mirror of https://github.com/opencv/opencv.git
Open Source Computer Vision Library
https://opencv.org/
You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
104 lines
3.7 KiB
104 lines
3.7 KiB
import numpy as np |
|
import cv2 |
|
import video |
|
|
|
help_message = '''USAGE: camshift.py [<video source>] |
|
|
|
Select a bright colored object to track. |
|
|
|
Keys: |
|
ESC - exit |
|
b - toggle back-projected probability visualization |
|
''' |
|
|
|
|
|
class App(object): |
|
def __init__(self, video_src): |
|
self.cam = video.create_capture(video_src) |
|
ret, self.frame = self.cam.read() |
|
cv2.namedWindow('camshift') |
|
cv2.setMouseCallback('camshift', self.onmouse) |
|
|
|
self.selection = None |
|
self.drag_start = None |
|
self.tracking_state = 0 |
|
self.show_backproj = False |
|
|
|
def onmouse(self, event, x, y, flags, param): |
|
x, y = np.int16([x, y]) # BUG |
|
if event == cv2.EVENT_LBUTTONDOWN: |
|
self.drag_start = (x, y) |
|
self.tracking_state = 0 |
|
if self.drag_start: |
|
if flags & cv2.EVENT_FLAG_LBUTTON: |
|
h, w = self.frame.shape[:2] |
|
xo, yo = self.drag_start |
|
x0, y0 = np.maximum(0, np.minimum([xo, yo], [x, y])) |
|
x1, y1 = np.minimum([w, h], np.maximum([xo, yo], [x, y])) |
|
self.selection = None |
|
if x1-x0 > 0 and y1-y0 > 0: |
|
self.selection = (x0, y0, x1, y1) |
|
else: |
|
self.drag_start = None |
|
if self.selection is not None: |
|
self.tracking_state = 1 |
|
|
|
def show_hist(self): |
|
bin_count = self.hist.shape[0] |
|
bin_w = 24 |
|
img = np.zeros((256, bin_count*bin_w, 3), np.uint8) |
|
for i in xrange(bin_count): |
|
h = int(self.hist[i]) |
|
cv2.rectangle(img, (i*bin_w+2, 255), ((i+1)*bin_w-2, 255-h), (int(180.0*i/bin_count), 255, 255), -1) |
|
img = cv2.cvtColor(img, cv2.COLOR_HSV2BGR) |
|
cv2.imshow('hist', img) |
|
|
|
def run(self): |
|
while True: |
|
ret, self.frame = self.cam.read() |
|
vis = self.frame.copy() |
|
hsv = cv2.cvtColor(self.frame, cv2.COLOR_BGR2HSV) |
|
mask = cv2.inRange(hsv, np.array((0, 60, 32)), np.array((180, 255, 255))) |
|
|
|
if self.selection: |
|
x0, y0, x1, y1 = self.selection |
|
self.track_window = (x0, y0, x1-x0, y1-y0) |
|
hsv_roi = hsv[y0:y1, x0:x1] |
|
mask_roi = mask[y0:y1, x0:x1] |
|
hist = cv2.calcHist( [hsv_roi], [0], mask_roi, [16], [0, 180] ) |
|
cv2.normalize(hist, hist, 0, 255, cv2.NORM_MINMAX); |
|
self.hist = hist.reshape(-1) |
|
self.show_hist() |
|
|
|
vis_roi = vis[y0:y1, x0:x1] |
|
cv2.bitwise_not(vis_roi, vis_roi) |
|
vis[mask == 0] = 0 |
|
|
|
if self.tracking_state == 1: |
|
self.selection = None |
|
prob = cv2.calcBackProject([hsv], [0], self.hist, [0, 180], 1) |
|
prob &= mask |
|
term_crit = ( cv2.TERM_CRITERIA_EPS | cv2.TERM_CRITERIA_COUNT, 10, 1 ) |
|
track_box, self.track_window = cv2.CamShift(prob, self.track_window, term_crit) |
|
|
|
if self.show_backproj: |
|
vis[:] = prob[...,np.newaxis] |
|
try: cv2.ellipse(vis, track_box, (0, 0, 255), 2) |
|
except: print track_box |
|
|
|
cv2.imshow('camshift', vis) |
|
|
|
ch = cv2.waitKey(5) |
|
if ch == 27: |
|
break |
|
if ch == ord('b'): |
|
self.show_backproj = not self.show_backproj |
|
|
|
|
|
if __name__ == '__main__': |
|
import sys |
|
try: video_src = sys.argv[1] |
|
except: video_src = video.presets['chess'] |
|
print help_message |
|
App(video_src).run() |
|
|
|
|