Coding

安装

1. 下载并安装anaconda

   https://www.anaconda.com/distribution/
   *不用安装python,anaconda中自带python执行环境
   *并且安装了pip包管理工具,conda安装提示的包没有的话，可以用pip进行安装
   

2. 安装OpenCV、numpy

   conda install opencv
   

3. 安装tensorflow

   conda install tensorflow
   

4. 下载并安装CUDA

   https://developer.nvidia.com/cuda-downloads
   *最好安装一下显卡的最新驱动
   

5. 下载并安装cuDDN

   https://developer.nvidia.com/cudnn
   *版本要和CUDA版本相对应
   

6. 安装GPU版本的tensorflow

   conda uninstall tensorflow
   conda install tensorflow-gpu
   

7. 下载并安装PyCharm,也可以直接使用anaconda自带的Jupyter编写python

   https://www.jetbrains.com/pycharm/download/#section=windows
   *下载社区版本即刻
   

8. 配置PyCharm环境

   

   

   

9. 使用Jupyter

   

   

   

第一个OpenCV程序

import cv2

img = cv2.imread('0004.jpg')
gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
gray = cv2.equalizeHist(gray);
binary = cv2.Canny(gray,  50, 200,apertureSize=3,L2gradient=False);
img1, contours, hierarchy = cv2.findContours(binary,cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE)
cv2.drawContours(img,contours,-1,(0,0,255),3)
cv2.imwrite("test.jpg", img)

第一个numpy程序

import numpy
import math
def softmax(isMatrix):
    m,n = numpy.shape(isMatrix)
    outMatrix = numpy.mat(numpy.zeros((m,n)))
    soft_sum = 0
    for idx in range(0,n):
        outMatrix[0,idx] = math.exp(isMatrix[0,idx])
        soft_sum += outMatrix[0,idx]
    for idx in range(0,n):
        outMatrix[0,idx] = outMatrix [0,idx] / soft_sum
    return outMatrix

def main():
    result = softmax(numpy.array([[1,2,1,2,1,1,3]]))
    print(result)

if __name__ == '__main__':
    main()

第一个tensorflow程序

import tensorflow as tf
hello = tf.constant("hello tensorflow")
sess = tf.Session()
print(sess.run(hello))

代码

https://github.com/tomsnail/opencv_tf_py

数据集

资源

https://www.jianshu.com/nb/4904019

http://blog.topspeedsnail.com/archives/tag/tensorflow

https://cloud.tencent.com/developer/labs/gallery?tagId=12