def __init__(self, dir_path = 'dataset/data',csv_path='image_data.csv' ):
self.image_size = tuple((500, 500))
self.features = []
self.image_path_list = []
self.mse_all = []
self.labels = []
#object of feature extractor
self.fe_obj = fe.Global_feature_extraction()
self.dir_path = dir_path
self.data = pd.read_csv(csv_path,index_col=0)
def __init__(self):
with open('conf/conf.json') as f:
self.config = json.load(f)
with open('conf/feature_names.json') as f:
self.features_name = json.load(f)
self.csv_path = self.config["csv_path"]
self.data = pd.read_csv(self.csv_path, index_col=0)
self.image_size = tuple((500, 500))
#objects of feature extractor
self.fe_glb = fe.Global_feature_extraction()
self.fe_lcl = fe.Local_feature_extractor()
def __init__(self):
with open('conf/conf.json') as f:
self.config = json.load(f)
self.csv_path = self.config["csv_path"]
self.image_size = tuple((500, 500))
self.features = []
self.image_path_list = []
self.mse_all = []
self.labels = []
#object of feature extractor
self.fe_obj = fe.Global_feature_extraction()
self.data = pd.read_csv(self.csv_path, index_col=0)
import numpy as np
import cv2
import features as fe
import glob
import pickle as pkl
import pandas as pd
import json
image_path2 = '/home/mahdi/Pictures/test/2.jpeg'
image_path = '/home/mahdi/Pictures/test/3.jpeg'
image_size = tuple((500, 500))
with open('conf/feature_names.json') as f:
features_name = json.load(f)
fe_glb = fe.Global_feature_extraction()
args = ['shape', 'texture', 'sift']
feature_table = {
'shape': None,
'texture': None,
'color': None,
'SIFT': None,
'SURF': None,
'KAZE': None,
'Dense': None
}
Image = cv2.imread(image_path)
Image = cv2.resize(Image, image_size)
Shape = getattr(fe_glb, features_name['shape'])
def hstack_maker(*args):
features = np.hstack(args)
return features
####################################################
## this is the second way for feature selection ##
####################################################
def feature_selector(first, second, third, **options):
if options.get("action") == "sum":
print("The sum is: %d" %(first + second + third))
if options.get("number") == "first":
return first
def foo(first, second, third, *therest):
print("First: %s" %(first))
features = fe.
shape = getattr(fe.Global_feature_extraction(),config['global_features'][0])
for i in config['global_features']:
print(i)
this_fea