| --- |
| language: |
| - en |
| --- |
| ```python |
| import paddle |
| from ppdiffusers import DiffusionPipeline, ControlNetModel |
| from ppdiffusers.utils import load_image, image_grid |
| import numpy as np |
| from PIL import Image |
| import cv2 |
| |
| class CannyDetector: |
| def __call__(self, img, low_threshold, high_threshold): |
| return cv2.Canny(img, low_threshold, high_threshold) |
| apply_canny = CannyDetector() |
| |
| # 加载模型 |
| controlnet = ControlNetModel.from_pretrained("lllyasviel/sd-controlnet-canny", paddle_dtype=paddle.float16) |
| pipe = DiffusionPipeline.from_pretrained("runwayml/stable-diffusion-v1-5", |
| controlnet=controlnet, |
| safety_checker=None, |
| feature_extractor=None, |
| requires_safety_checker=False, |
| paddle_dtype=paddle.float16, |
| custom_pipeline="webui_stable_diffusion_controlnet", |
| custom_revision="9aa0fcae034d99a796c3077ec6fea84808fc5875") |
| |
| # 或者 # custom_pipeline="junnyu/webui_controlnet_ppdiffusers") |
| |
| # 加载图片 |
| raw_image = load_image("https://paddlenlp.bj.bcebos.com/models/community/junnyu/develop/control_bird_canny_demo.png") |
| canny_image = Image.fromarray(apply_canny(np.array(raw_image), low_threshold=100, high_threshold=200)) |
| |
| # 选择sampler |
| # Please choose in ['pndm', 'lms', 'euler', 'euler-ancestral', 'dpm-multi', 'dpm-single', 'unipc-multi', 'ddim', 'ddpm', 'deis-multi', 'heun', 'kdpm2-ancestral', 'kdpm2']! |
| pipe.switch_scheduler('euler-ancestral') |
| |
| # propmpt 和 negative_prompt |
| prompt = "a (blue:1.5) bird" |
| negative_prompt = "" |
| # 想要返回多少张图片 |
| num = 4 |
| clip_skip = 2 |
| controlnet_conditioning_scale = 1. |
| num_inference_steps = 50 |
| |
| all_images = [] |
| print("raw_image vs canny_image") |
| display(image_grid([raw_image, canny_image], 1, 2)) |
| for i in range(num): |
| img = pipe( |
| prompt=prompt, |
| negative_prompt = negative_prompt, |
| image=canny_image, |
| num_inference_steps=num_inference_steps, |
| controlnet_conditioning_scale=controlnet_conditioning_scale, |
| clip_skip= clip_skip, |
| ).images[0] |
| all_images.append(img) |
| display(image_grid(all_images, 1, num)) |
| ``` |
|
|
|  |
