年龄性别分类
使用OUI-Adience dataset，预训练的Resnet50和MobilenetV3模型
最终精度：性别96.94%，年龄78.79% (resnet50)；性别96.12%，年龄82.12% (mobilenet_v3)
MobilenetV3实现源自pytorch-image-models
预训练模型：
模型输入图像大小224x224，输出age_logits (bs x 8), gender_logits (bs x 3) age logits——0-2, 3-6, 8-13, 15-20, 22-32, 34-43, 45-53, 55-100的8组中每组的图像概率
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