Update README.md

README.md

@@ -91,6 +91,53 @@ controlnet_strength:1.0
 stargt_percent:0.0
 end_percent:0.9
 ```
+## Diffusers pipeline
+Make sure to first install the libraries:
+```
+pip install accelerate transformers safetensors opencv-python diffusers
+```
+And then we're ready to go:
+```
+from diffusers import ControlNetModel, StableDiffusionXLControlNetPipeline, AutoencoderKL
+from diffusers.utils import load_image
+from PIL import Image
+import torch
+import numpy as np
+import cv2
+
+prompt = "aerial view, a futuristic research complex in a bright foggy jungle, hard lighting"
+negative_prompt = 'low quality, bad quality, sketches'
+
+image = load_image("https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/sd_controlnet/hf-logo.png")
+
+controlnet_conditioning_scale = 0.5
+
+controlnet = ControlNetModel.from_pretrained(
+    "diffusers/controlnet-canny-sdxl-1.0",
+    torch_dtype=torch.float16
+)
+vae = AutoencoderKL.from_pretrained("TheMistoAI/MistoLine", torch_dtype=torch.float16)
+pipe = StableDiffusionXLControlNetPipeline.from_pretrained(
+    "stabilityai/stable-diffusion-xl-base-1.0",
+    controlnet=controlnet,
+    vae=vae,
+    torch_dtype=torch.float16,
+)
+pipe.enable_model_cpu_offload()
+
+image = np.array(image)
+image = cv2.Canny(image, 100, 200)
+image = image[:, :, None]
+image = np.concatenate([image, image, image], axis=2)
+image = Image.fromarray(image)
+
+images = pipe(
+    prompt, negative_prompt=negative_prompt, image=image, controlnet_conditioning_scale=controlnet_conditioning_scale,
+    ).images
+
+images[0].save(f"hug_lab.png")
+```
+
 
 ## Checkpoints
 * mistoLine_rank256.safetensors : General usage version, for ComfyUI and AUTOMATIC1111-WebUI.