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":