登录
首页 » Python » SLIC超像素1

SLIC超像素1

于 2020-07-08 发布
0 247
下载积分: 1 下载次数: 1

代码说明:

说明:  通过超像素算法,读入图片确定分割数,得到最佳图像分割结果(Through the superpixel algorithm, read in the picture to determine the number of divisions to get the best image segmentation result)

文件列表:

SLIC超像素1.ipynb, 147103 , 2020-05-11

下载说明:请别用迅雷下载,失败请重下,重下不扣分!

发表评论

0 个回复

  • 基于稀疏表达的多源数据融合spatiotemporal
    说明:  基于稀疏表达的多源图像数据融合,遥感图像融合(Multi-source image data fusion based on sparse expression, remote sensing image fusion)
    2020-07-13 16:48:52下载
    积分:1
  • 光强分布MATLAB
    说明:  matlab编写高斯光束高斯光束模拟的焦点附近光场分布(Matlab programming of Gaussian beam the distribution of light field near the focus of Gaussian beam simulation)
    2020-12-03 15:19:25下载
    积分:1
  • binocular_stereo_measuring
    通过两台相机拍摄的立体像对完成对目标的快速实时测量,用于构建道路交通等数据快速采集系统。(Through two three-dimensional camera for the completion of the goal as fast real-time measurement, used to build road traffic, such as rapid data acquisition system.)
    2007-09-27 22:36:56下载
    积分:1
  • yijie_HMM
    1阶HMM模型多个观察值序列的评估和训练问题模型。适合用于图像纹理的去噪,分割等问题。程序用于为网友提供学习之用,由于是自编自用,所以如有不通的地方仅供参考。另由于数据较大,没有上传。(Evaluation and Training of multiObservation sequence Used by 1-order HMM)
    2020-06-28 12:40:02下载
    积分:1
  • Registration
    主要是对视网膜图像进行血管分割,效果还不错(Primarily on retinal vascular image segmentation, the effect was not bad)
    2021-04-26 21:18:45下载
    积分:1
  • number
    将图片转化为BMP位图,然后通过逐行扫描识别图片中的数字。(A picture into a BMP bitmap, and then through the progressive scanned image in the figure.)
    2009-10-15 16:05:44下载
    积分:1
  • SFM
    计算机视觉中,structure from motion的代码(computer vision, structure from motion code)
    2007-05-24 16:22:05下载
    积分:1
  • haar_adaboost_vehicle_detection
    说明:  基于Haar+AdaBoost+bdd100k数据集做车辆识别(Vehicle recognition based on Haar + AdaBoost + bdd100k dataset)
    2020-11-02 14:12:20下载
    积分:1
  • hough1
    hough 检测直线 算法简单 是静态图像中检测直线的快速实现( Hough detecting )
    2009-11-07 20:01:46下载
    积分:1
  • heiv_src
    C++ code implementing the estimation of errors-in-variables models under point dependent noise. It includes examples for linear, ellipse, fundamental matrix and trifocal tensor estimation. The theory is described in A general method for errors-in-variables problems in computer vision(err)
    2020-12-18 20:19:10下载
    积分:1
  • 696516资源总数
  • 106914会员总数
  • 0今日下载