bf93c0a1393731b2b3d8afc7055ece2abea55f4e,detect.py,,,#,24

Before Change

    opt = parser.parse_args()
    print(opt)

    cuda = torch.cuda.is_available()

    os.makedirs("output", exist_ok=True)

    // Set up model
    model = Darknet(opt.config_path, img_size=opt.img_size)

    if opt.weights_path.endswith(".weights"):
        // Load darknet weights
        model.load_darknet_weights(opt.weights_path)
    else:
        // Load checkpoint weights
        model.load_state_dict(torch.load(opt.weights_path))

    if cuda:
        model.cuda()

    model.eval()  // Set in evaluation mode

    dataloader = DataLoader(
        ImageFolder(opt.image_folder, img_size=opt.img_size),

After Change

    opt = parser.parse_args()
    print(opt)

    device = torch.device("cuda" if torch.cuda.is_available() else "cpu")

    os.makedirs("output", exist_ok=True)

Instances