from controlnet_aux import ( CannyDetector, ContentShuffleDetector, HEDdetector, LineartAnimeDetector, LineartDetector, MediapipeFaceDetector, MidasDetector, MLSDdetector, NormalBaeDetector, OpenposeDetector, PidiNetDetector, SamDetector, ) import numpy as np import cv2 def pad64(x): return int(np.ceil(float(x) / 64.0) * 64 - x) def HWC3(x): assert x.dtype == np.uint8 if x.ndim == 2: x = x[:, :, None] assert x.ndim == 3 H, W, C = x.shape assert C == 1 or C == 3 or C == 4 if C == 3: return x if C == 1: return np.concatenate([x, x, x], axis=2) if C == 4: color = x[:, :, 0:3].astype(np.float32) alpha = x[:, :, 3:4].astype(np.float32) / 255.0 y = color * alpha + 255.0 * (1.0 - alpha) y = y.clip(0, 255).astype(np.uint8) return y def safer_memory(x): return np.ascontiguousarray(x.copy()).copy() def resize_image_with_pad(input_image, resolution, skip_hwc3=False): if skip_hwc3: img = input_image else: img = HWC3(input_image) H_raw, W_raw, _ = img.shape k = float(resolution) / float(min(H_raw, W_raw)) interpolation = cv2.INTER_CUBIC if k > 1 else cv2.INTER_AREA H_target = int(np.round(float(H_raw) * k)) W_target = int(np.round(float(W_raw) * k)) img = cv2.resize(img, (W_target, H_target), interpolation=interpolation) H_pad, W_pad = pad64(H_target), pad64(W_target) img_padded = np.pad(img, [[0, H_pad], [0, W_pad], [0, 0]], mode='edge') def remove_pad(x): return safer_memory(x[:H_target, :W_target]) return safer_memory(img_padded), remove_pad def scribble_xdog(img, res=512, thr_a=32, **kwargs): img, remove_pad = resize_image_with_pad(img, res) g1 = cv2.GaussianBlur(img.astype(np.float32), (0, 0), 0.5) g2 = cv2.GaussianBlur(img.astype(np.float32), (0, 0), 5.0) dog = (255 - np.min(g2 - g1, axis=2)).clip(0, 255).astype(np.uint8) result = np.zeros_like(img, dtype=np.uint8) result[2 * (255 - dog) > thr_a] = 255 return remove_pad(result), True def none_preprocces(image_path:str): return Image.open(image_path) PREPROCCES_DICT = { "Hed": HEDdetector.from_pretrained("lllyasviel/Annotators"), "Midas": MidasDetector.from_pretrained("lllyasviel/Annotators"), "MLSD": MLSDdetector.from_pretrained("lllyasviel/Annotators"), "Openpose": OpenposeDetector.from_pretrained("lllyasviel/Annotators"), "PidiNet": PidiNetDetector.from_pretrained("lllyasviel/Annotators"), "NormalBae": NormalBaeDetector.from_pretrained("lllyasviel/Annotators"), "Lineart": LineartDetector.from_pretrained("lllyasviel/Annotators"), "LineartAnime": LineartAnimeDetector.from_pretrained( "lllyasviel/Annotators" ), "Canny": CannyDetector(), "ContentShuffle": ContentShuffleDetector(), "MediapipeFace": MediapipeFaceDetector(), "ScribbleXDOG": scribble_xdog, "None": none_preprocces }