| import warnings | |
| import cv2 | |
| import numpy as np | |
| from PIL import Image | |
| from ..util import HWC3, resize_image | |
| class CannyDetector: | |
| def __call__(self, input_image=None, low_threshold=100, high_threshold=200, detect_resolution=512, image_resolution=512, output_type=None, **kwargs): | |
| if "img" in kwargs: | |
| warnings.warn("img is deprecated, please use `input_image=...` instead.", DeprecationWarning) | |
| input_image = kwargs.pop("img") | |
| if input_image is None: | |
| raise ValueError("input_image must be defined.") | |
| if not isinstance(input_image, np.ndarray): | |
| input_image = np.array(input_image, dtype=np.uint8) | |
| output_type = output_type or "pil" | |
| else: | |
| output_type = output_type or "np" | |
| input_image = HWC3(input_image) | |
| input_image = resize_image(input_image, detect_resolution) | |
| detected_map = cv2.Canny(input_image, low_threshold, high_threshold) | |
| detected_map = HWC3(detected_map) | |
| img = resize_image(input_image, image_resolution) | |
| H, W, C = img.shape | |
| detected_map = cv2.resize(detected_map, (W, H), interpolation=cv2.INTER_LINEAR) | |
| if output_type == "pil": | |
| detected_map = Image.fromarray(detected_map) | |
| return detected_map | |