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indexor.py
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indexor.py
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#!/usr/bin/env python
# -*- coding: utf-8 -*-
# @Author: ritesh
# @Date: 2015-08-21 14:47:47
# @Last Modified by: ritesh
# @Last Modified time: 2015-08-21 15:46:25
# import the necessary packages
from descriptor import RGBHistogram
import argparse
import cPickle
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 computed index will be stored")
args = vars(ap.parse_args())
# initialize the index dictionary to store our our quantifed
# images, with the 'key' of the dictionary being the image
# filename and the 'value' our computed features
index = {}
# initialize our image descriptor -- a 3D RGB histogram with
# 8 bins per channel
desc = RGBHistogram([8, 8, 8])
# use glob to grab the image paths and loop over them
for imagePath in glob.glob(args["dataset"] + "/*.*"):
# extract our unique image ID (i.e. the filename)
k = imagePath[imagePath.rfind("/") + 1:]
# load the image, describe it using our RGB histogram
# descriptor, and update the index
image = cv2.imread(imagePath)
features = desc.describe(image)
index[k] = features
# we are now done indexing our image -- now we can write our
# index to disk
f = open(args["index"], "w")
f.write(cPickle.dumps(index))
f.close()