
             negative_prompt_2=negative_prompt_2,
-            width=width,
-            height=height,
             guidance_scale=guidance_scale_base,
             num_inference_steps=num_inference_steps_base,
             generator=generator,
-            output_type="pil",
         ).images[0]
-    else:
+        return images
+    if use_img2img:
         images = pipe(
             prompt=prompt,
             image=init_image,
@@ -130,6 +141,19 @@ def generate(
             output_type="pil",
         ).images[0]
         return images
+    else:
+        return pipe(
+            prompt=prompt,
+            negative_prompt=negative_prompt,
+            prompt_2=prompt_2,
+            negative_prompt_2=negative_prompt_2,
+            width=width,
+            height=height,
+            guidance_scale=guidance_scale_base,
+            num_inference_steps=num_inference_steps_base,
+            generator=generator,
+            output_type="pil",
+        ).images[0]
 
 examples = [
     "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k",
@@ -166,6 +190,7 @@ with gr.Blocks(theme=gr.themes.Soft(), css="style.css") as demo:
         result = gr.Image(label="Result", show_label=False)
     with gr.Accordion("Advanced options", open=False):
         with gr.Row():
+            use_inpainting = gr.Checkbox(label='Use Inpainting', value=False, visible=ENABLE_USE_INPAINTING)
             use_img2img = gr.Checkbox(label='Use Img2Img', value=False, visible=ENABLE_USE_IMG2IMG)
             use_vae = gr.Checkbox(label='Use VAE', value=False, visible=ENABLE_USE_VAE)
             use_lora = gr.Checkbox(label='Use Lora', value=False, visible=ENABLE_USE_LORA)
@@ -293,6 +318,20 @@ with gr.Blocks(theme=gr.themes.Soft(), css="style.css") as demo:
         queue=False,
         api_name=False,
     )
+    use_inpainting.change(
+        fn=lambda x: gr.update(visible=x),
+        inputs=use_inpainting,
+        outputs=img_url,
+        queue=False,
+        api_name=False,
+    )
+    use_inpainting.change(
+        fn=lambda x: gr.update(visible=x),
+        inputs=use_inpainting,
+        outputs=mask_url,
+        queue=False,
+        api_name=False,
+    )
 
     gr.on(
         triggers=[
@@ -330,6 +369,7 @@ with gr.Blocks(theme=gr.themes.Soft(), css="style.css") as demo:
             lora,
             lora_scale,
             use_img2img,
+            use_inpainting
             url,
         ],
         outputs=result,