랜덤 샘플 이미지

@torch.no_grad()
def inference(weight, name, img):
    if img is None:
        img = np.random.randint(0, 255, size=(112, 112, 3), dtype=np.uint8)
    else:
        img = cv2.imread(img)
        img = cv2.resize(img, (112, 112))

    img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
    img = np.transpose(img, (2, 0, 1))
    img = torch.from_numpy(img).unsqueeze(0).float()
    img.div_(255).sub_(0.5).div_(0.5)
    net = get_model(name, fp16=False)
    net.load_state_dict(torch.load(weight))
    net.eval()
    feat = net(img).numpy()
    print(feat)