def __init__(self, data_path):
# 源代码生成的txt文件的临时存放区域
self._data_path = data_path
self._extractor = Extractor()
self._interpreter = Interpreter(self._data_path)
self._path_vec = []
def extractFeatures(data):
extractor = Extractor(data)
data = extractor.extractFeatures()
import cv2
import numpy as np
import Config
from tqdm import tqdm
from PIL import Image
from sklearn.svm import LinearSVC
from sklearn.neural_network import MLPClassifier
from skimage.transform import pyramid_gaussian
from sklearn.externals import joblib
from FeatureExtractor import Extractor
## Initialize the Extractor
conf = Config.Config()
extractor = Extractor(conf)
class Classifier(object):
def __init__(self, config):
self.config = config
def load_data(self):
'''
This function is used to load the training data, positive data
and negtive data.The features of images are stored in self.fds,
the labels are stored in self.labels.
:return: None
'''
self.fds = []
self.labels = []