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import warnings
import numpy as np
import cv2
UPSCALE_METHODS = ["INTER_NEAREST", "INTER_LINEAR", "INTER_AREA", "INTER_CUBIC", "INTER_LANCZOS4"]
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):
# Fix many MAC/AMD problems
return np.ascontiguousarray(x.copy()).copy()
def get_upscale_method(method_str):
assert method_str in UPSCALE_METHODS, f"Method {method_str} not found in {UPSCALE_METHODS}"
return getattr(cv2, method_str)
def pad64(x):
return int(np.ceil(float(x) / 64.0) * 64 - x)
# https://github.com/Mikubill/sd-webui-controlnet/blob/main/scripts/processor.py#L17
# Added upscale_method, mode params
def resize_image_with_pad(input_image, resolution, upscale_method = "", skip_hwc3=False, mode='edge'):
if skip_hwc3:
img = input_image
else:
img = HWC3(input_image)
H_raw, W_raw, _ = img.shape
if resolution == 0:
return img, lambda x: x
k = float(resolution) / float(min(H_raw, W_raw))
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=get_upscale_method(upscale_method) if k > 1 else cv2.INTER_AREA)
H_pad, W_pad = pad64(H_target), pad64(W_target)
img_padded = np.pad(img, [[0, H_pad], [0, W_pad], [0, 0]], mode=mode)
def remove_pad(x):
return safer_memory(x[:H_target, :W_target, ...])
return safer_memory(img_padded), remove_pad
def common_input_validate(input_image, output_type, **kwargs):
if "img" in kwargs:
warnings.warn("img is deprecated, please use `input_image=...` instead.", DeprecationWarning)
input_image = kwargs.pop("img")
if "return_pil" in kwargs:
warnings.warn("return_pil is deprecated. Use output_type instead.", DeprecationWarning)
output_type = "pil" if kwargs["return_pil"] else "np"
if type(output_type) is bool:
warnings.warn("Passing `True` or `False` to `output_type` is deprecated and will raise an error in future versions")
if output_type:
output_type = "pil"
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"
return (input_image, output_type)
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