Create app.py

app.py

@@ -0,0 +1,45 @@
+import gradio as gr
+from PIL import Image
+
+import torch
+from diffusers import AutoPipelineForInpainting
+from diffusers.utils import load_image
+
+def draw_on_image(image, prompt):
+    print(image, prompt)
+
+    if not prompt:
+        return
+
+    init_image = load_image(
+        image["image"]
+    )
+    mask_image = load_image(
+        image["mask"]
+    )
+
+    res_image = pipeline(prompt=prompt, image=init_image, mask_image=mask_image).images[0]
+
+    return res_image
+
+inputs = [
+            gr.Image(tool="sketch", label="Image", type="pil"),
+            gr.Text(max_lines=1)
+    ]
+
+if torch.cuda.is_available():
+    torch_dtype = torch.float32
+    device = "cuda"
+else:
+    torch_dtype = torch.float16
+    device = "cpu"
+
+pipeline = AutoPipelineForInpainting.from_pretrained(
+    "kandinsky-community/kandinsky-2-2-decoder-inpaint", torch_dtype=torch_dtype
+)
+
+pipeline.to(device)
+
+app = gr.Interface(draw_on_image, inputs=inputs, outputs="image")
+app.queue()
+app.launch(share=True)