divisor.xflux1.util
1# SPDX-License-Identifier:Apache-2.0 2# original XFlux code from https://github.com/TencentARC/FluxKits 3 4import cv2 5import numpy as np 6 7 8def c_crop(image): 9 width, height = image.size 10 new_size = min(width, height) 11 left = (width - new_size) / 2 12 top = (height - new_size) / 2 13 right = (width + new_size) / 2 14 bottom = (height + new_size) / 2 15 return image.crop((left, top, right, bottom)) 16 17 18def pad64(x): 19 return int(np.ceil(float(x) / 64.0) * 64 - x) 20 21 22def HWC3(x): 23 assert x.dtype == np.uint8 24 if x.ndim == 2: 25 x = x[:, :, None] 26 assert x.ndim == 3 27 H, W, C = x.shape 28 assert C == 1 or C == 3 or C == 4 29 if C == 3: 30 return x 31 if C == 1: 32 return np.concatenate([x, x, x], axis=2) 33 if C == 4: 34 color = x[:, :, 0:3].astype(np.float32) 35 alpha = x[:, :, 3:4].astype(np.float32) / 255.0 36 y = color * alpha + 255.0 * (1.0 - alpha) 37 y = y.clip(0, 255).astype(np.uint8) 38 return y 39 40 41def safer_memory(x): 42 # Fix many MAC/AMD problems 43 return np.ascontiguousarray(x.copy()).copy() 44 45 46# https://github.com/Mikubill/sd-webui-controlnet/blob/main/scripts/processor.py#L17 47# Added upscale_method, mode params 48def resize_image_with_pad(input_image, resolution, skip_hwc3=False, mode="edge"): 49 if skip_hwc3: 50 img = input_image 51 else: 52 img = HWC3(input_image) 53 H_raw, W_raw, _ = img.shape # type: ignore 54 if resolution == 0: 55 return img, lambda x: x 56 k = float(resolution) / float(min(H_raw, W_raw)) 57 H_target = int(np.round(float(H_raw) * k)) 58 W_target = int(np.round(float(W_raw) * k)) 59 img = cv2.resize(img, (W_target, H_target), interpolation=cv2.INTER_AREA) # type: ignore 60 H_pad, W_pad = pad64(H_target), pad64(W_target) 61 img_padded = np.pad(img, [[0, H_pad], [0, W_pad], [0, 0]], mode=mode) # type: ignore 62 63 def remove_pad(x): 64 return safer_memory(x[:H_target, :W_target, ...]) 65 66 return safer_memory(img_padded), remove_pad
def
c_crop(image):
def
pad64(x):
def
HWC3(x):
23def HWC3(x): 24 assert x.dtype == np.uint8 25 if x.ndim == 2: 26 x = x[:, :, None] 27 assert x.ndim == 3 28 H, W, C = x.shape 29 assert C == 1 or C == 3 or C == 4 30 if C == 3: 31 return x 32 if C == 1: 33 return np.concatenate([x, x, x], axis=2) 34 if C == 4: 35 color = x[:, :, 0:3].astype(np.float32) 36 alpha = x[:, :, 3:4].astype(np.float32) / 255.0 37 y = color * alpha + 255.0 * (1.0 - alpha) 38 y = y.clip(0, 255).astype(np.uint8) 39 return y
def
safer_memory(x):
def
resize_image_with_pad(input_image, resolution, skip_hwc3=False, mode='edge'):
49def resize_image_with_pad(input_image, resolution, skip_hwc3=False, mode="edge"): 50 if skip_hwc3: 51 img = input_image 52 else: 53 img = HWC3(input_image) 54 H_raw, W_raw, _ = img.shape # type: ignore 55 if resolution == 0: 56 return img, lambda x: x 57 k = float(resolution) / float(min(H_raw, W_raw)) 58 H_target = int(np.round(float(H_raw) * k)) 59 W_target = int(np.round(float(W_raw) * k)) 60 img = cv2.resize(img, (W_target, H_target), interpolation=cv2.INTER_AREA) # type: ignore 61 H_pad, W_pad = pad64(H_target), pad64(W_target) 62 img_padded = np.pad(img, [[0, H_pad], [0, W_pad], [0, 0]], mode=mode) # type: ignore 63 64 def remove_pad(x): 65 return safer_memory(x[:H_target, :W_target, ...]) 66 67 return safer_memory(img_padded), remove_pad