index.py

#import the necessary packages
from features.colordescriptor import ColorDescriptor
import argparse
import glob
import cv2

#construct the argument parser and parse the arguments
ap = argparse.ArgumentParser()
ap.add_argument("-d", "--dataset", required=True,
	help = "path to the directory that contains the images to be indexed")
ap.add_argument("-i", "--index", required=True,
	help = "path to where the index should be stored")
args = vars(ap.parse_args())

#initialize the color descriptor
cd = ColorDescriptor((8, 12, 3))

#open the output index file for writing
output = open(args["index"], "w")
types = ('/*.jpg', '/*.png', '/*.gif') # the tuple of file types
files_grabbed = []
for files in types:
    files_grabbed.extend(glob.glob(args["dataset"]+files))

#use glob to grab the image paths and loop over them
for imagePath in files_grabbed:
    #extract the imageID from the image
    #path and load the image itself

    imageID = imagePath[imagePath.rfind("/")+1:]
    image = cv2.imread(imagePath)
    # print(imageID)
    tmp=imageID.split('\\')
    # print(tmp[1])
    #describe the image
    features = cd.describe(image)

    #write the features to file
    features = [str(f) for f in features]
    output.write("%s,%s\n" % (tmp[1], ",".join(features)))

# close the index file
output.close()