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run_local_xl_inpaint.py

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+#!/usr/bin/env python3
+from diffusers import DiffusionPipeline, EulerDiscreteScheduler, StableDiffusionPipeline, KDPM2DiscreteScheduler, StableDiffusionImg2ImgPipeline, HeunDiscreteScheduler, KDPM2AncestralDiscreteScheduler, DDIMScheduler
+from diffusers import StableDiffusionXLPipeline, StableDiffusionXLImg2ImgPipeline, StableDiffusionXLInpaintPipeline, AutoencoderKL
+import time
+from pytorch_lightning import seed_everything
+import os
+from huggingface_hub import HfApi
+# from compel import Compel
+import torch
+import sys
+from pathlib import Path
+import requests
+from PIL import Image
+from io import BytesIO
+
+api = HfApi()
+start_time = time.time()
+
+use_refiner = bool(int(sys.argv[1]))
+use_diffusers = True
+
+vae = AutoencoderKL.from_pretrained("madebyollin/sdxl-vae-fp16-fix", torch_dtype=torch.float16, force_upcast=True)
+pipe = StableDiffusionXLInpaintPipeline.from_pretrained("stabilityai/stable-diffusion-xl-base-0.9", vae=vae, torch_dtype=torch.float16, variant="fp16", use_safetensors=True, local_files_only=True)
+print(time.time() - start_time)
+pipe.to("cuda")
+
+def download_image(url):
+    response = requests.get(url)
+    return Image.open(BytesIO(response.content)).convert("RGB")
+
+
+img_url = "https://raw.githubusercontent.com/CompVis/latent-diffusion/main/data/inpainting_examples/overture-creations-5sI6fQgYIuo.png"
+mask_url = "https://raw.githubusercontent.com/CompVis/latent-diffusion/main/data/inpainting_examples/overture-creations-5sI6fQgYIuo_mask.png"
+
+init_image = download_image(img_url).resize((1024, 1024))
+mask_image = download_image(mask_url).resize((1024, 1024))
+
+if use_refiner:
+    start_time = time.time()
+    refiner = StableDiffusionXLInpaintPipeline.from_pretrained("stabilityai/stable-diffusion-xl-refiner-0.9", vae=vae, torch_dtype=torch.float16, use_safetensors=True, variant="fp16")
+    refiner.to("cuda")
+    # refiner.enable_sequential_cpu_offload()
+
+prompt = "A majestic tiger sitting on a bench"
+steps = 100
+seed = 3
+seed_everything(seed)
+start_time = time.time()
+image = pipe(prompt=prompt, image=init_image, mask_image=mask_image, num_inference_steps=steps, denoising_end=0.8, strength=0.80, output_type="latent").images
+print(time.time() - start_time)
+
+if use_refiner:
+    image = refiner(prompt=prompt, image=image, mask_image=mask_image, num_inference_steps=steps, denoising_start=0.8).images[0]
+
+file_name = f"aaa_1"
+path = os.path.join(Path.home(), "images", "ediffi_sdxl", f"{file_name}.png")
+image.save(path)
+
+api.upload_file(
+    path_or_fileobj=path,
+    path_in_repo=path.split("/")[-1],
+    repo_id="patrickvonplaten/images",
+    repo_type="dataset",
+)
+print(f"https://huggingface.co/datasets/patrickvonplaten/images/blob/main/{file_name}.png")