uP

README.md

@@ -7,12 +7,12 @@ tags:
 - stable-diffusion
 ---
 
-# Controlnet - v1.1 - *normalbae Version*
+# Controlnet - v1.1 - *lineart Version*
 
 **Controlnet v1.1** is the successor model of [Controlnet v1.0](https://huggingface.co/lllyasviel/ControlNet)
 and was released in [lllyasviel/ControlNet-v1-1](https://huggingface.co/lllyasviel/ControlNet-v1-1) by [Lvmin Zhang](https://huggingface.co/lllyasviel).
 
-This checkpoint is a conversion of [the original checkpoint](https://huggingface.co/lllyasviel/ControlNet-v1-1/blob/main/control_v11p_sd15_normalbae.pth) into `diffusers` format.
+This checkpoint is a conversion of [the original checkpoint](https://huggingface.co/lllyasviel/ControlNet-v1-1/blob/main/control_v11p_sd15_lineart.pth) into `diffusers` format.
 It can be used in combination with **Stable Diffusion**, such as [runwayml/stable-diffusion-v1-5](https://huggingface.co/runwayml/stable-diffusion-v1-5).
 
 
@@ -23,7 +23,7 @@ ControlNet is a neural network structure to control diffusion models by adding e
 
 ![img](./sd.png)
 
-This checkpoint corresponds to the ControlNet conditioned on **normalbae images**.
+This checkpoint corresponds to the ControlNet conditioned on **lineart images**.
 
 ## Model Details
 - **Developed by:** Lvmin Zhang, Maneesh Agrawala
@@ -86,7 +86,7 @@ from pathlib import Path
 from diffusers.utils import load_image
 from PIL import Image
 import numpy as np
-from controlnet_aux import NormalBaeDetector
+from controlnet_aux import LineartDetector
 
 from diffusers import (
     ControlNetModel,
@@ -94,14 +94,14 @@ from diffusers import (
     UniPCMultistepScheduler,
 )
 
-checkpoint = "ControlNet-1-1-preview/control_v11p_sd15_normalbae"
+checkpoint = "ControlNet-1-1-preview/control_v11p_sd15_lineart"
 
 image = load_image(
-    "https://huggingface.co/ControlNet-1-1-preview/control_v11p_sd15_normalbae/resolve/main/images/input.png"
+    "https://huggingface.co/ControlNet-1-1-preview/control_v11p_sd15_lineart/resolve/main/images/input.png"
 )
 
-prompt = "A head full of roses"
-processor = NormalBaeDetector.from_pretrained("lllyasviel/Annotators")
+prompt = "michael jackson concert"
+processor = LineartDetector.from_pretrained("lllyasviel/Annotators")
 
 control_image = processor(image)
 control_image.save("./images/control.png")