# initialize our image descriptor -- a 3D RGB histogram with
# 8 bins per channel
desc = RGBHistogram([8, 8, 8])
# load the image, describe it using our RGB histogram
# descriptor, and update the index
image = cv2.imread(args["dataset"] + "/" + args["file"])
features = desc.describe(image)
index[args["file"]] = features
# we are now done indexing our image -- now we can write our
# index to disk
s.insert(
{
"name": args["file"],
"features": cPickle.dumps(features),
"created_at": datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S"),
}
)
# f = open(args["index"], "a")
# f.write(cPickle.dumps(index))
# f.close()
# show how many images we indexed
# index = cPickle.loads(open(args["index"]).read())
print "done...add indexed %d images" % (len(index))
print "has exist"
sys.exit(0)
index = {}
# initialize our image descriptor -- a 3D RGB histogram with
# 8 bins per channel
desc = RGBHistogram([8, 8, 8])
# load the image, describe it using our RGB histogram
# descriptor, and update the index
image = cv2.imread(args["dataset"] + "/" + args["file"])
features = desc.describe(image)
index[args["file"]] = features
# we are now done indexing our image -- now we can write our
# index to disk
s.insert({
'name': args["file"],
'features': cPickle.dumps(features),
'created_at': datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S")
})
# f = open(args["index"], "a")
# f.write(cPickle.dumps(index))
# f.close()
# show how many images we indexed
#index = cPickle.loads(open(args["index"]).read())
print "done...add indexed %d images" % (len(index))
