Created
September 2, 2024 01:20
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StableDiffusionImg2ImgPipeline
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| import torch | |
| from PIL import Image | |
| from diffusers import StableDiffusionImg2ImgPipeline | |
| model_id = "CompVis/stable-diffusion-v1-4" | |
| device = "cuda" if torch.cuda.is_available() else "cpu" | |
| pipeline = StableDiffusionImg2ImgPipeline.from_pretrained(model_id) | |
| pipeline = pipeline.to(device) | |
| input_image_path = "image.png" | |
| try: | |
| input_image = Image.open(input_image_path) | |
| input_image = input_image.convert("RGB") | |
| except Exception as e: | |
| raise ValueError(f"Error loading imagen: {e}") | |
| prompt = ( | |
| "only modify the hairstyle of this person to add a futuristic haircut, " | |
| "without changing any other facial features or background." | |
| ) | |
| init_image = input_image.resize((512, 512)) | |
| try: | |
| output = pipeline( | |
| prompt=prompt, image=init_image, strength=0.75, guidance_scale=7.5 | |
| ).images[0] | |
| except Exception as e: | |
| raise ValueError(f"Error generating imagen: {e}") | |
| output_image_path = "output_image_modified.png" | |
| output.save(output_image_path) | |
| print(f"DONE... '{output_image_path}'") |
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