Create app.py

app.py

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+import gradio as gr
+from controlnet_aux import OpenposeDetector
+from PIL import Image
+from diffusers import StableDiffusionControlNetPipeline, ControlNetModel, UniPCMultistepScheduler
+import torch
+from controlnet_aux import OpenposeDetector
+from diffusers.utils import load_image
+
+#Models
+openpose = OpenposeDetector.from_pretrained('lllyasviel/ControlNet')
+controlnet = ControlNetModel.from_pretrained("lllyasviel/sd-controlnet-openpose", torch_dtype=torch.float16)
+pipe = StableDiffusionControlNetPipeline.from_pretrained("/content/drive/MyDrive/hack/800", controlnet=controlnet, safety_checker=None, torch_dtype=torch.float16)
+
+#optimizations
+pipe.scheduler = UniPCMultistepScheduler.from_config(pipe.scheduler.config)
+pipe.enable_xformers_memory_efficient_attention()
+pipe.enable_model_cpu_offload()
+
+def generate(image,prompt):
+    image = openpose(image)
+    print(image)
+    image = pipe(prompt, image, num_inference_steps=20).images[0]
+    return image
+
+gr.Interface(fn=generate, inputs=["image","text"], outputs="image").launch(share=True)
+