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()