add all scripts

control_net_lineart.py

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+#!/usr/bin/env python3
+import torch
+import os
+from huggingface_hub import HfApi
+from pathlib import Path
+from diffusers.utils import load_image
+from controlnet_aux import LineartDetector
+
+from diffusers import (
+    ControlNetModel,
+    StableDiffusionControlNetPipeline,
+    UniPCMultistepScheduler,
+)
+import sys
+
+checkpoint = sys.argv[1]
+
+url = "https://github.com/lllyasviel/ControlNet-v1-1-nightly/raw/main/test_imgs/bag.png"
+url = "https://github.com/lllyasviel/ControlNet-v1-1-nightly/raw/main/test_imgs/person_1.jpeg"
+image = load_image(url)
+
+prompt = "michael jackson concert"
+
+processor = LineartDetector.from_pretrained("lllyasviel/Annotators")
+image = processor(image)
+image.save("/home/patrick/images/check.png")
+
+controlnet = ControlNetModel.from_pretrained(checkpoint, torch_dtype=torch.float16)
+pipe = StableDiffusionControlNetPipeline.from_pretrained(
+    "runwayml/stable-diffusion-v1-5", controlnet=controlnet, torch_dtype=torch.float16
+)
+
+pipe.scheduler = UniPCMultistepScheduler.from_config(pipe.scheduler.config)
+pipe.enable_model_cpu_offload()
+
+generator = torch.manual_seed(0)
+out_image = pipe(prompt, num_inference_steps=30, generator=generator, image=image).images[0]
+
+path = os.path.join(Path.home(), "images", "aa.png")
+out_image.save(path)
+
+api = HfApi()
+
+api.upload_file(
+    path_or_fileobj=path,
+    path_in_repo=path.split("/")[-1],
+    repo_id="patrickvonplaten/images",
+    repo_type="dataset",
+)
+print("https://huggingface.co/datasets/patrickvonplaten/images/blob/main/aa.png")