File size: 2,912 Bytes
6ee3369
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
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)