#!/usr/bin/env python3 # -*- coding: utf-8 -*- """ Created on Fri Sep 14 21:02:42 2018 @author: jbuisine """ from __future__ import print_function import sys, os, getopt import numpy as np import random import time import json config_filename = "config" zone_folder = "zone" min_max_filename = "min_max_values" output_file_svd = "SVD_LAB_test_im6.csv" output_file_svdn = "SVDN_LAB_test_im6.csv" output_file_svdne = "SVDNE_LAB_test_im6.csv" # define all scenes values scenes = ['Appart1opt02', 'Bureau1', 'Cendrier', 'Cuisine01', 'EchecsBas', 'PNDVuePlongeante', 'SdbCentre', 'SdbDroite', 'Selles'] scenes_indexes = ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I'] choices = ['svd', 'svdn', 'svdne'] path = './fichiersSVD' zones = np.arange(16) file_choice = [output_file_svd, output_file_svdn, output_file_svdne] seuil_expe_filename = 'seuilExpe' def generate_data_svd_lab(): """ @brief Method which generates all .csv files from scenes photos @param path - path of scenes folder information @return nothing """ # TODO : # - parcourir chaque dossier de scene scenes = os.listdir(path) for folder_scene in scenes: folder_path = path + "/" + folder_scene with open(folder_path + "/" + config_filename, "r") as config_file: last_image_name = config_file.readline().strip() prefix_image_name = config_file.readline().strip() start_index_image = config_file.readline().strip() end_index_image = config_file.readline().strip() step_counter = int(config_file.readline().strip()) current_counter_index = int(start_index_image) end_counter_index = int(start_index_image) print(current_counter_index) while(current_counter_index <= end_index_image): print(current_counter_index) current_counter_index += step_counter # - récupérer les informations des fichiers de configurations # - création des fichiers de sortie SVD, SVDE, SVDNE def construct_new_line(path_seuil, interval, line, sep, index): begin, end = interval line_data = line.split(';') seuil = line_data[0] metrics = line_data[begin+1:end+1] with open(path_seuil, "r") as seuil_file: seuil_learned = int(seuil_file.readline().strip()) if seuil_learned > int(seuil): line = '0' else: line = '1' for idx, val in enumerate(metrics): if index: line += " " + str(idx + 1) line += sep line += val line += '\n' return line def generate_data_svm(_filename, _interval, _choice, _scenes = scenes, _nb_zones = 4, _percent = 1, _sep=':', _index=True): output_train_filename = _filename + ".train" output_test_filename = _filename + ".test" if not '/' in output_train_filename: raise Exception("Please select filename with directory path to save data. Example : data/dataset") # create path if not exists output_folder = output_train_filename.split('/')[0] if not os.path.exists(output_folder): os.makedirs(output_folder) train_file = open(output_train_filename, 'w') test_file = open(output_test_filename, 'w') scenes = os.listdir(path) for id_scene, folder_scene in enumerate(scenes): scene_path = path + "/" + folder_scene zones_folder = [] # create zones list for index in zones: index_str = str(index) if len(index_str) < 2: index_str = "0" + index_str zones_folder.append("zone"+index_str) # shuffle list of zones (=> randomly choose zones) random.shuffle(zones_folder) for id_zone, zone_folder in enumerate(zones_folder): zone_path = scene_path + "/" + zone_folder data_filename = file_choice[choices.index(_choice)] data_file_path = zone_path + "/" + data_filename # getting number of line and read randomly lines f = open(data_file_path) lines = f.readlines() num_lines = len(lines) lines_indexes = np.arange(num_lines) random.shuffle(lines_indexes) path_seuil = zone_path + "/" + seuil_expe_filename counter = 0 # check if user select current scene and zone to be part of training data set for index in lines_indexes: line = construct_new_line(path_seuil, _interval, lines[index], _sep, _index) percent = counter / num_lines if id_zone < _nb_zones and folder_scene in _scenes and percent <= _percent: train_file.write(line) else: test_file.write(line) counter += 1 f.close() train_file.close() test_file.close() def main(): if len(sys.argv) <= 1: print('Run with default parameters...') print('python generate_data.py --output xxxx --interval 0,20 --kind svdne --scenes "A, B, D" --nb_zones 5 --percent 0.7 --sep : --rowindex 1') sys.exit(2) try: opts, args = getopt.getopt(sys.argv[1:], "ho:i:k:s:n:p:r", ["help=", "output=", "interval=", "kind=", "scenes=", "nb_zones=", "percent=", "sep=", "rowindex="]) except getopt.GetoptError: # print help information and exit: print('python generate_data.py --output xxxx --interval 0,20 --kind svdne --scenes "A, B, D" --nb_zones 5 --percent 0.7 --sep : --rowindex 1') sys.exit(2) for o, a in opts: if o == "-h": print('python generate_data.py --output xxxx --interval 0,20 --kind svdne --scenes "A, B, D" --nb_zones 5 --percent 0.7 --sep : --rowindex 1') sys.exit() elif o in ("-o", "--output"): p_filename = a elif o in ("-i", "--interval"): p_interval = list(map(int, a.split(','))) elif o in ("-k", "--kind"): p_kind = a elif o in ("-s", "--scenes"): p_scenes = a.split(',') elif o in ("-n", "--nb_zones"): p_nb_zones = int(a) elif o in ("-p", "--percent"): p_percent = float(a) elif o in ("-s", "--sep"): p_sep = a elif o in ("-r", "--rowindex"): if int(a) == 1: p_rowindex = True else: p_rowindex = False else: assert False, "unhandled option" # getting scenes from indexes user selection scenes_selected = [] for scene_id in p_scenes: index = scenes_indexes.index(scene_id.strip()) scenes_selected.append(scenes[index]) for scene in scenes_selected: print(scene) # create database using img folder (generate first time only) generate_data_svm(p_filename, p_interval, p_kind, scenes_selected, p_nb_zones, p_percent, p_sep, p_rowindex) if __name__== "__main__": main()