def __init__(self, argvs=[]): # self.argv_parser(argvs) parser = OptionParser() parser.add_option("-c", "--conf", dest="configure", help="configure filename") (options, args) = parser.parse_args() if options.configure: conf_file = str(options.configure) print('config loaded') else: print('please specify --conf configure filename') exit(0) self.common_params, self.dataset_params, self.net_params, self.solver_params = process_config( conf_file) print(self.common_params) print(self.dataset_params) print(self.net_params) print(self.solver_params) self.image_size = int(self.common_params['image_size']) self.batch_size = int(self.common_params['batch_size']) self.cell_size = int(self.net_params['cell_size']) self.boxes_per_cell = int(self.net_params['boxes_per_cell']) self.num_classes = int(self.common_params['num_classes']) self.object_scale = float(self.net_params['object_scale']) self.noobject_scale = float(self.net_params['noobject_scale']) self.class_scale = float(self.net_params['class_scale']) self.coord_scale = float(self.net_params['coord_scale']) self.max_objects = int(self.common_params['max_objects_per_image']) self.max_iterators = int(self.solver_params['max_iterators']) self.learning_rate = float(self.solver_params['learning_rate']) self.moment = float(self.solver_params['moment']) self.train_dir = self.solver_params['train_dir'] self.pretrain_path = str(self.solver_params['pretrain_model_path']) self.build_networks() # self.fromfile ='./cat.jpg' if self.fromfile is not None: self.detect_from_file(self.fromfile)
import sys from optparse import OptionParser sys.path.append('./') sys.path.append('./yolo/') import yolo from yolo.utils.process_config import process_config parser = OptionParser() parser.add_option("-c", "--conf", dest="configure", help="configure filename") (options, args) = parser.parse_args() if options.configure: conf_file = str(options.configure) else: print('please sspecify --conf configure filename') exit(0) common_params, dataset_params, net_params, solver_params = process_config( conf_file) dataset = eval(dataset_params['name'])(common_params, dataset_params) net = eval(net_params['name'])(common_params, net_params) solver = eval(solver_params['name'])(dataset, net, common_params, solver_params) solver.solve()
from optparse import OptionParser sys.path.append('./') import yolo import os from yolo.utils.process_config import process_config parser = OptionParser() parser.add_option("-c", "--conf", dest="configure", help="configure filename") parser.add_option("-g", "--gpu", dest="gpu", help="gpu_to_use") (options, args) = parser.parse_args() if options.configure: conf_file = str(options.configure) else: print('please sspecify --conf configure filename') exit(0) if options.gpu: os.environ['CUDA_VISIBLE_DEVICES'] = options.gpu else: print('please specify --gpu 0') exit(0) common_params, dataset_params, net_params, solver_params = process_config(conf_file) dataset = eval(dataset_params['name'])(common_params, dataset_params) net = eval(net_params['name'])(common_params, net_params) solver = eval(solver_params['name'])(dataset, net, common_params, solver_params) solver.solve()