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