def showSegROI():
cv2.destroyAllWindows()
cap = cv2.VideoCapture(r'H:\human_dataset\3_shenle.avi')
ii = 0
while True:
ret, frame = cap.read()
ii += 1
grayim = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
if ret == False: break
cv2.imshow('origin', frame)
cv2.waitKey(10)
ceterframe = frame[105:105 + 300, 104:104 + 512]
cetergrayim = grayim[105:105 + 300, 104:104 + 512]
threshimg, segrois = roiextract.segmetation_roi(ceterframe)
# dimg = cv2.adaptiveThreshold(src = graim,maxValue = 255, adaptiveMethod = cv2.ADAPTIVE_THRESH_GAUSSIAN_C,thresholdType = cv2.THRESH_BINARY_INV,blockSize = 5,C = 3)
# dimg = doDualThreshold()#statrow = 105,statcol = 104
# labelrois = labelConnectedComponent(dimg)
# for roi in segrois:
# hog.svmPredict(cetergrayim,roi)
Visual.showResult(cetergrayim, segrois, winname='seg',
color=200) #color值越大越线条越偏白
if cv2.waitKey(1) == 32:
print('space')
while True:
if (cv2.waitKey(1) == 32): break
cv2.destroyAllWindows()
def segDetect():
cv2.destroyAllWindows()
cap = cv2.VideoCapture(r'H:\human_dataset\3_shenle.avi')
ii = 0
while True:
ret, frame = cap.read()
ii += 1
grayim = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
if ret == False: break
cv2.imshow('origin', frame)
cv2.waitKey(10)
ceterframe = frame[105:105 + 300, 104:104 + 512]
cetergrayim = grayim[105:105 + 300, 104:104 + 512]
threshimg, segrois = roiextract.segmetation_roi(ceterframe)
personroi = []
filteredrois = roifilter.getFilteredROI(segrois)
print(len(filteredrois))
for roi in filteredrois:
if hogsvm.svmPredict(cetergrayim, roi) == 1:
personroi.append(roi)
print('person')
Visual.showResult(threshimg, segrois, winname='seg roi',
color=200) #color值越大越线条越偏白
# for roi in segrois:
# hog.svmPredict(cetergrayim,roi)
Visual.showResult(cetergrayim,
personroi,
winname='person roi',
color=200) #color值越大越线条越偏白
if cv2.waitKey(1) == 32:
print('space')
while True:
if (cv2.waitKey(1) == 32): break
cv2.destroyAllWindows()
def showSURFROI():
cv2.destroyAllWindows()
cap = cv2.VideoCapture(r'H:\human_dataset\3_shenle.avi')
ii = 0
while True:
ret, frame = cap.read()
ii += 1
grayim = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
if ret == False: break
cv2.imshow('origin', frame)
cv2.waitKey(10)
ceterframe = frame[105:105 + 300, 104:104 + 512]
cetergrayim = grayim[105:105 + 300, 104:104 + 512]
filteredkps, surfrois = roiextract.surf_roi(cetergrayim, 512, 300)
kpimg = cv2.drawKeypoints(ceterframe, filteredkps, None, (255, 0, 0),
4)
cv2.imshow('surf keypoint', kpimg)
cv2.waitKey(10)
# for roi in segrois:
# hog.svmPredict(cetergrayim,roi)
Visual.showResult(cetergrayim, surfrois, winname='surf',
color=200) #color值越大越线条越偏白
if cv2.waitKey(1) == 32:
print('space')
while True:
if (cv2.waitKey(1) == 32): break
cv2.destroyAllWindows()
def kpAnnShow():
kpsinfos = parseAllKPFile()#解析所有kp文件
anninfos = parse_all_ann_filtered()#解析所有标注
videopathes = getVideoPath()#读取所有视频路径
for setnum in range(len(videopathes)):#处理所有set
for vpath in videopathes[setnum]:#处理set中所有特征点文件
indrs = vpath.rfind('\\')
indp = vpath.rfind('.')
vstr = vpath[indrs+2:indp]#获取去掉"V"和后缀的视频名
cap = cv2.VideoCapture(vpath)
frameindex = 0
vkey = '%02d'%(setnum)+vstr
anninfo = anninfos[vkey]
kpsinfo = kpsinfos[vkey]
while True:
frameindex +=1
ret,frame = cap.read()
if ret == False:break
#kpskey = '%05d'%(frameindex)
framekey = vkey+'%05d'%(frameindex)
kps = kpsinfo[framekey]
ann = anninfo[framekey]
ceterframe = frame[105:105 + 300,104:104 + 512]
threshimg,segrois = roiextract.segmetation_roi(ceterframe)
kprois = cKPS2ROIs(kps)
Visual.showResult(ceterframe,ann,'annotation',(255,0,0))
Visual.showResult(ceterframe,kprois,'surf_roi',(0,0,255))
Visual.showResult(ceterframe,segrois,winname = 'seg',color = 200)#color值越大越线条越偏白
# cv2.waitKey(50)
return None
def surfDetect(outPath=None):
if outPath != None: #将结果写出到视频
fps = 25 #视频帧率
fourcc = cv2.VideoWriter_fourcc('X', 'V', 'I', 'D')
videoWriter = cv2.VideoWriter(outPath, fourcc, fps,
(768, 576)) #(1360,480)为视频大小
cv2.destroyAllWindows()
cap = cv2.VideoCapture(r'H:\human_dataset\3_shenle.avi')
ii = 0
while True:
ret, frame = cap.read()
ii += 1
grayim = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
if ret == False: break
cv2.imshow('origin', frame)
cv2.waitKey(10)
ceterframe = frame[105:105 + 300, 104:104 + 512]
cetergrayim = grayim[105:105 + 300, 104:104 + 512]
filteredkps, surfrois = roiextract.surf_roi(cetergrayim, 512, 300)
kpimg = cv2.drawKeypoints(ceterframe, filteredkps, None, (255, 0, 0),
4)
personroi = []
filteredrois = roifilter.getFilteredROI(surfrois)
for roi in filteredrois:
if hogsvm.svmPredict(cetergrayim, roi) == 1:
personroi.append(roi)
print('person')
cv2.imshow('surf keypoint', kpimg)
cv2.waitKey(10)
Visual.showResult(cetergrayim,
personroi,
winname='person roi',
color=200) #color值越大越线条越偏白
if cv2.waitKey(1) == 32:
print('space')
while True:
if (cv2.waitKey(1) == 32): break
if outPath != None: #将结果写出到视频
videoWriter.write(kpimg)
cv2.destroyAllWindows()
