index.py

# USAGE
# python index.py --dataset dataset --index index.csv

# import the necessary packages
from pyimagesearch.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 computed index will 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")

# use glob to grab the image paths and loop over them
globpath = []
globpath = globpath + glob.glob(args["dataset"] + "/*.png")
globpath = globpath + glob.glob(args["dataset"] + "/*.jpg")
# for imagePath in glob.glob(args["dataset"] + "/*.png"):
for imagePath in globpath:
	# extract the image ID (i.e. the unique filename) from the image
	# path and load the image itself
	# imageID = imagePath[imagePath.rfind("/") + 1:]
	imageID = imagePath[imagePath.rfind("\\") + 1:]
	image = cv2.imread(imagePath)

	# describe the image
	features = cd.describe(image)

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


# for imagePath in glob.glob(args["dataset"] + "/*.jpg"):
# 	# extract the image ID (i.e. the unique filename) from the image
# 	# path and load the image itself
# 	# imageID = imagePath[imagePath.rfind("/") + 1:]
# 	imageID = imagePath[imagePath.rfind("\\") + 1:]
# 	image = cv2.imread(imagePath)
#
# 	# describe the image
# 	features = cd.describe(image)
#
# 	# write the features to file
# 	features = [str(f) for f in features]
# 	output.write("%s,%s\n" % (imageID, ",".join(features)))

# close the index file
output.close()