▍1. 3Dircadb_unet
说明： 对脑肿瘤进行分割 基于3dunet(Brain tumors were segmented based on 3dunet)
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▍2. DensePose-master
DensePose用深度学习把2D图像坐标映射到3D人体表面上，再加上以每秒多帧的速度处理密集坐标，最后实现动态人物的精确定位和姿态估计。该技术集目标检测、姿态估计、目标部分/实例分割等多种计算机视觉任务于一身的一个综合问题。(DensePost maps 2D image coordinates to 3D human body surface by in-depth learning, and processes dense coordinates at the speed of multiple frames per second. Finally, it realizes precise positioning and attitude estimation of dynamic characters. This technology integrates many kinds of computer vision tasks, such as target detection, attitude estimation, target part/instance segmentation, etc.)
▍3. DensePose-master
说明： DensePose用深度学习把2D图像坐标映射到3D人体表面上，再加上以每秒多帧的速度处理密集坐标，最后实现动态人物的精确定位和姿态估计。该技术集目标检测、姿态估计、目标部分/实例分割等多种计算机视觉任务于一身的一个综合问题。(DensePost maps 2D image coordinates to 3D human body surface by in-depth learning, and processes dense coordinates at the speed of multiple frames per second. Finally, it realizes precise positioning and attitude estimation of dynamic characters. This technology integrates many kinds of computer vision tasks, such as target detection, attitude estimation, target part/instance segmentation, etc.)
▍6. threshold
python语言，三种阈值分割方式，简单阈值分割，自适应阈值分割，OTsu分割方式(Python language, three methods of image segmentation , simple threshold segmentation, adaptive threshold segmentation, OTsu segmentation)
▍7. threshold
说明： python语言，三种阈值分割方式，简单阈值分割，自适应阈值分割，OTsu分割方式(Python language, three methods of image segmentation , simple threshold segmentation, adaptive threshold segmentation, OTsu segmentation)
▍10. python pca svm
python实现人脸识别，通过pca进行降维然后使用SVM算法进行分类(Python realizes face recognition, dimensionality reduction through pca and classification by SVM algorithm)
▍11. python pca svm
说明： python实现人脸识别，通过pca进行降维然后使用SVM算法进行分类(Python realizes face recognition, dimensionality reduction through pca and classification by SVM algorithm)
▍12. Point Cloud Mosaic Using PCL
PCL是一个类似于OpenCV的开源库，提供了很多三维点云的处理功能，其中就包括点云拼接。在三维扫描项目中，需要利用点云拼接方法将多次扫描得到的点云数据拼合成一个整体。在本例中，用一幅包含人脸的深度图像去匹配之前获得的人脸模板，这将使我们能够确定人脸在场景中的位置和方向。(PCL is an open source library similar to OpenCV, which provides a lot of processing functions for three-dimensional point clouds, including point cloud mosaic. In the three-dimensional scanning project, it is necessary to use point cloud mosaic method to combine the point cloud data obtained from multiple scans into a whole. In this example, a depth image containing face is used to match the face template obtained before, which will enable us to determine the position and direction of the face in the scene.)
▍13. Point Cloud Mosaic Using PCL
说明： PCL是一个类似于OpenCV的开源库，提供了很多三维点云的处理功能，其中就包括点云拼接。在三维扫描项目中，需要利用点云拼接方法将多次扫描得到的点云数据拼合成一个整体。在本例中，用一幅包含人脸的深度图像去匹配之前获得的人脸模板，这将使我们能够确定人脸在场景中的位置和方向。(PCL is an open source library similar to OpenCV, which provides a lot of processing functions for three-dimensional point clouds, including point cloud mosaic. In the three-dimensional scanning project, it is necessary to use point cloud mosaic method to combine the point cloud data obtained from multiple scans into a whole. In this example, a depth image containing face is used to match the face template obtained before, which will enable us to determine the position and direction of the face in the scene.)
▍17. ImageSimilarity
计算img文件夹内所有图像之间的相似度，并根据相似度排序，呈现每个图片的最相似图片结果(calculate the image similarity of each pic in img filedir)
▍18. TensorFlow-Examples-master
基于Tensorflow的Unet实现，里面有详细的教程。(TensorFlow for Unet, in which there are detailed teaching lecture.)
▍20. exp_2_1
Iris数据集，计算协方差矩阵和相关系数矩阵和kl变换(The goal of this programming experiment is to: Calculate the covariance matrix and the correlation coefficient matrix of the Iris data set. Perform the Karhunen-Loeve transform on this data set.)
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