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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
}
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