YOLOX Win10 Project

class Exp(MyExp):
    def __init__(self):
        super(Exp, self).__init__()
        self.num_classes = 42         #修改成自己的类别
        self.depth = 0.33
        self.width = 0.50
        self.warmup_epochs = 1

class Exp(BaseExp):
    def __init__(self):
        super().__init__()

        # ---------------- model config ---------------- #
        self.num_classes = 80  #因为在yolox_voc_s.py中已经重新赋值，此处不用修改
        self.depth = 1.00
        self.width = 1.00
        self.act = 'silu'

        # ---------------- dataloader config ---------------- #
        # set worker to 4 for shorter dataloader init time
        self.data_num_workers = 1
        self.input_size = (640, 640)  # (height, width)
        # Actual multiscale ranges: [640-5*32, 640+5*32].
        # To disable multiscale training, set the
        # self.multiscale_range to 0.
        self.multiscale_range = 5 #五种输入大小随机调整
        # You can uncomment this line to specify a multiscale range
        # self.random_size = (14, 26)
        self.data_dir = None
        self.train_ann = "instances_train2017.json"
        self.val_ann = "instances_val2017.json"

        # --------------- transform config ----------------- #
        self.mosaic_prob = 1.0   #数据增强概率，可以根据需要调整
        self.mixup_prob = 1.0
        self.hsv_prob = 1.0
        self.flip_prob = 0.5
        self.degrees = 10.0
        self.translate = 0.1
        self.mosaic_scale = (0.1, 2)
        self.mixup_scale = (0.5, 1.5)
        self.shear = 2.0
        self.enable_mixup = True

        # --------------  training config --------------------- #
        self.warmup_epochs = 5
        self.max_epoch = 100  #设置训练轮数
        self.warmup_lr = 0
        self.basic_lr_per_img = 0.01 / 64.0
        self.scheduler = "yoloxwarmcos"
        self.no_aug_epochs = 15 #不适用数据增强轮数
        self.min_lr_ratio = 0.05
        self.ema = True

        self.weight_decay = 5e-4
        self.momentum = 0.9
        self.print_interval = 10 #每隔十步打印输出一次训练信息
        self.eval_interval = 1 #每隔1轮保存一次
        self.exp_name = os.path.split(os.path.realpath(__file__))[1].split(".")[0]

        # -----------------  testing config ------------------ #
        self.test_size = (640, 640)
        self.test_conf = 0.01
        self.nmsthre = 0.65

python tools/train.py  -c /path/to/yolox_s.pth

python tools/train.py  -d 1 -b 8 --fp16 -c /path/to/yolox_s.pth

python tools/train.py --resume

python tools/eval.py

python tools/eval.py -n  yolox-s -c yolox_s.pth -b 8 -d 1 --conf 0.001 
                         yolox-m
                         yolox-l
                         yolox-x