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2022-10-11
简简单单用OpenCV让一只小猫咪变成奶凶奶凶的科技猫
重磅干货,第一时间送达
导读
Hi,大家好,今天给各位读者分享一个比较酷炫的特效。
下面将会一步一步演示,并 详细分析内部的原因,会尽量用清晰直观的方式,让大家去理解,以收获更多的知识!
效果展示
首先看一下目标效果:
将一只可爱的小猫猫变成一只充满科技感奶凶的猫猫!
原图
效果图
思路详解 & 代码实现
一、思路讲解
Gabor 滤波器特征检测对特征信息进行重复赋值使用滑动条调整参数
1、Gabor 滤波器特征检测
Gabor 变换是一种短时加窗Fourier变换(简单理解起来就是在特定时间窗内做Fourier变换),是短时傅里叶变换中窗函数取为高斯函数时的一种特殊情况。因此,Gabor滤波器可以在频域上不同尺度、不同方向上提取相关的特征。另外,Gabor函数与人眼的作用相仿,所以经常用作纹理识别上,并取得了较好的效果。在二维空间中,使用一个三角函数(a)(如正弦函数)与一个高斯函数(b)叠加,我们得到了一个Gabor滤波器(c)。如下图所示:
二维 Gab or函数的数学表达式如下:
公式比较抽象,下面有基于不同 θ 值的效果图
其他参数的示例可以参考:
在本文中设置了 16 个不同的滤波器角度,分别检测不同角度
经过每个滤波器处理之后的效果(高能,把我看晕了):
上面基于不同gabar 滤波器 θ 值设定输出的结果,这里仅显示 前四个的结果,上图可能不方便观察,但是连续播放时,可以清楚看到每个滤波器输出的结果时存在差异,主要表现在能够检测到不同角度的纹理。
# 创建滤波器(们)def build_filters(a=31): filters = [] ksize = a print(ksize) # 此处创建16个滤波器,只有getGaborKernel的第三个参数theta不同。 for theta in np.arange(0, np.pi, np.pi / 16): kern = cv.getGaborKernel((ksize, ksize), 4.0, theta, 10.0, 0.5, 0, ktype=cv.CV_32F) kern /= 1.5*kern.sum() filters.append(kern)
2、对特征信息进行重复赋值
对使用不同参数(这里仅设置不同的 θ 角)的gabor滤波器检测到的特征(主要毛发等),然后对这些特征重复作为最终输出的结果
这里需要介绍的一个函数 np.maximum,
import numpy as npa =[-5,-4,-3,-2,-1,0,1,2,3,4,5]>>> np.maximum(a,0)# 输出 array([0, 0, 0, 0, 0, 0, 1, 2, 3, 4, 5])
np.maximum 对参数中对应位置的值进行比较,输出较大的值作为最终的结果。
在曲线上表现形式如上图所示,那么对于一张图片又是如何呢?
曲线都是一维的情况,当我们这里处理的是图片时,此时numpy 处理的是三个通道的值,原理还是一样对应位置进行比较。
更加具体的来说,一张图片可以看成是 三通道的, RGB, 为了便于理解,我们假设取其中一个通道 例如 R 通道的值进行比较,那么最终的输出结果,一定是所有结果处理完(不同参数)之后 ,R 通道值最大的结果,同理可以对 G 通道和 B 通道也是 如此,因此最终的输出结果显示的颜色会比较鲜艳,比较亮。
# 重新赋值过程# 将不同滤波器处理的结果,经过 np.maximum 输出每个位置最亮的值 def process(img, filters): # zeros_like:返回和输入大小相同,类型相同,用0填满的数组 accum = np.zeros_like(img) for kern in filters: fimg = cv.filter2D(img, cv.CV_8UC3, kern) # maximum:逐位比较取其大 np.maximum(accum, fimg, accum) return accum
知识点汇总和代码分享
本文简单介绍了 Gabor 滤波器,通过设置不同的滤波器参数来得到我们希望检测的特征,然后对特征进一步出来,展示出来较酷炫的效果。在代码中,我们还会用到 滑动条 以便更加轻松的调节参数。
具体的代码,在下面的内容中分享
后续会将代码和素材更新到项目中:__future__ import print_functionimport numpy as npimport cv2 as cvfrom multiprocessing.pool import ThreadPool# 创建滤波器(们)def build_filters(a=31): filters = [] ksize = a print(ksize) # 此处创建16个滤波器,只有getGaborKernel的第三个参数theta不同。 for theta in np.arange(0, np.pi, np.pi / 16): kern = cv.getGaborKernel((ksize, ksize), 4.0, theta, 10.0, 0.5, 0, ktype=cv.CV_32F) kern /= 1.5*kern.sum() filters.append(kern) return filters# 单线程处理def process(img, filters): # zeros_like:返回和输入大小相同,类型相同,用0填满的数组 accum = np.zeros_like(img) for kern in filters: fimg = cv.filter2D(img, cv.CV_8UC3, kern) #cv.imshow('fimg',fimg) #cv.waitKey(0) # maximum:逐位比较取其大 np.maximum(accum, fimg, accum) return accum# 多线程处理,threadn = 8def process_threaded(img, filters, threadn = 8): accum = np.zeros_like(img) def f(kern): return cv.filter2D(img, cv.CV_8UC3, kern) pool = ThreadPool(processes=threadn) for fimg in pool.imap_unordered(f, filters): np.maximum(accum, fimg, accum) return accumdef nothing(x): passif __name__ == '__main__': import sys from common import Timer # 输出文件开头由''' '''包含的注释内容 print(__doc__) try: img_fn = sys.argv[1] except: img_fn = 'cat1.jpg' img = cv.imread(img_fn) # 判断图片是否读取成功 if img is None: print('Failed to load image file:', img_fn) sys.exit(1) # 增加滑动条 cv.namedWindow('result') cv.createTrackbar('a', 'result', 0, 60, nothing) tmp =-1 while True: a = cv.getTrackbarPos('a', 'result') print("a:",a) if a == tmp: cv.imshow('result', res2) if cv.waitKey(1) == 27: break if cv.waitKey(1) == ord('s'): cv.imwrite(str(a)+'.jpg', res2) continue tmp = a filters = build_filters(a) with Timer('running single-threaded'): res1 = process(img, filters) with Timer('running multi-threaded'): res2 = process_threaded(img, filters) print('res1 == res2: ', (res1 == res2).all()) # cv.imshow('img', img) cv.imshow('result', res2) if cv.waitKey(1) == 27: break # cv.destroyAllWindows()
还需要将下面的代码保存为 common.py
#!/usr/bin/env python'''This module contains some common routines used by other samples.'''# Python 2/3 compatibilityfrom __future__ import print_functionimport sysPY3 = sys.version_info[0] == 3if PY3: from functools import reduceimport numpy as npimport cv2 as cv# built-in modulesimport osimport itertools as itfrom contextlib import contextmanagerimage_extensions = ['.bmp', '.jpg', '.jpeg', '.png', '.tif', '.tiff', '.pbm', '.pgm', '.ppm']class Bunch(object): def __init__(self, **kw): self.__dict__.update(kw) def __str__(self): return str(self.__dict__)def splitfn(fn): path, fn = os.path.split(fn) name, ext = os.path.splitext(fn) return path, name, extdef anorm2(a): return (a*a).sum(-1)def anorm(a): return np.sqrt( anorm2(a) )def homotrans(H, x, y): xs = H[0, 0]*x + H[0, 1]*y + H[0, 2] ys = H[1, 0]*x + H[1, 1]*y + H[1, 2] s = H[2, 0]*x + H[2, 1]*y + H[2, 2] return xs/s, ys/sdef to_rect(a): a = np.ravel(a) if len(a) == 2: a = (0, 0, a[0], a[1]) return np.array(a, np.float64).reshape(2, 2)def rect2rect_mtx(src, dst): src, dst = to_rect(src), to_rect(dst) cx, cy = (dst[1] - dst[0]) / (src[1] - src[0]) tx, ty = dst[0] - src[0] * (cx, cy) M = np.float64([[ cx, 0, tx], [ 0, cy, ty], [ 0, 0, 1]]) return Mdef lookat(eye, target, up = (0, 0, 1)): fwd = np.asarray(target, np.float64) - eye fwd /= anorm(fwd) right = np.cross(fwd, up) right /= anorm(right) down = np.cross(fwd, right) R = np.float64([right, down, fwd]) tvec = -np.dot(R, eye) return R, tvecdef mtx2rvec(R): w, u, vt = cv.SVDecomp(R - np.eye(3)) p = vt[0] + u[:,0]*w[0] # same as np.dot(R, vt[0]) c = np.dot(vt[0], p) s = np.dot(vt[1], p) axis = np.cross(vt[0], vt[1]) return axis * np.arctan2(s, c)def draw_str(dst, target, s): x, y = target cv.putText(dst, s, (x+1, y+1), cv.FONT_HERSHEY_PLAIN, 1.0, (0, 0, 0), thickness = 2, lineType=cv.LINE_AA) cv.putText(dst, s, (x, y), cv.FONT_HERSHEY_PLAIN, 1.0, (255, 255, 255), lineType=cv.LINE_AA)class Sketcher: def __init__(self, windowname, dests, colors_func): self.prev_pt = None self.windowname = windowname self.dests = dests self.colors_func = colors_func self.dirty = False self.show() cv.setMouseCallback(self.windowname, self.on_mouse) def show(self): cv.imshow(self.windowname, self.dests[0]) def on_mouse(self, event, x, y, flags, param): pt = (x, y) if event == cv.EVENT_LBUTTONDOWN: self.prev_pt = pt elif event == cv.EVENT_LBUTTONUP: self.prev_pt = None if self.prev_pt and flags & cv.EVENT_FLAG_LBUTTON: for dst, color in zip(self.dests, self.colors_func()): cv.line(dst, self.prev_pt, pt, color, 5) self.dirty = True self.prev_pt = pt self.show()# palette data from matplotlib/_cm.py_jet_data = {'red': ((0., 0, 0), (0.35, 0, 0), (0.66, 1, 1), (0.89,1, 1), (1, 0.5, 0.5)), 'green': ((0., 0, 0), (0.125,0, 0), (0.375,1, 1), (0.64,1, 1), (0.91,0,0), (1, 0, 0)), 'blue': ((0., 0.5, 0.5), (0.11, 1, 1), (0.34, 1, 1), (0.65,0, 0), (1, 0, 0))}cmap_data = { 'jet' : _jet_data }def make_cmap(name, n=256): data = cmap_data[name] xs = np.linspace(0.0, 1.0, n) channels = [] eps = 1e-6 for ch_name in ['blue', 'green', 'red']: ch_data = data[ch_name] xp, yp = [], [] for x, y1, y2 in ch_data: xp += [x, x+eps] yp += [y1, y2] ch = np.interp(xs, xp, yp) channels.append(ch) return np.uint8(np.array(channels).T*255)def nothing(*arg, **kw): passdef clock(): return cv.getTickCount() / cv.getTickFrequency()@contextmanagerdef Timer(msg): print(msg, '...',) start = clock() try: yield finally: print("%.2f ms" % ((clock()-start)*1000))class StatValue: def __init__(self, smooth_coef = 0.5): self.value = None self.smooth_coef = smooth_coef def update(self, v): if self.value is None: self.value = v else: c = self.smooth_coef self.value = c * self.value + (1.0-c) * vclass RectSelector: def __init__(self, win, callback): self.win = win self.callback = callback cv.setMouseCallback(win, self.onmouse) self.drag_start = None self.drag_rect = None def onmouse(self, event, x, y, flags, param): x, y = np.int16([x, y]) # BUG if event == cv.EVENT_LBUTTONDOWN: self.drag_start = (x, y) return if self.drag_start: if flags & cv.EVENT_FLAG_LBUTTON: xo, yo = self.drag_start x0, y0 = np.minimum([xo, yo], [x, y]) x1, y1 = np.maximum([xo, yo], [x, y]) self.drag_rect = None if x1-x0 > 0 and y1-y0 > 0: self.drag_rect = (x0, y0, x1, y1) else: rect = self.drag_rect self.drag_start = None self.drag_rect = None if rect: self.callback(rect) def draw(self, vis): if not self.drag_rect: return False x0, y0, x1, y1 = self.drag_rect cv.rectangle(vis, (x0, y0), (x1, y1), (0, 255, 0), 2) return True @property def dragging(self): return self.drag_rect is not Nonedef grouper(n, iterable, fillvalue=None): '''grouper(3, 'ABCDEFG', 'x') --> ABC DEF Gxx''' args = [iter(iterable)] * n if PY3: output = it.zip_longest(fillvalue=fillvalue, *args) else: output = it.izip_longest(fillvalue=fillvalue, *args) return outputdef mosaic(w, imgs): '''Make a grid from images. w -- number of grid columns imgs -- images (must have same size and format) ''' imgs = iter(imgs) if PY3: img0 = next(imgs) else: img0 = imgs.next() pad = np.zeros_like(img0) imgs = it.chain([img0], imgs) rows = grouper(w, imgs, pad) return np.vstack(map(np.hstack, rows))def getsize(img): h, w = img.shape[:2] return w, hdef mdot(*args): return reduce(np.dot, args)def draw_keypoints(vis, keypoints, color = (0, 255, 255)): for kp in keypoints: x, y = kp.pt cv.circle(vis, (int(x), int(y)), 2, color)
最后
本文详细分析如何实现一直科技猫,同样可以用于你想要测试的图片素材上
感谢看到这里的小伙伴,希望能给个三连支持一下,周末还在努力的打工人!下期见
参考文献:
http://aas--/fileZDHXB/journal/article/zdhxb/2007/5/PDF/070502.pdfhttps://zhuanlan.zhihu.com/p/33311267
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