#! /usr/bin/env python

import numpy as np
import argparse
from cv2 import SVM_RBF, SVM_C_SVC
#from cv2.ml import SVM_RBF, SVM_C_SVC, ROW_SAMPLE # row_sample for layout in cv2.ml.SVM_load

import cvutils, moving, ml, storage

parser = argparse.ArgumentParser(description='The program extracts labeled image patches to train the HoG-SVM classifier, and optionnally speed information')
parser.add_argument('--cfg', dest = 'configFilename', help = 'name of the configuration file', required = True)

#parser.add_argument('-d', dest = 'directoryName', help = 'parent directory name for the directories containing the samples for the different road users', required = True)

args = parser.parse_args()
params = storage.ProcessParameters(args.configFilename)
classifierParams = storage.ClassifierParameters(params.classifierFilename)

# need all info as for classification (image info)

# todo speed info: distributions AND min speed equiprobable

# provide csv delimiter for the classification file as arg