Create app.py

1st deployment

app.py

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+import torch #needed only for GPU
+from PIL import Image
+from io import BytesIO
+from diffusers import StableDiffusionUpscalePipeline
+import gradio as gr
+# load model and scheduler
+model_id = "stabilityai/stable-diffusion-x4-upscaler"
+pipeline = StableDiffusionUpscalePipeline.from_pretrained(model_id)
+pipeline = pipeline.to("cpu")
+#define interface 
+def upscale(low_res_img, prompt, guide):
+ low_res_img = Image.open(low_res_img).convert("RGB")
+ low_res_img = low_res_img.resize((128, 128))
+ upscaled_image = pipeline(prompt=prompt, image=low_res_img, guidance_scale=guide).images[0]
+ upscaled_image.save("upsampled.png")
+ return upscaled_image
+#launch interface
+gr.Interface(fn=upscale, inputs=[gr.Image(type='filepath'), 'text', gr.Slider(1, 20, 5)], outputs=gr.Image(type='filepath')).launch(max_threads=True, debug=True)