Updated some change missing in this

README.md

@@ -64,7 +64,9 @@ pip install diffusers
 ```py
 from diffusers import ControlNetModel, StableDiffusionXLControlNetPipeline
 import torch
-
+import cv2
+from PIL import Image
+import numpy as np 
 controlnet = ControlNetModel.from_pretrained(
     "briaai/ControlNet-Canny",
     torch_dtype=torch.float16
@@ -80,12 +82,15 @@ pipe.to("cuda")
 prompt = "A portrait of a Beautiful and playful ethereal singer, golden designs, highly detailed, blurry background"
 negative_prompt = "Logo,Watermark,Text,Ugly,Morbid,Extra fingers,Poorly drawn hands,Mutation,Blurry,Extra limbs,Gross proportions,Missing arms,Mutated hands,Long neck,Duplicate,Mutilated,Mutilated hands,Poorly drawn face,Deformed,Bad anatomy,Cloned face,Malformed limbs,Missing legs,Too many fingers"
 
+
+low_threshold=100
+high_threshold=200
 # Calculate Canny image
 input_image = cv2.imread('pics/singer.png')
-input_image = cv2.Canny(input_image, low_threshold, high_threshold)
+canny_image = cv2.Canny(input_image, low_threshold, high_threshold)
 input_image = input_image[:, :, None]
-input_image = np.concatenate([input_image, input_image, input_image], axis=2)
-canny_image = Image.fromarray(image)
+input_image = np.concatenate([input_image, canny_image, input_image], axis=2)
+canny_image = Image.fromarray(canny_image)
 
 image = pipe(prompt=prompt, negative_prompt=negative_prompt, image=canny_image, controlnet_conditioning_scale=1.0, height=1024, width=1024).images[0]
 ```