Create app.py

app.py

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+from diffusers import StableDiffusionXLInpaintPipeline
+import gradio as gr
+import numpy as np
+import imageio
+from PIL import Image
+import torch
+import modin.pandas as pd
+
+device = "cuda" if torch.cuda.is_available() else "cpu"
+pipe = StableDiffusionXLInpaintPipeline.from_pretrained("stabilityai/sdxl-turbo", safety_checker=None)
+pipe = pipe.to(device)
+
+def resize(value,img):
+    img = Image.open(img)
+    img = img.resize((value,value))
+    return img
+
+def img2img(source_img, prompt, strength):
+    imageio.imwrite("data.png", source_img['image'])
+    imageio.imwrite("data_mask.png", source_img["mask"])
+    src = resize(768, "data.png")
+    src.save("src.png")
+    mask = resize(768, "data_mask.png")
+    mask.save("mask.png")
+    image = pipe(prompt=prompt, image=src, mask_image=mask, num_inference_steps=6, strength=strength, guidance_scale=0.0).images[0]
+    return image
+
+title="GoldExtra Zeichnung zu 2.5D"
+description="OpenCV.js > i2i > 3D"
+gr.Interface(fn=img2img, inputs=[gr.Image(source="upload", tool="sketch", label="Source Image"), 
+                                gr.Textbox(label='What you want the AI to Generate, 77 Token limit'),
+                                gr.Slider(minimum=.5, maximum=1, value=.75, step=.025, label='Strength')], 
+             outputs='image', 
+             title=title, 
+             description=description, 
+             article = "Code Monkey: <a href=\"https://huggingface.co/Manjushri\">Manjushri</a>").launch(max_threads=True, debug=True)