mirror of https://github.com/opencv/opencv.git
Open Source Computer Vision Library
https://opencv.org/
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117 lines
3.5 KiB
117 lines
3.5 KiB
import numpy as np |
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import cv2 |
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import os |
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image_extensions = ['.bmp', '.jpg', '.jpeg', '.png', '.tif', '.tiff', '.pbm', '.pgm', '.ppm'] |
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def splitfn(fn): |
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path, fn = os.path.split(fn) |
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name, ext = os.path.splitext(fn) |
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return path, name, ext |
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def anorm2(a): |
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return (a*a).sum(-1) |
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def anorm(a): |
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return np.sqrt( anorm2(a) ) |
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def homotrans(H, x, y): |
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xs = H[0, 0]*x + H[0, 1]*y + H[0, 2] |
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ys = H[1, 0]*x + H[1, 1]*y + H[1, 2] |
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s = H[2, 0]*x + H[2, 1]*y + H[2, 2] |
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return xs/s, ys/s |
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def to_rect(a): |
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a = np.ravel(a) |
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if len(a) == 2: |
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a = (0, 0, a[0], a[1]) |
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return np.array(a, np.float64).reshape(2, 2) |
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def rect2rect_mtx(src, dst): |
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src, dst = to_rect(src), to_rect(dst) |
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cx, cy = (dst[1] - dst[0]) / (src[1] - src[0]) |
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tx, ty = dst[0] - src[0] * (cx, cy) |
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M = np.float64([[ cx, 0, tx], |
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[ 0, cy, ty], |
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[ 0, 0, 1]]) |
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return M |
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def lookat(eye, target, up = (0, 0, 1)): |
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fwd = np.asarray(target, np.float64) - eye |
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fwd /= anorm(fwd) |
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right = np.cross(fwd, up) |
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right /= anorm(right) |
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down = np.cross(fwd, right) |
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R = np.float64([right, down, fwd]) |
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tvec = -np.dot(R, eye) |
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return R, tvec |
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def mtx2rvec(R): |
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w, u, vt = cv2.SVDecomp(R - np.eye(3)) |
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p = vt[0] + u[:,0]*w[0] # same as np.dot(R, vt[0]) |
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c = np.dot(vt[0], p) |
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s = np.dot(vt[1], p) |
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axis = np.cross(vt[0], vt[1]) |
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return axis * np.arctan2(s, c) |
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def draw_str(dst, (x, y), s): |
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cv2.putText(dst, s, (x+1, y+1), cv2.FONT_HERSHEY_PLAIN, 1.0, (0, 0, 0), thickness = 2, linetype=cv2.CV_AA) |
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cv2.putText(dst, s, (x, y), cv2.FONT_HERSHEY_PLAIN, 1.0, (255, 255, 255), linetype=cv2.CV_AA) |
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class Sketcher: |
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def __init__(self, windowname, dests, colors_func): |
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self.prev_pt = None |
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self.windowname = windowname |
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self.dests = dests |
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self.colors_func = colors_func |
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self.dirty = False |
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self.show() |
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cv2.setMouseCallback(self.windowname, self.on_mouse) |
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def show(self): |
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cv2.imshow(self.windowname, self.dests[0]) |
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def on_mouse(self, event, x, y, flags, param): |
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pt = (x, y) |
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if event == cv2.EVENT_LBUTTONDOWN: |
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self.prev_pt = pt |
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if self.prev_pt and flags & cv2.EVENT_FLAG_LBUTTON: |
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for dst, color in zip(self.dests, self.colors_func()): |
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cv2.line(dst, self.prev_pt, pt, color, 5) |
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self.dirty = True |
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self.prev_pt = pt |
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self.show() |
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else: |
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self.prev_pt = None |
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# palette data from matplotlib/_cm.py |
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_jet_data = {'red': ((0., 0, 0), (0.35, 0, 0), (0.66, 1, 1), (0.89,1, 1), |
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(1, 0.5, 0.5)), |
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'green': ((0., 0, 0), (0.125,0, 0), (0.375,1, 1), (0.64,1, 1), |
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(0.91,0,0), (1, 0, 0)), |
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'blue': ((0., 0.5, 0.5), (0.11, 1, 1), (0.34, 1, 1), (0.65,0, 0), |
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(1, 0, 0))} |
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cmap_data = { 'jet' : _jet_data } |
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def make_cmap(name, n=256): |
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data = cmap_data[name] |
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xs = np.linspace(0.0, 1.0, n) |
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channels = [] |
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eps = 1e-6 |
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for ch_name in ['blue', 'green', 'red']: |
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ch_data = data[ch_name] |
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xp, yp = [], [] |
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for x, y1, y2 in ch_data: |
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xp += [x, x+eps] |
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yp += [y1, y2] |
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ch = np.interp(xs, xp, yp) |
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channels.append(ch) |
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return np.uint8(np.array(channels).T*255) |
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def nothing(*arg, **kw): |
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pass |
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def clock(): |
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return cv2.getTickCount() / cv2.getTickFrequency() |