Create app.py

app.py

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+import gradio as gr
+from PIL import Image
+import torch
+from diffusers import DiffusionPipeline
+from diffusers.utils import load_image
+import io
+
+pipeline = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-refiner-1.0")
+
+def generate_image(uploaded_file, surgery_option, additional_info):
+    if uploaded_file is not None:
+        pil_image = Image.open(io.BytesIO(uploaded_file.read()))
+        init_image = load_image(pil_image).convert("RGB")
+        prompt = f"generate image of how this person would look after {surgery_option} also use this additional information {additional_info}"
+        image = pipeline(prompt, image=init_image).images[0]
+        return image
+    else:
+        return "No image uploaded."
+
+surgery_options = ["Face Lift", "Nose Correction", "Chin Implant"]
+
+iface = gr.Interface(
+    fn=generate_image,
+    inputs=[
+        gr.inputs.Image(type="file", label="Upload an Image"),
+        gr.inputs.Dropdown(surgery_options, label="Select Surgery Option"),
+        gr.inputs.Textbox(label="Additional Information")
+    ],
+    outputs=gr.outputs.Image(type="pil", label="Generated Image"),
+    title="SurgiLook.ai",
+    description="Visualize the results of a surgical procedure before it happens."
+)
+
+iface.launch()