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control_net_canny.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 CannyDetector
+
+from diffusers import (
+    ControlNetModel,
+    StableDiffusionControlNetPipeline,
+    UniPCMultistepScheduler,
+)
+import sys
+
+checkpoint = sys.argv[1]
+
+image = load_image(
+    "https://huggingface.co/lllyasviel/sd-controlnet-canny/resolve/main/images/bird.png"
+)
+
+canny_detector = CannyDetector()
+canny_image = canny_detector(image, low_threshold=100, high_threshold=200)
+
+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(33)
+out_image = pipe("a blue paradise bird in the jungle", num_inference_steps=20, generator=generator, image=canny_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")

diffusion_pytorch_model.bin

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diffusion_pytorch_model.fp16.bin

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diffusion_pytorch_model.fp16.safetensors

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diffusion_pytorch_model.safetensors

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