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feature.py
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feature.py
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#!/usr/bin/env python
# -*- coding: UTF-8 -*-
import os
import itertools
import csv
import numpy as np
import caffe
import cv2
class Feature():
def __init__(self, flag_separate=False):
MEAN = '../path/to/mean_file'
NET = '../path/to/network_file'
MODEL = '../path/to/model_file'
self.LAYER = 'fc6wi'
self.INDEX = 4
self.feature = []
self.flag_separate = flag_separate
self.net = caffe.Classifier(NET, MODEL)
caffe.set_mode_cpu()
self.net.transformer.set_mean('data', np.load(MEAN))
self.net.transformer.set_raw_scale('data', 255)
self.net.transformer.set_channel_swap('data', (2, 1, 0))
def input_data(self):
self.files = os.listdir('./data/')
def get_featurevextor(self):
self.input_data()
for filename in self.files:
if not self.flag_separate:
self.feature_extraction(filename)
else:
separated_files = self.separate(filename)
for separated_filename in separated_files: