batchPrepare Namespace Reference

Variables
int	height = 300
int	width = 300
int	NUM_BATCHES = 0
int	NUM_PER_BATCH = 1
int	NUM_CALIBRATION_IMAGES = 50
	parser = argparse.ArgumentParser()
	required
	True
	help
	args = parser.parse_args()
string	CALIBRATION_DATASET_LOC = args.inDir + '/*.jpg'
list	imgs = []
string	outDir = args.outDir+"/batches"
int	img = 0
string	batchfile = outDir + "/batch_calibration" + str(i) + ".batch"
string	batchlistfile = outDir + "/batch_calibration" + str(i) + ".list"
	batchlist = open(batchlistfile,'a')
	batch = np.zeros(shape=(NUM_PER_BATCH, 3, height, width), dtype = np.float32)
	im = Image.open(imgs[img]).resize((width,height), Image.NEAREST)
	in_ = np.array(im, dtype=np.float32, order='C')
	ba = bytearray(struct.pack("4i", batch.shape[0], batch.shape[1], batch.shape[2], batch.shape[3]))
	content = f.read()

Variable Documentation

height

int batchPrepare.height = 300

width

int batchPrepare.width = 300

NUM_BATCHES

int batchPrepare.NUM_BATCHES = 0

NUM_PER_BATCH

int batchPrepare.NUM_PER_BATCH = 1

NUM_CALIBRATION_IMAGES

int batchPrepare.NUM_CALIBRATION_IMAGES = 50

parser

batchPrepare.parser = argparse.ArgumentParser()

required

batchPrepare.required

True

batchPrepare.True

help

batchPrepare.help

args

batchPrepare.args = parser.parse_args()

CALIBRATION_DATASET_LOC

string batchPrepare.CALIBRATION_DATASET_LOC = args.inDir + '/*.jpg'

imgs

list batchPrepare.imgs = []

outDir

string batchPrepare.outDir = args.outDir+"/batches"

img

int batchPrepare.img = 0

batchfile

string batchPrepare.batchfile = outDir + "/batch_calibration" + str(i) + ".batch"

batchlistfile

string batchPrepare.batchlistfile = outDir + "/batch_calibration" + str(i) + ".list"

batchlist

batchPrepare.batchlist = open(batchlistfile,'a')

batch

batchPrepare.batch = np.zeros(shape=(NUM_PER_BATCH, 3, height, width), dtype = np.float32)

im

batchPrepare.im = Image.open(imgs[img]).resize((width,height), Image.NEAREST)

in_

batchPrepare.in_ = np.array(im, dtype=np.float32, order='C')

ba

batchPrepare.ba = bytearray(struct.pack("4i", batch.shape[0], batch.shape[1], batch.shape[2], batch.shape[3]))

content

batchPrepare.content = f.read()