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CpicImgSim/utils.py

+import numpy as np
+import scipy.ndimage as nd
+import logging
+import random
+# DO NOT IMPORT CPICIMGSIM MODULES HERE
+
+
+class Logger(object):
+    def __init__(self, filename, level='INFO'):
+        self.logger = logging.getLogger('cpism_log')
+        self.logger.setLevel(logging.DEBUG)
+
+        shinfo = logging.StreamHandler()
+        onlyinfo = logging.Filter()
+        onlyinfo.filter = lambda record: (record.levelno < logging.WARNING)
+        fmtstr = '%(message)s'
+        shinfo.setFormatter(logging.Formatter(fmtstr))  # 设置屏幕上显示的格式
+        shinfo.setLevel(logging.INFO)
+        shinfo.addFilter(onlyinfo)
+
+        sh = logging.StreamHandler()
+        fmtstr = '!%(levelname)s!: %(message)s [%(filename)s - %(funcName)s (line: %(lineno)d)]: '
+        sh.setFormatter(logging.Formatter(fmtstr))  # 设置屏幕上显示的格式
+        sh.setLevel(logging.WARNING)
+
+        th = logging.FileHandler(filename)  # 往文件里写入#指定间隔时间自动生成文件的处理器
+
+        fmtstr = '%(asctime)s %(filename)s [%(funcName)s] - %(levelname)s: %(message)s'
+        th.setFormatter(logging.Formatter(fmtstr))  # 设置文件里写入的格式
+        th.setLevel(logging.__dict__.get(level.upper()))
+        self.logger.addHandler(shinfo)
+        self.logger.addHandler(sh)
+        self.logger.addHandler(th)
+
+
+def random_seed_select(seed=-1):
+    """
+    Select a random seed for numpy.random and return it.
+    """
+    if seed == -1:
+        seed = random.randint(0, 2**32-1)
+    np.random.seed(seed)
+    return seed
+
+
+def region_replace(
+    background: np.ndarray,
+    front: np.ndarray,
+    shift: list,
+    bmask: float = 1.0,
+    fmask: float = 1.0,
+    padded_in: bool = False,
+    padded_out: bool = False,
+    subpix: bool = False
+):
+    """
+    replace a region of the background with the front image.
+
+    Parameters
+    ----------
+    background: np.ndarray
+        The background image.
+    front: np.ndarray
+        The front image.
+    shift: list
+        The [x, y] shift of the front image. Unit: pixel.
+        Relative to the lower-left corner of the background image.
+        [0, 0] means the lower-left corner of the front image is at the lower-left corner of the background image. 
+    bmask: float
+        The mask of the background image. Default: 1.0
+        0.0 means the background image is masked.
+        1.0 means the background image is fully added.
+    fmask: float
+        The mask of the front image. Default: 1.0
+        0.0 means the front image is masked (not added).
+        1.0 means the front image is fully added.
+    padded_in: bool
+        Whether the input background image is padded. Default: False
+        In the function, the background image is padded by the size of the front image.
+        If True, means the background image is padded.
+    padded_out: bool
+        Whether the output image is padded. Default: False
+        In the function, the background image is padded by the size of the front image.
+        If True, means the output image is padded.
+        padded_in and padded_out are designed for the case that replace_region fuction is called multiple times.
+    subpix: bool
+        Whether the shift is subpixel. Default: False
+        If True, the shift is subpixel, using scipy.ndimage.shift to shift the front image.
+        If False, the shift is integer, using numpy slicing to shift the front image.
+
+    Returns
+    -------
+    np.ndarray
+        The output image.
+        shape = background.shape if padded_out = False
+        shape = background.shape + 2 * front.shape if padded_out = True
+    """
+
+    int_shift = np.array(shift).astype(int)
+    b_sz = np.array(background.shape)
+    f_sz = np.array(front.shape)
+
+    if padded_in:
+        padded = background
+        b_sz = b_sz - f_sz * 2
+    else:
+        padded = np.pad(background, ((f_sz[0], f_sz[0]), (f_sz[1], f_sz[1])))
+
+    if np.any((int_shift < -b_sz) | (int_shift > b_sz)):
+        if padded_out:
+            return padded
+        return background
+
+    if subpix:
+        subs = np.array(shift) - int_shift
+        front = nd.shift(front, (subs[0], subs[1]))
+
+    int_shift += f_sz
+    roi_y = int_shift[1]
+    roi_x = int_shift[0]
+    padded[roi_y: roi_y+f_sz[0], roi_x:roi_x+f_sz[1]] *= bmask
+    padded[roi_y: roi_y+f_sz[0], roi_x:roi_x+f_sz[1]] += fmask * front
+
+    if padded_out:
+        return padded
+
+    return padded[f_sz[0]:b_sz[0]+f_sz[0], f_sz[1]:b_sz[1]+f_sz[1]]