def classify(self, img):
IHandler = Func.PornImageHandler()
#img = cv2.imread(filename)
num = 1
VecList = []
label = []
# 将图片特征向量
VecList.append(IHandler.GetFeature(img))
label.append(1)
num += 1
if os.path.exists(self.modelpath):
model = svm.svm_load_model(self.modelpath)
else:
self.train()
p_labs, p_acc, p_vals = svm.svm_predict(label, VecList, model, '-b 1')
print p_labs, p_acc, p_vals
if p_labs[0] > 0.5:
return True
else:
return False
def ExtractFeature(self, truepath, falsepath):
num = 1
VecList = []
label = []
self.truelist = self.__load_images(truepath)
self.falselist = self.__load_images(falsepath)
IHandler = Func.PornImageHandler()
# 训练正样本
for img in self.truelist:
self.__SubProc(IHandler, VecList, label, img, 1, num,
len(self.truelist) + len(self.falselist))
num += 1
# 训练负样本
for img in self.falselist:
self.__SubProc(IHandler, VecList, label, img, 0, num,
len(self.truelist) + len(self.falselist))
num += 1
print "[*] Created Process Pool!"
print len(VecList), " ", len(label)
return label, VecList
def run(P, truepath, falsepath):
IHandler = Func.PornImageHandler()
truelist = __load_images(truepath)
falselist = __load_images(falsepath)
# Multi Proc
VecList = []
label = []
result = []
num = 1
pool = Pool()
for img in truelist:
result.append(pool.apply_async(SubProc, args = (IHandler, img, 1, num, len(truelist) + len(falselist), )))
num += 1
for img in falselist:
result.append(pool.apply_async(SubProc, args = (IHandler, img, 0, num, len(truelist) + len(falselist), )))
num += 1
pool.close()
pool.join()
for r in result:
print r.get()[1]
VecList.append(r.get()[0])
label.append(r.get()[1])
return label, VecList
