def dirPicTest():
clf = joblib.load('model/svm.pkl')
print type(clf)
print clf
platePath = 'resource/general_test'
for root, dirs, files in os.walk( platePath ):
print len(files)
for file in files:
path = os.path.join( root, file )
print 'loading....',path
imgPlate = cv2.imread(path,cv2.IMREAD_COLOR)
PlateLocater.m_debug = False
Result = PlateLocater.fuzzyLocate(imgPlate)
for plate in Result:
feature = PlateJudger.getHistogramFeatures(plate)
res = clf.predict(feature)
flag = (res==1)
print flag[0]
if flag[0]:
cv2.imshow('test',plate)
cv2.waitKey(0)
cv2.destroyAllWindows()
return None
def CV_dirPicTest():
model = CV_trainModel()
platePath = 'resource/general_test'
for root, dirs, files in os.walk( platePath ):
print len(files)
for file in files:
path = os.path.join( root, file )
print 'loading....',path
imgPlate = cv2.imread(path,cv2.IMREAD_COLOR)
PlateLocater.m_debug = False
Result = PlateLocater.fuzzyLocate(imgPlate)
for plate in Result:
feature = PlateJudger.getHistogramFeatures(plate)
print feature.dtype
feature = np.float32(feature)
res = model.predict(feature)
a = (res==1)
print a[0]
if a[0]:
cv2.imshow('test',plate)
cv2.waitKey(0)
cv2.destroyAllWindows()
def CV_PicTest():
model = CV_trainModel()
imgPlate = cv2.imread('plate_judge.jpg',cv2.IMREAD_COLOR)
PlateLocater.m_debug = False
Result = PlateLocater.fuzzyLocate(imgPlate)
for plate in Result:
cv2.imshow('test',plate)
feature = PlateJudger.getHistogramFeatures(plate)
feature = np.float32(feature)
res = model.predict(feature)
print res
cv2.waitKey(0)
cv2.destroyAllWindows()
def loadNegativeTrainData(platePath): traindata = np.ones((1,172)) label = np.array([0]) isFirst = True for root, dirs, files in os.walk( platePath ): print len(files) for file in files: path = os.path.join( root, file ) print 'loading....',path imgPlate = cv2.imread(path,cv2.IMREAD_COLOR) feature = PlateJudger.getHistogramFeatures(imgPlate) if isFirst: traindata = feature isFirst = False else: traindata = np.vstack([traindata,feature]) label = np.hstack([label,0]) return traindata,label
