def load_faceboxes():
"""
Load FaceBoxes model and weight in pytorch
"""
print('---------------------------------------------------')
pretrained_path = 'weights/FaceBoxes.pth'
net = FaceBoxes(phase='test', size=None,
num_classes=2) # initialize detector
net = load_model(net, pretrained_path)
net.eval()
print('Finished loading model')
print('---------------------------------------------------')
return net.cpu()
model.load_state_dict(pretrained_dict, strict=False)
return model
if __name__ == '__main__':
# net and model
net = FaceBoxes(phase='test', size=None, num_classes=2) # initialize detector
net = load_model(net, args.trained_model)
net.eval()
print('Finished loading model!')
print(net)
if args.cuda:
net = net.cuda()
cudnn.benchmark = True
else:
net = net.cpu()
# save file
if not os.path.exists(args.save_folder):
os.makedirs(args.save_folder)
fw = open(os.path.join(args.save_folder, args.dataset + '_dets.txt'), 'w')
# testing dataset
testset_folder = os.path.join('data', args.dataset, 'images/')
testset_list = os.path.join('data', args.dataset, 'img_list.txt')
with open(testset_list, 'r') as fr:
test_dataset = fr.read().split()
num_images = len(test_dataset)
# testing scale
if args.dataset == "FDDB":