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.gitattributes CHANGED
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README.md CHANGED
@@ -1,3 +1,43 @@
1
  ---
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  license: mit
 
 
3
  ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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  license: mit
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+ tags:
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+ - image-to-image
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  ---
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+
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+ # InstructPix2Pix: Learning to Follow Image Editing Instructions
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+ GitHub: https://github.com/timothybrooks/instruct-pix2pix
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+ <img src='https://instruct-pix2pix.timothybrooks.com/teaser.jpg'/>
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+
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+
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+
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+ ## Example
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+
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+ To use `InstructPix2Pix`, install `diffusers` using `main` for now. The pipeline will be available in the next release
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+
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+ ```bash
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+ pip install diffusers accelerate safetensors transformers
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+ ```
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+
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+ ```python
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+ import PIL
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+ import requests
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+ import torch
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+ from diffusers import StableDiffusionInstructPix2PixPipeline, EulerAncestralDiscreteScheduler
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+
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+ model_id = "timbrooks/instruct-pix2pix"
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+ pipe = StableDiffusionInstructPix2PixPipeline.from_pretrained(model_id, torch_dtype=torch.float16, safety_checker=None)
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+ pipe.to("cuda")
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+ pipe.scheduler = EulerAncestralDiscreteScheduler.from_config(pipe.scheduler.config)
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+
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+ url = "https://raw.githubusercontent.com/timothybrooks/instruct-pix2pix/main/imgs/example.jpg"
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+ def download_image(url):
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+ image = PIL.Image.open(requests.get(url, stream=True).raw)
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+ image = PIL.ImageOps.exif_transpose(image)
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+ image = image.convert("RGB")
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+ return image
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+ image = download_image(url)
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+
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+ prompt = "turn him into cyborg"
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+ images = pipe(prompt, image=image, num_inference_steps=10, image_guidance_scale=1).images
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+ images[0]
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+ ```
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+ 0.4578275,
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+ 0.40821073
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+ ],
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+ "image_processor_type": "CLIPImageProcessor",
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+ "image_std": [
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+ 0.26862954,
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+ 0.26130258,
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+ 0.27577711
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+ ],
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+ "resample": 3,
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+ "size": {
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+ "shortest_edge": 224
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+ }
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+ }
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+ {
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+ "_class_name": "StableDiffusionInstructPix2PixPipeline",
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+ "_diffusers_version": "0.12.0.dev0",
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+ "feature_extractor": [
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+ "transformers",
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+ "CLIPImageProcessor"
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+ ],
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+ "requires_safety_checker": false,
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+ "stable_diffusion",
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+ "StableDiffusionSafetyChecker"
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+ ],
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+ "scheduler": [
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+ "diffusers",
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+ "EulerAncestralDiscreteScheduler"
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+ ],
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+ "text_encoder": [
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+ "transformers",
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+ "CLIPTextModel"
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+ "unet": [
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+ "diffusers",
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+ "UNet2DConditionModel"
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+ ],
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+ "vae": [
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+ "diffusers",
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+ "AutoencoderKL"
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+ ]
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+ }
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