#AWC=cap.get(cv2.CAP_PROP_AUTOFOCUS)
#AWC=cap.get(cv2.CAP_PROP_IOS_DEVICE_WHITEBALANCE)
#print AWC
return cap
if __name__ == '__main__':
from fps import FPS
fps = FPS().start()
cap = cv2.VideoCapture(1)
#cap.set(cv2.CAP_PROP_FRAME_WIDTH, 640);
#cap.set(cv2.CAP_PROP_FRAME_HEIGHT, 480);
time.sleep(2)
#print cap.set(cv2.CAP_PROP_WHITE_BALANCE_BLUE_U,4000)
#AWC=cap.set(cv2.CAP_PROP_FPS,0)
while True:
_, frame = cap.read()
#print cap.get(cv2.CAP_PROP_XI_AUTO_WB)
f = fps.approx_compute()
cv2.putText(frame, 'FPS {:.3f}'.format(f), (10, 10),
cv2.FONT_HERSHEY_SIMPLEX, 0.3, (255, 255, 255), 1,
cv2.LINE_AA)
cv2.imshow('test', frame)
ch = cv2.waitKey(2)
if ch == 27:
break
if ch == ord('r'):
fps.reset()
cap.release()
class App(object):
def __init__(self, video_src):
#树莓派ip
#self.server_address='rtmp://localhost/dji/stream.h264'
#self.server_address='rtmp://127.0.0.1:1935/dji'
self.server_address = 'http://192.168.40.146:8000/stream.mjpg'
#self.server_address='rtsp://:192.168.40.118/1'
#self.server_address=0
#self.server_address='udp://@:8000 --demux=h264'
#self.cam = video.create_capture(self.server_address)
self.cam = WebcamVideoStream(self.server_address).start()
ret, self.frame = self.cam.read()
self.fish_cali = fish_calibration(self.frame)
self.drag_start = None
self.list_camshift = []
self.show_backproj = False
self.newcamshift = None
self.selection = None
self.lock = False
self.mdp = MyUdp()
#self.count=0
self.light = self.get_light()
self.swicht = False
#self.list_camshift.append(self.get_car('red.jpg',0))
#self.list_camshift.append(self.get_car('green.jpg',1))
self.fps = FPS().start()
#wifi模块IP
self.mdp.client_address = ('192.168.40.31', 8899)
cv2.namedWindow('TUCanshift')
cv2.setMouseCallback('TUCanshift', self.onmouse)
def onmouse(self, event, x, y, flags, param):
if self.lock:
if event == cv2.EVENT_RBUTTONDOWN:
self.pop_camshift()
return
if event == cv2.EVENT_LBUTTONDOWN:
self.drag_start = (x, y)
self.newcamshift = mycamshift()
if self.drag_start:
xmin = min(x, self.drag_start[0])
ymin = min(y, self.drag_start[1])
xmax = max(x, self.drag_start[0])
ymax = max(y, self.drag_start[1])
self.selection = (xmin, ymin, xmax, ymax)
if event == cv2.EVENT_LBUTTONUP:
self.fps.reset()
self.drag_start = None
if self.newcamshift is not None and self.newcamshift.getHist(
) is not None:
self.newcamshift.ID = len(self.list_camshift)
self.list_camshift.append(self.newcamshift)
self.newcamshift = None
self.selection = None
def pop_camshift(self):
if (len(self.list_camshift) < 1):
return True
cv2.destroyWindow(str(len(self.list_camshift) - 1))
cv2.destroyWindow('%s%s' % ('cam', str(len(self.list_camshift) - 1)))
self.list_camshift.pop()
return False
@staticmethod
def creat_camshift_from_img(hsv):
camshift = mycamshift()
mask = np.ones((hsv.shape[0], hsv.shape[1]), dtype=np.uint8)
camshift.preProcess(hsv, mask, (0, 0, hsv.shape[1], hsv.shape[0]), 32)
return camshift
def get_light(self):
temp = mycamshift()
temp.prProcess_light(self.frame)
temp.ID = 99
return temp
def get_car(self, file, ID):
img = cv2.imread(file, cv2.IMREAD_UNCHANGED)
img = cv2.resize(img, (self.frame.shape[1], self.frame.shape[0]))
hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
temp = App.creat_camshift_from_img(hsv)
cv2.imshow(str(ID), temp.getHist())
temp.ID = ID
return temp
def run(self):
while True:
if not (self.cam.renew and self.cam.grabbed):
continue
ret, self.frame = self.cam.read()
#self.frame=cv2.GaussianBlur(self.frame,(5,5),2)
self.frame = cv2.medianBlur(self.frame, 5)
#self.frame=self.fish_cali.cali(self.frame)
imshow_vis = self.frame.copy()
hsv = cv2.cvtColor(self.frame, cv2.COLOR_BGR2HSV)
mask = mycamshift.filte_background_color(hsv,
offset1=16,
offset2=40,
iterations=3)
if self.newcamshift is not None:
if self.newcamshift.preProcess(hsv, mask, self.selection, 16):
cv2.imshow(str(ll), self.newcamshift.getHist())
self.lock = False
ll = len(self.list_camshift)
if ll > 0:
light_gray = cv2.cvtColor(self.frame, cv2.COLOR_BGR2GRAY)
mean, temp = cv2.threshold(light_gray, 0, 255,
cv2.THRESH_BINARY + cv2.THRESH_OTSU)
thresh = (255 - mean) * 0.8 + mean
if thresh > 230:
thresh = 230
_, light_gray = cv2.threshold(light_gray, thresh, 255,
cv2.THRESH_BINARY)
light_gray = cv2.morphologyEx(light_gray,
cv2.MORPH_OPEN,
cv2.getStructuringElement(
cv2.MORPH_ELLIPSE, (5, 5)),
iterations=2,
borderType=cv2.BORDER_REPLICATE)
cv2.imshow('light', light_gray)
track_box = [self.light.go_once_gray(light_gray)]
for x in self.list_camshift:
track_box.append(x.go_once(hsv, mask))
n = len(track_box)
#if n>2:
if n > 2:
p3 = track_box[0]
p1, p2 = track_box[n - 2:]
try:
p1 = p1[0]
except:
p1 = None
try:
p2 = p2[0]
except:
p2 = None
try:
p3 = p3[0]
except:
p3 = None
if p1 and p2:
try:
#snap(img,p1,p2,障碍侦测范围，障碍侦测宽度，微调：避免将车头识别为障碍)
theta, D, dst = snap(mask, p1, p2, 5.0, 2.3, 2.1,
2.9)
dst = cv2.resize(dst, (400, 200))
cv2.imshow('snap', dst)
if theta is not None:
mes = (int(theta), int(D))
self.mdp.send_message('avoid', mes)
print('Block ahead')
cv2.putText(imshow_vis,
'Block ahead:%s,%s' % mes,
(10, 230),
cv2.FONT_HERSHEY_SIMPLEX, 1,
(255, 255, 255), 1, cv2.LINE_AA)
print(mes)
elif p3:
t, d = get_direction(p1, p2, p3)
mes = (int(t), int(d))
self.mdp.send_message('guidance', mes)
print('guidance')
cv2.putText(imshow_vis, 'Guidance:%s,%s' % mes,
(10, 230),
cv2.FONT_HERSHEY_SIMPLEX, 1,
(255, 255, 255), 1, cv2.LINE_AA)
print mes
else:
cv2.putText(imshow_vis, 'Taget LOST',
(10, 230),
cv2.FONT_HERSHEY_SIMPLEX, 1,
(255, 255, 255), 1, cv2.LINE_AA)
self.mdp.send_message('lost')
except:
cv2.putText(imshow_vis, '0/0 is error', (10, 230),
cv2.FONT_HERSHEY_SIMPLEX, 1,
(255, 255, 255), 1, cv2.LINE_AA)
self.mdp.send_message('lost')
else:
cv2.putText(imshow_vis, 'Wait for START', (10, 230),
cv2.FONT_HERSHEY_SIMPLEX, 1,
(255, 255, 255), 1, cv2.LINE_AA)
self.mdp.send_message('lost')
else:
cv2.putText(imshow_vis, 'Wait for START', (10, 230),
cv2.FONT_HERSHEY_SIMPLEX, 1, (255, 255, 255),
1, cv2.LINE_AA)
#self.mdp.send_message('lost')
prob = self.list_camshift[ll - 1].prob
if self.show_backproj and prob is not None:
self.frame = prob[..., np.newaxis]
for x in track_box:
try:
cv2.ellipse(imshow_vis, x, (0, 0, 255), 2)
pts = cv2.boxPoints(x)
pts = np.int0(pts)
cv2.polylines(imshow_vis, [pts], True, 255, 2)
except:
pass
else:
cv2.putText(imshow_vis, 'Wait for START', (10, 230),
cv2.FONT_HERSHEY_SIMPLEX, 1, (255, 255, 255), 1,
cv2.LINE_AA)
#self.mdp.send_message('lost')
self.lock = True
if self.selection is not None:
x0, y0, x1, y1 = self.selection
vis_roi = self.frame[y0:y1, x0:x1]
cv2.bitwise_not(vis_roi, vis_roi)
fps = self.fps.approx_compute()
# print("FPS: {:.3f}".format(fps))
cv2.putText(imshow_vis, 'FPS {:.3f}'.format(fps), (10, 10),
cv2.FONT_HERSHEY_SIMPLEX, 0.3, (255, 255, 255), 1,
cv2.LINE_AA)
cv2.imshow('TUCanshift', imshow_vis)
#print (str(self.count))
#self.count=self.count+1
ch = cv2.waitKey(2)
if ch == 27:
break
if ch == ord('b'):
self.show_backproj = not self.show_backproj
#data, addr = self.mdp.recv_message()
#data=MyUdp.getdata(data)
#if data:
# print "received:", data, "from", addr
cv2.destroyAllWindows()
self.cam.release()
self.mdp.close()
class App(object):
def __init__(self):
# self.cam = cv2.VideoCapture(0)
# self.cam.set(3, 320)
# self.cam.set(4, 240)
self.cam = WebcamVideoStream(src=0, resolution=(640, 480)).start()
self.fps = FPS().start()
ret, self.frame = self.cam.read()
self.conf = {
'ColorFrameNum': 7,
'LBPFrameNum': 7,
'MaxFrameDiffClr': 15,
'MaxLBPFrameUpdate': 30,
'L_Weight': 0.3,
'A_Weight': 0.7,
'B_Weight': 0.7
}
self.ColorCheck = AdaptiveThreshold(teta=3, max_lost_cnt=1)
self.LBPCheck = AdaptiveThreshold(teta=2, max_lost_cnt=1)
self.ColorDistance = LABDistance()
self.LBPDistance = LocalBinaryPatterns(
numPoints=8,
radius=2,
update_prev_hist=self.conf['MaxLBPFrameUpdate'])
self.isLost = False
self.isLBPLost = False
self.height, self.width = self.frame.shape[:2]
self.kernel_e = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (3, 3))
self.kernel_d = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (7, 7))
self.kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (5, 5))
cv2.namedWindow('camshift')
self.obj_select = RectSelector('camshift', self.onmouse)
self.LAB_CHANNELS = (
(24, [0, 256], "light"), # L
(24, [0, 256], "a"), # a
(24, [0, 256], "b") # b
)
self.show_backproj = False
self.track_window = None
self.histLAB = []
self.track_box = None
def onmouse(self, rect):
xmin, ymin, xmax, ymax = rect
labRoi = self.lab[ymin:ymax, xmin:xmax]
bgrRoi = self.frame[ymin:ymax, xmin:xmax]
self.calcLABhist(labRoi)
self.ColorDistance.init(bgrRoi)
self.track_window = (xmin, ymin, xmax - xmin, ymax - ymin)
# self.init_suspend(labRoi)
self.isLost = False
self.isLBPLost = False
self.fps.reset()
def calcLABhist(self, labRoi):
self.histLAB = []
for channel, param in enumerate(self.LAB_CHANNELS):
# Init LAB histogram
hist = cv2.calcHist([labRoi], [channel], None, [param[0]],
param[1])
hist = cv2.normalize(hist, hist, 0, 255, cv2.NORM_MINMAX)
self.histLAB.append(hist)
# Show hist of each channel separately
# self.show_hist(hist, param[2])
def calcBackProjection(self):
ch_prob = []
ch_back_proj_prob = []
for channel, param in enumerate(self.LAB_CHANNELS):
prob = cv2.calcBackProject([self.lab], [channel],
self.histLAB[channel], param[1], 1)
cv2.imshow('Back projection ' + str(param[2]), prob)
ret, prob = cv2.threshold(prob, 70, 255, cv2.THRESH_BINARY)
cv2.imshow('Back projection thresh ' + str(param[2]), prob)
# prob = cv2.morphologyEx(prob, cv2.MORPH_ERODE, self.kernel_e, iterations=1)
# prob = cv2.morphologyEx(prob, cv2.MORPH_DILATE, self.kernel, iterations=1)
prov = cv2.morphologyEx(prob,
cv2.MORPH_CLOSE,
self.kernel_e,
iterations=2)
ch_prob.append(prob)
ch_back_proj_prob.append(
cv2.addWeighted(ch_prob[0], self.conf['L_Weight'], ch_prob[1],
self.conf['A_Weight'], 0))
ch_back_proj_prob.append(
cv2.addWeighted(ch_prob[0], self.conf['L_Weight'], ch_prob[2],
self.conf['B_Weight'], 0))
back_proj_prob = cv2.bitwise_and(ch_back_proj_prob[0],
ch_back_proj_prob[1])
ret, back_proj_prob = cv2.threshold(back_proj_prob, 150, 255,
cv2.THRESH_BINARY)
back_proj_prob = cv2.morphologyEx(back_proj_prob,
cv2.MORPH_ERODE,
self.kernel_e,
iterations=1)
back_proj_prob = cv2.morphologyEx(back_proj_prob,
cv2.MORPH_DILATE,
self.kernel_e,
iterations=2)
return back_proj_prob
@staticmethod
def show_hist(hist, channel='None'):
bin_count = hist.shape[0]
bin_w = 24
img = np.zeros((256, bin_count * bin_w, 3), np.uint8)
for i in range(bin_count):
h = int(hist[i])
if str(channel) == 'light':
cv2.rectangle(img, (i * bin_w + 2, 255),
((i + 1) * bin_w - 2, 255 - h),
(int(255.0 * i / bin_count), 255, 255), -1)
elif str(channel) == 'a':
cv2.rectangle(img, (i * bin_w + 2, 255),
((i + 1) * bin_w - 2, 255 - h),
(255, int(255.0 * i / bin_count), 255), -1)
elif str(channel) == 'b':
cv2.rectangle(img, (i * bin_w + 2, 255),
((i + 1) * bin_w - 2, 255 - h),
(255, 255, int(255.0 * i / bin_count)), -1)
else:
cv2.rectangle(img, (i * bin_w + 2, 255),
((i + 1) * bin_w - 2, 255 - h), (255, 255, 255),
-1)
img = cv2.cvtColor(img, cv2.COLOR_LAB2BGR)
cv2.imshow('hist ' + str(channel), img)
def camshift_algorithm(self):
prob = self.calcBackProjection()
term_crit = (cv2.TERM_CRITERIA_EPS | cv2.TERM_CRITERIA_COUNT, 10, 1)
self.track_box, self.track_window = cv2.CamShift(
prob, self.track_window, term_crit)
if self.show_backproj:
cv2.imshow("Back Projection", prob[..., np.newaxis])
else:
cv2.destroyWindow("Back Projection")
def run(self):
scaling_factor = 0.5
last_frame_number = 0
while True:
if not self.obj_select.dragging:
ret, self.frame = self.cam.read()
self.frame = cv2.resize(self.frame,
None,
fx=scaling_factor,
fy=scaling_factor,
interpolation=cv2.INTER_AREA)
self.lab = cv2.cvtColor(self.frame, cv2.COLOR_BGR2LAB)
# self.lab = cv2.GaussianBlur(self.lab, (3,3), 0)
kernel = np.ones((5, 5), np.float32) / 25
self.lab = cv2.filter2D(self.lab, -1, kernel)
self.gray = cv2.cvtColor(self.frame, cv2.COLOR_BGR2GRAY)
if ret:
vis = self.frame.copy()
track_window_condition = ((self.track_window)
and (self.track_window[2] > 0)
and (self.track_window[3] > 0))
target_lost = self.isLost and self.isLBPLost
# Main proccess flow
if track_window_condition:
if not target_lost:
# Apply CamShift algorithm and get new track_box
self.camshift_algorithm()
if self.fps.NumFrame % self.conf[
'ColorFrameNum'] == 0 and not self.isLost:
color_distance = self.ColorDistance.update(
self.frame, self.track_box)
self.isLost = self.ColorCheck.target_lost(
color_distance)
print("[INFO] Color track is lost: '{}'\n".format(
self.isLost))
if self.isLost:
last_frame_number = self.fps.NumFrame
if self.fps.NumFrame % self.conf[
'LBPFrameNum'] == 0 and not self.isLBPLost:
LBP_distance = self.LBPDistance.update(
self.gray, self.track_window)
self.isLBPLost = self.LBPCheck.target_lost(
LBP_distance)
print("[INFO] LBP track is lost: '{}'\n".format(
self.isLBPLost))
if self.isLBPLost:
last_frame_number = self.fps.NumFrame
if self.fps.NumFrame - last_frame_number >= self.conf[
'MaxLBPFrameUpdate']:
self.isLBPLost = False
self.isLost = False
try:
cv2.ellipse(vis, self.track_box, (0, 0, 255), 2)
pts = cv2.boxPoints(self.track_box)
pts = np.int0(pts)
cv2.polylines(vis, [pts], True, 255, 2)
except:
print(self.track_box)
else:
cv2.putText(vis, 'Target Lost', (10, 230),
cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 0, 255), 1,
cv2.LINE_AA)
# print("[INFO] Starting recovery proccess")
elif not track_window_condition:
cv2.putText(vis, 'Mark area of the object', (10, 230),
cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 255, 0), 1,
cv2.LINE_AA)
# frame processing throughput rate
fps = self.fps.approx_compute()
cv2.putText(vis, 'FPS {:.3f}'.format(fps), (10, 10),
cv2.FONT_HERSHEY_SIMPLEX, 0.3, (255, 255, 255), 1,
cv2.LINE_AA)
self.obj_select.draw(vis)
cv2.imshow('camshift', vis)
ch = 0xFF & cv2.waitKey(1)
if ch == 27:
break
if ch == ord('b'):
self.show_backproj = not self.show_backproj
cv2.destroyAllWindows()
class App(object):
def __init__(self):
# self.cam = cv2.VideoCapture(0)
# self.cam.set(3, 320)
# self.cam.set(4, 240)
self.cam = WebcamVideoStream(src=0, resolution=(640, 480)).start()
self.fps = FPS().start()
ret, self.frame = self.cam.read()
self.suspend_tracking = SuspendTracking(teta=3)
self.height, self.width = self.frame.shape[:2]
self.kernel_erode = cv2.getStructuringElement(cv2.MORPH_ELLIPSE,
(3, 3))
self.kernel_dilate = cv2.getStructuringElement(cv2.MORPH_ELLIPSE,
(7, 7))
cv2.namedWindow('camshift')
self.obj_select = RectSelector('camshift', self.onmouse)
radius = 3
n_point = 8 * radius
self.lbpDesc = LBP(n_point, radius)
self.HSV_CHANNELS = (
(24, [0, 180], "hue"), # Hue
(8, [0, 256], "sat"), # Saturation
(8, [0, 256], "val") # Value
)
self.show_backproj = False
self.track_window = None
self.histHSV = []
self.track_box = None
def onmouse(self, rect):
xmin, ymin, xmax, ymax = rect
hsvRoi = self.hsv[ymin:ymax, xmin:xmax]
self.calcHSVhist(hsvRoi)
self.track_window = (xmin, ymin, xmax - xmin, ymax - ymin)
self.init_suspend(hsvRoi)
self.fps.reset()
def init_suspend(self, hsvRoi):
track_window_condition = self.track_window and self.track_window[
2] > 0 and self.track_window[3] > 0
if track_window_condition:
self.camshift_algorithm()
self.suspend_tracking.init(hsvRoi)
def calcHSVhist(self, hsvRoi):
self.histHSV = []
for channel, param in enumerate(self.HSV_CHANNELS):
# Init HSV histogram
hist = cv2.calcHist([hsvRoi], [channel], None, [param[0]],
param[1])
hist = cv2.normalize(hist, hist, 0, 255, cv2.NORM_MINMAX)
self.histHSV.append(hist)
# Show hist of each channel separately
self.show_hist(hist, param[2])
def calcBackProjection(self):
ch_prob = []
ch_back_proj_prob = []
# back_proj_prob = np.ones(shape=(self.height, self.width), dtype=np.uint8) * 255
# back_proj_prob = np.zeros(shape=(self.height, self.width), dtype=np.uint8)
for channel, param in enumerate(self.HSV_CHANNELS):
prob = cv2.calcBackProject([self.hsv], [channel],
self.histHSV[channel], param[1], 1)
cv2.imshow('Back projection ' + str(param[2]), prob)
# ret, prob = cv2.threshold(prob, 0, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU)
ret, prob = cv2.threshold(prob, 70, 255, cv2.THRESH_BINARY)
cv2.imshow('Back projection thresh ' + str(param[2]), prob)
# prob = cv2.morphologyEx(prob, cv2.MORPH_ERODE, self.kernel_erode, iterations=2)
# prob = cv2.morphologyEx(prob, cv2.MORPH_DILATE, self.kernel_dilate, iterations=3)
# back_proj_prob = cv2.bitwise_and(back_proj_prob, prob)
# back_proj_prob = cv2.addWeighted(back_proj_prob, 0.4, prob, 0.6, 0)
ch_prob.append(prob)
ch_back_proj_prob.append(
cv2.addWeighted(ch_prob[0], 0.6, ch_prob[1], 0.4, 0))
ch_back_proj_prob.append(
cv2.addWeighted(ch_prob[0], 0.6, ch_prob[2], 0.4, 0))
back_proj_prob = cv2.bitwise_and(ch_back_proj_prob[0],
ch_back_proj_prob[1])
ret, back_proj_prob = cv2.threshold(back_proj_prob, 150, 255,
cv2.THRESH_BINARY)
back_proj_prob = cv2.morphologyEx(back_proj_prob,
cv2.MORPH_ERODE,
self.kernel_erode,
iterations=1)
back_proj_prob = cv2.morphologyEx(back_proj_prob,
cv2.MORPH_DILATE,
self.kernel_erode,
iterations=2)
return back_proj_prob
@staticmethod
def show_hist(hist, channel='None'):
bin_count = hist.shape[0]
bin_w = 24
img = np.zeros((256, bin_count * bin_w, 3), np.uint8)
for i in range(bin_count):
h = int(hist[i])
if str(channel) == 'hue':
cv2.rectangle(img, (i * bin_w + 2, 255),
((i + 1) * bin_w - 2, 255 - h),
(int(180.0 * i / bin_count), 255, 255), -1)
elif str(channel) == 'sat':
cv2.rectangle(img, (i * bin_w + 2, 255),
((i + 1) * bin_w - 2, 255 - h),
(180, int(255.0 * i / bin_count), 255), -1)
elif str(channel) == 'val':
cv2.rectangle(img, (i * bin_w + 2, 255),
((i + 1) * bin_w - 2, 255 - h),
(180, 255, int(255.0 * i / bin_count)), -1)
else:
cv2.rectangle(img, (i * bin_w + 2, 255),
((i + 1) * bin_w - 2, 255 - h), (180, 255, 255),
-1)
img = cv2.cvtColor(img, cv2.COLOR_HSV2BGR)
cv2.imshow('hist ' + str(channel), img)
def camshift_algorithm(self):
prob = self.calcBackProjection()
term_crit = (cv2.TERM_CRITERIA_EPS | cv2.TERM_CRITERIA_COUNT, 10, 1)
self.track_box, self.track_window = cv2.CamShift(
prob, self.track_window, term_crit)
if self.show_backproj:
cv2.imshow("Back Projection", prob[..., np.newaxis])
else:
cv2.destroyWindow("Back Projection")
def run(self):
scaling_factor = 0.5
while True:
if not self.obj_select.dragging:
ret, self.frame = self.cam.read()
self.frame = cv2.resize(self.frame,
None,
fx=scaling_factor,
fy=scaling_factor,
interpolation=cv2.INTER_AREA)
# blur_frame = cv2.GaussianBlur(self.frame, (21,21), 0)
self.hsv = cv2.cvtColor(self.frame, cv2.COLOR_BGR2HSV)
if ret:
vis = self.frame.copy()
track_window_condition = self.track_window and self.track_window[
2] > 0 and self.track_window[3] > 0
if track_window_condition and not self.suspend_tracking.is_suspend(
self.hsv, self.track_box):
self.camshift_algorithm()
try:
cv2.ellipse(vis, self.track_box, (0, 0, 255), 2)
pts = cv2.boxPoints(self.track_box)
pts = np.int0(pts)
cv2.polylines(vis, [pts], True, 255, 2)
except:
print(self.track_box)
else:
cv2.putText(vis, 'Target Lost', (10, 230),
cv2.FONT_HERSHEY_SIMPLEX, 1, (255, 255, 255), 1,
cv2.LINE_AA)
# frame processing throughput rate
fps = self.fps.approx_compute()
# print("FPS: {:.3f}".format(fps))
cv2.putText(vis, 'FPS {:.3f}'.format(fps), (10, 10),
cv2.FONT_HERSHEY_SIMPLEX, 0.3, (255, 255, 255), 1,
cv2.LINE_AA)
self.obj_select.draw(vis)
cv2.imshow('camshift', vis)
ch = 0xFF & cv2.waitKey(1)
if ch == 27:
break
if ch == ord('b'):
self.show_backproj = not self.show_backproj
cv2.destroyAllWindows()
class App(object):
def __init__(self, video_src):
#树莓派ip
self.mdp = MyUdp()
#self.server_address='http://%s:8000/stream.mjpg' % MyUdp.get_piIP('raspberrypi')
#self.server_address='http://192.168.56.146:8080/?action=stream'
#self.server_address='rtmp://127.0.0.1/live/stream'
#self.server_address='rtmp://127.0.0.1:1935/dji'
#self.server_address='http://192.168.56.240:8000/stream.mjpg'
#self.server_address='http://192.168.56.240:8000/?action=stream'
#self.server_address='http://192.168.191.3:8000/stream.mjpg'
#self.server_address='rtsp://:192.168.40.118/1'
self.server_address = 0
#self.server_address='C:\\Users\\Carole\\Desktop\\as.mp4'
#self.cam = video.create_capture(self.server_address)
self.cam = WebcamVideoStream(self.server_address).start()
ret, self.frame = self.cam.read()
self.fish_cali = fish_calibration((560, 420))
self.drag_start = None
try:
self.list_camshift = pickle.load(open("color_instant.p", "rb"))
except:
self.list_camshift = []
print 'Load color_instant.p FAIL...'
else:
print 'Load color_instant.p Success!!!'
#self.list_camshift=[]
#self.show_backproj = False
self.newcamshift = None
self.selection = None
self.lock = False
self.lastorder = None
self.track_box = []
self.first_start = True
self.car_found_first = False
self.lastime = time.time()
self.lastime_car = time.time()
self.sumtime = 0
self.car_lost_time = 0
self.car_lost = False
#self.count=0
self.light = self.get_light()
self.JK_flag = False
self.swicht = False
#self.list_camshift.append(self.get_car('red.jpg',0))
#self.list_camshift.append(self.get_car('yellow.jpg',1))
#H,S
#self.mask_avoid=cv2.cvtColor(cv2.imread('C:\\Users\\nuc\\Desktop\\src\\mask_avoid_1.bmp'),cv2.COLOR_BGR2GRAY)
self.mask_avoid = cv2.cvtColor(cv2.imread('mask_avoid_1.bmp'),
cv2.COLOR_BGR2GRAY)
self.BACKGROUND_PARAM = App.calc_HS(
cv2.cvtColor(self.frame, cv2.COLOR_BGR2HSV))
self.miste = True
self.fps = FPS().start()
#wifi模块IP
while True:
try:
self.mdp.client_address = (socket.gethostbyname('Doit_WiFi'),
8899)
break
except:
print 'Doit_WiFi NOT FOUND'
#新车
#self.mdp.client_address=('192.168.56.207', 8899)
cv2.namedWindow('TUCanshift')
cv2.setMouseCallback('TUCanshift', self.onmouse)
hm = pyHook.HookManager()
hm.KeyDown = self.onKeyBoard
hm.HookKeyboard()
def onKeyBoard(self, event):
if event.Key == 'K':
self.JK_flag = False
if event.Key == 'J':
self.JK_flag = True
if event.Key == 'Escape':
cv2.destroyAllWindows()
self.cam.release()
self.mdp.close()
import os
os._exit(0)
if event.Key == 'W':
print 'W'
self.mdp.send_message('guidance', (0, 5))
if event.Key == 'S':
print 'S'
self.mdp.send_message('back_car', (0, 0))
#if event.Key=='B':
# if len(self.list_camshift)==2:
# pickle.dump(self.list_camshift,open("color_instant.p","wb"))
# print 'Dump Success!'
return True
def onmouse(self, event, x, y, flags, param):
if self.lock:
if event == cv2.EVENT_RBUTTONDOWN:
self.pop_camshift()
return
if event == cv2.EVENT_LBUTTONDOWN and len(self.list_camshift) <= 1:
self.drag_start = (x, y)
self.newcamshift = mycamshift()
if self.drag_start:
xmin = min(x, self.drag_start[0])
ymin = min(y, self.drag_start[1])
xmax = max(x, self.drag_start[0])
ymax = max(y, self.drag_start[1])
self.selection = (xmin, ymin, xmax, ymax)
if event == cv2.EVENT_LBUTTONUP:
self.fps.reset()
self.drag_start = None
if self.newcamshift is not None and self.newcamshift.getHist(
) is not None:
self.newcamshift.ID = len(self.list_camshift)
self.list_camshift.append(self.newcamshift)
self.newcamshift = None
self.selection = None
return True
def pop_camshift(self):
if (len(self.list_camshift) < 1):
return True
cv2.destroyWindow(str(len(self.list_camshift) - 1))
cv2.destroyWindow('%s%s' % ('cam', str(len(self.list_camshift) - 1)))
self.list_camshift.pop()
return False
@staticmethod
def creat_camshift_from_img(hsv):
camshift = mycamshift()
mask = np.ones((hsv.shape[0], hsv.shape[1]), dtype=np.uint8)
camshift.preProcess(hsv, mask, (0, 0, hsv.shape[1], hsv.shape[0]), 32)
return camshift
def get_light(self):
temp = mycamshift()
temp.prProcess_light(self.frame)
temp.ID = 99
return temp
def get_car(self, file, ID):
img = cv2.imread(file, cv2.IMREAD_UNCHANGED)
img = cv2.resize(img, (self.frame.shape[1], self.frame.shape[0]))
hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
temp = App.creat_camshift_from_img(hsv)
cv2.imshow(str(ID), temp.getHist())
temp.ID = ID
return temp
@staticmethod
def calc_HS(hsv):
H_hist = cv2.calcHist([hsv], [0], None, [180], [0, 180])
H = H_hist.argmax(axis=None, out=None)
S_hist = cv2.calcHist([hsv], [1], None, [255], [0, 255])
S = S_hist.argmax(axis=None, out=None)
return (H, S)
def run(self):
while True:
if not (self.cam.renew and self.cam.grabbed):
if not self.cam.grabbed:
self.mdp.send_message('lost')
continue
ret, self.frame = self.cam.read()
#self.frame=cv2.resize(self.frame,(560,420),interpolation=cv2.INTER_AREA)
#self.frame=cv2.GaussianBlur(self.frame,(5,5),2)
#self.frame=cv2.medianBlur(self.frame,5)
self.frame = self.fish_cali.cali(self.frame)
imshow_vis = self.frame.copy()
hsv = cv2.cvtColor(self.frame, cv2.COLOR_BGR2HSV)
#注掉使用背景参数的静态方法
self.BACKGROUND_PARAM = App.calc_HS(hsv)
mask = mycamshift.filte_background_color(hsv,
self.BACKGROUND_PARAM,
offset1=16.,
offset2=90.,
iterations=3)
if self.miste:
cv2.imshow('fore_ground', mask)
if self.newcamshift is not None:
if self.newcamshift.preProcess(hsv, mask, self.selection, 24):
cv2.imshow(str(ll), self.newcamshift.getHist())
light_gray = cv2.cvtColor(self.frame, cv2.COLOR_BGR2GRAY)
#cv2.imshow('gray',light_gray)
mean, temp = cv2.threshold(light_gray, 0, 255,
cv2.THRESH_BINARY + cv2.THRESH_OTSU)
thresh = (255 - mean) * 0.7 + mean
if thresh > 230:
thresh = 230
#_,light_gray=cv2.threshold(light_gray,thresh,255,cv2.THRESH_BINARY)
_, light_gray_ths = cv2.threshold(light_gray, thresh, 255,
cv2.THRESH_BINARY)
light_gray = cv2.bitwise_and(light_gray,
light_gray,
mask=cv2.bitwise_and(
mask, light_gray_ths))
light_gray = cv2.morphologyEx(light_gray,
cv2.MORPH_OPEN,
cv2.getStructuringElement(
cv2.MORPH_ELLIPSE, (3, 3)),
iterations=2,
borderType=cv2.BORDER_REPLICATE)
if self.miste:
cv2.imshow('light', light_gray)
self.track_box = [self.light.go_once_gray(light_gray)]
if self.track_box[0] is None:
self.sumtime = time.time() - self.lastime + self.sumtime
else:
self.sumtime = 0
self.first_start = True
self.lastime = time.time()
#print self.sumtime
if self.sumtime > 0.5 and self.first_start:
print 'lost light GUIDANCE'
self.track_box = [(self.frame.shape[1] / 2,
self.frame.shape[0] / 2)]
if self.sumtime > 3600:
self.sumtime = 36
self.lock = False
ll = len(self.list_camshift)
if ll > 0:
#mask_hsv=cv2.bitwise_and(hsv,hsv,mask=mask)
#cv2.imshow('mask_hsv',mask_hsv)
for x in self.list_camshift:
self.track_box.append(x.go_once(hsv, mask))
#prob=self.list_camshift[ll-1].prob
#if self.show_backproj and prob is not None:
# self.frame=prob[...,np.newaxis]
else:
cv2.putText(imshow_vis, 'Wait for START', (10, 230),
cv2.FONT_HERSHEY_SIMPLEX, 1, (255, 255, 255), 1,
cv2.LINE_AA)
#self.mdp.send_message('lost')
self.lock = True
n = len(self.track_box)
#if n>2:
if n == 3:
p3 = self.track_box[0]
p1, p2 = self.track_box[n - 2:]
try:
p1 = p1[0]
except:
p1 = None
try:
p2 = p2[0]
except:
p2 = None
try:
p3 = p3[0]
except:
p3 = None
if p1 and p2:
self.car_found_first = True
try:
#snap(img,p1,p2,障碍侦测范围，障碍侦测宽度，微调：避免将车头识别为障碍)
#theta,D,dst=snap(mask,p1,p2,4.5,0.75,2.0,2.2)
#theta,D,dst=snap_c(mask,p1,p2,4.5,1.7,1.7,1.65)
#新车
#theta,D,dst=snap(mask,p1,p2,8.0,0.9,2.2,2.2)
if p3:
try:
t_guidance, d_guidance = get_direction(
p1, p2, p3)
except:
t_guidance = None
d_guidance = None
if t_guidance is not None and d_guidance is not None:
if abs(t_guidance) < 70 and d_guidance < 4:
mask = light_gray
if abs(t_guidance) < 20 and d_guidance < 7:
mask = light_gray
theta, D, dst = snap_test(mask, self.mask_avoid, p1,
p2, 5.0, 0.9, 2.2, 2.2)
dst = cv2.resize(dst, (400, 200))
if self.miste:
cv2.imshow('snap', dst)
if theta is not None:
mes = (int(theta), int(D))
self.mdp.send_message('avoid', mes)
self.lastorder = ('avoid', mes)
#print('Block ahead')
cv2.putText(imshow_vis, 'Block ahead:%s,%s' % mes,
(10, 230), cv2.FONT_HERSHEY_SIMPLEX, 1,
(255, 255, 255), 1, cv2.LINE_AA)
#print(mes)
elif p3:
t, d = get_direction(p1, p2, p3)
mes = (int(t), int(d))
self.mdp.send_message('guidance', mes)
self.lastorder = ('guidance', mes)
#print('guidance')
cv2.putText(imshow_vis, 'Guidance:%s,%s' % mes,
(10, 230), cv2.FONT_HERSHEY_SIMPLEX, 1,
(255, 255, 255), 1, cv2.LINE_AA)
#print mes
else:
cv2.putText(imshow_vis, 'Taget LOST', (10, 230),
cv2.FONT_HERSHEY_SIMPLEX, 1,
(255, 255, 255), 1, cv2.LINE_AA)
#self.mdp.send_message('lost')
except:
cv2.putText(imshow_vis, '0/0 is error', (10, 230),
cv2.FONT_HERSHEY_SIMPLEX, 1,
(255, 255, 255), 1, cv2.LINE_AA)
self.mdp.send_message('lost')
else:
cv2.putText(imshow_vis, 'Car LOST', (10, 230),
cv2.FONT_HERSHEY_SIMPLEX, 1, (255, 255, 255),
1, cv2.LINE_AA)
self.car_lost = True
#self.mdp.send_message('lost')
# elif n>1:
# cv2.putText(imshow_vis, 'Wait for START', (10, 230),cv2.FONT_HERSHEY_SIMPLEX, 1, (255, 255,255), 1, cv2.LINE_AA)
# self.mdp.send_message('lost')
else:
cv2.putText(imshow_vis, 'Wait for START', (10, 230),
cv2.FONT_HERSHEY_SIMPLEX, 1, (255, 255, 255), 1,
cv2.LINE_AA)
self.mdp.send_message('lost')
if self.car_lost and self.first_start:
self.car_lost = False
self.car_lost_time = time.time(
) - self.lastime_car + self.car_lost_time
else:
self.car_lost_time = 0
self.lastime_car = time.time()
if self.car_lost_time > 0.5 and self.car_found_first and self.first_start and self.lastorder is not None:
o, m = self.lastorder
if m[0] < 50 and m[0] >= 0:
m = (50, m[1])
if m[0] > -50 and m[0] < 0:
m = (-50, m[1])
self.mdp.send_message(o, m)
print 'car LOST guidance'
if len(self.track_box) > 0:
for x in self.track_box:
try:
cv2.ellipse(imshow_vis, x, (0, 0, 255), 2)
pts = cv2.boxPoints(x)
pts = np.int0(pts)
cv2.polylines(imshow_vis, [pts], True, 255, 2)
except:
pass
fps = self.fps.approx_compute()
# print("FPS: {:.3f}".format(fps))
cv2.putText(imshow_vis, 'FPS {:.3f}'.format(fps), (10, 10),
cv2.FONT_HERSHEY_SIMPLEX, 0.3, (255, 255, 255), 1,
cv2.LINE_AA)
if self.selection is not None:
x0, y0, x1, y1 = self.selection
vis_roi = imshow_vis[y0:y1, x0:x1]
cv2.bitwise_not(vis_roi, vis_roi)
if self.miste:
cv2.imshow('TUCanshift', imshow_vis)
#if not self.first_start:
# print 'WAIT...'
#else:
# print 'GO'
ch = cv2.waitKey(1)
if ch == ord('b'):
if len(self.list_camshift) == 2:
pickle.dump(self.list_camshift,
open('color_instant.p', 'wb'))
print 'Dump Success!'
else:
print 'ni mei quan -_-'
#if ch == 27:
# break
#if ch==ord('r'):
# self.BACKGROUND_PARAM=App.calc_HS(hsv)
# self.first_start=False
#if ch==ord('w'):
# self.mdp.send_message('guidance',(0,10))
#if ch==ord('s'):
# self.mdp.send_message('back_car',(0,0))
#if ch==ord('['):
# self.miste=not self.miste
while self.JK_flag:
try:
self.mdp.client_address = (
socket.gethostbyname('Doit_WiFi'), 8899)
self.mdp.send_message('lost')
except:
print 'Doit_WiFi NOT FOUND'
else:
print 'NEW IP:%s' % self.mdp.client_address[0]
cv2.waitKey(30)
cv2.destroyAllWindows()
self.cam.release()
self.mdp.close()