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Removed obsolete python samples #25268 Clean Samples #25006 This PR removes 36 obsolete python samples from the project, as part of an effort to keep the codebase clean and focused on current best practices. Some of these samples will be updated with latest algorithms or will be combined with other existing samples. Removed Samples: > browse.py camshift.py coherence.py color_histogram.py contours.py deconvolution.py dft.py dis_opt_flow.py distrans.py edge.py feature_homography.py find_obj.py fitline.py gabor_threads.py hist.py houghcircles.py houghlines.py inpaint.py kalman.py kmeans.py laplace.py lk_homography.py lk_track.py logpolar.py mosse.py mser.py opt_flow.py plane_ar.py squares.py stitching.py text_skewness_correction.py texture_flow.py turing.py video_threaded.py video_v4l2.py watershed.py These changes aim to improve the repository's clarity and usability by removing examples that are no longer relevant or have been superseded by more up-to-date techniques.
121 lines
3.8 KiB
Python
Executable File
121 lines
3.8 KiB
Python
Executable File
#!/usr/bin/env python
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'''
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Camshift tracker
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================
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This is a demo that shows mean-shift based tracking
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You select a color objects such as your face and it tracks it.
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This reads from video camera (0 by default, or the camera number the user enters)
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[1] http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.14.7673
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Usage:
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------
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camshift.py [<video source>]
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To initialize tracking, select the object with mouse
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Keys:
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-----
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ESC - exit
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b - toggle back-projected probability visualization
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'''
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import numpy as np
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import cv2 as cv
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# local module
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import video
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from video import presets
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class App(object):
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def __init__(self, video_src):
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self.cam = video.create_capture(video_src, presets['cube'])
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_ret, self.frame = self.cam.read()
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cv.namedWindow('camshift')
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cv.setMouseCallback('camshift', self.onmouse)
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self.selection = None
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self.drag_start = None
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self.show_backproj = False
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self.track_window = None
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def onmouse(self, event, x, y, flags, param):
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if event == cv.EVENT_LBUTTONDOWN:
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self.drag_start = (x, y)
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self.track_window = None
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if self.drag_start:
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xmin = min(x, self.drag_start[0])
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ymin = min(y, self.drag_start[1])
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xmax = max(x, self.drag_start[0])
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ymax = max(y, self.drag_start[1])
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self.selection = (xmin, ymin, xmax, ymax)
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if event == cv.EVENT_LBUTTONUP:
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self.drag_start = None
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self.track_window = (xmin, ymin, xmax - xmin, ymax - ymin)
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def show_hist(self):
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bin_count = self.hist.shape[0]
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bin_w = 24
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img = np.zeros((256, bin_count*bin_w, 3), np.uint8)
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for i in range(bin_count):
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h = int(self.hist[i])
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cv.rectangle(img, (i*bin_w+2, 255), ((i+1)*bin_w-2, 255-h), (int(180.0*i/bin_count), 255, 255), -1)
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img = cv.cvtColor(img, cv.COLOR_HSV2BGR)
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cv.imshow('hist', img)
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def run(self):
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while True:
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_ret, self.frame = self.cam.read()
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vis = self.frame.copy()
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hsv = cv.cvtColor(self.frame, cv.COLOR_BGR2HSV)
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mask = cv.inRange(hsv, np.array((0., 60., 32.)), np.array((180., 255., 255.)))
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if self.selection:
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x0, y0, x1, y1 = self.selection
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hsv_roi = hsv[y0:y1, x0:x1]
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mask_roi = mask[y0:y1, x0:x1]
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hist = cv.calcHist( [hsv_roi], [0], mask_roi, [16], [0, 180] )
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cv.normalize(hist, hist, 0, 255, cv.NORM_MINMAX)
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self.hist = hist.reshape(-1)
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self.show_hist()
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vis_roi = vis[y0:y1, x0:x1]
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cv.bitwise_not(vis_roi, vis_roi)
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vis[mask == 0] = 0
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if self.track_window and self.track_window[2] > 0 and self.track_window[3] > 0:
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self.selection = None
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prob = cv.calcBackProject([hsv], [0], self.hist, [0, 180], 1)
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prob &= mask
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term_crit = ( cv.TERM_CRITERIA_EPS | cv.TERM_CRITERIA_COUNT, 10, 1 )
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track_box, self.track_window = cv.CamShift(prob, self.track_window, term_crit)
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if self.show_backproj:
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vis[:] = prob[...,np.newaxis]
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try:
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cv.ellipse(vis, track_box, (0, 0, 255), 2)
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except:
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print(track_box)
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cv.imshow('camshift', vis)
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ch = cv.waitKey(5)
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if ch == 27:
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break
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if ch == ord('b'):
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self.show_backproj = not self.show_backproj
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cv.destroyAllWindows()
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if __name__ == '__main__':
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print(__doc__)
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import sys
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try:
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video_src = sys.argv[1]
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except:
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video_src = 0
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App(video_src).run()
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