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标注自己的数据集,训练、评估、测试、部署自己的人工智能算法

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train_custom_dataset's Introduction

子豪兄带你两天搞定AI毕业设计

标注自己的数据集,训练、评估、测试、部署自己的人工智能算法

作者:同济子豪兄 https://space.bilibili.com/1900783

代码测试云GPU环境:GPU RTX 3060、CUDA v11.2

优雅地感谢子豪兄

本教程的数据集、代码全部免费开源,数据集图像来自网络图片,仅用于教学、科研、科普等非盈利行为。任何后果与作者无关。

计算机视觉解决的基本问题

目标追踪、视频人流量计数

https://www.bilibili.com/video/BV1za411Y7Zm

大模型摘要生成

https://www.bilibili.com/video/BV1W44y1g7cB

CycleGAN图像风格迁移

https://www.bilibili.com/video/BV1wv4y1T71F

OCR文字识别

https://www.bilibili.com/video/BV1Ua411x7dB

图像分类

构建自己的图像分类数据集

收集图像、下载样例数据集,删除系统多余文件,划分训练集、测试集,统计图像尺寸、比例分布、拍照地点位置分布,统计各类别图像数量

https://www.bilibili.com/video/BV1Jd4y1T7rw

【Pytorch】ImageNet预训练图像分类模型预测

使用Pytorch自带的预训练图像分类模型,分别对单张图像、视频、摄像头实时画面运行图像分类预测

https://www.bilibili.com/video/BV1qe4y1D7zD

【Pytorch】迁移学习Fine-tuning训练自己的图像分类模型

迁移学习Fine-tuning训练、测试集评估、混淆矩阵、单张图像测试、视频测试、摄像头画面测试

【Pytorch】模型部署(智能手机、开发板)

【MMClassification】迁移学习Fine-tune训练自己的图像分类模型

可解释性分析

CAM可视化

【MMDeploy】模型部署(智能手机、开发板)

目标检测

标注自己的目标检测数据集

MS COCO预训练模型预测单张图像、视频、摄像头画面

YOLOV5训练自己的目标检测模型

模型部署(智能手机、开发板)

MMDetection训练自己的目标检测模型

图像分割

标注自己的图像分割数据集

关键点检测

标注自己的关键点检测数据集

声音分类

知识图谱

train_custom_dataset's People

Contributors

tommyzihao avatar

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