第七节课 pycharm——哈希算法和聚类色彩提取

第七节课 pycharm——哈希算法和聚类色彩提取

1.哈希算法

总体程序和之前在jupyternotebook上的差不多，但是需要做部分改动。

from flask import Flask, render_template
import cv2
import os

app = Flask(__name__)

def aHash(img):
    img = cv2.resize(img, (8, 8))

    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
    s = 0
    hash_str = ''
    for i in range(8):
        for j in range(8):
            s = s + gray[i, j]
    avg = s / 64
    for i in range(8):
        for j in range(8):
            if gray[i, j] > avg:
                hash_str = hash_str + '1'
            else:
                hash_str = hash_str + '0'
    return hash_str


def cmpHash(hash1, hash2):
    n = 0
    print(hash1)
    print(hash2)
    if len(hash1) != len(hash2):
        return -1
    for i in range(len(hash1)):
        if hash1[i] != hash2[i]:
            n = n + 1
    sim = 1-n/64
    return sim


#img1 = cv2.imread('./pic/image0.jpg')
#img2 = cv2.imread('./pic/image1.jpg')

#hash1 = aHash(img1)
#hash2 = aHash(img2)
#n = cmpHash(hash1, hash2)
#print('均值哈希算法相似度：', n)

def genframe():
    v_path = 'static/video.mp4'
    image_save = 'static/Hash2021'

    if not(os.path.exists(image_save)):
        os.mkdir(image_save)

    cap = cv2.VideoCapture(v_path)
    fc = cap.get(cv2.CAP_PROP_frame_COUNT)

    _, img1 = cap.read()
    cv2.imwrite('static/Hash2021/image{}.jpg'.format(0), img1)

    for i in range(int(fc)):
        _, img2 = cap.read()
        hash1 = aHash(img1)
        hash2 = aHash(img2)
        n = cmpHash(hash1, hash2)
        if n < 0.6:
            cv2.imwrite('static/Hash2021/image{}.jpg'.format(i), img2)
            img1 = img2

genframe()

以上这步是将通过哈希算法，分析出视频中不同的帧并保存

运行这一步时需要将右上角的运行程序进行更改，否则将会一直默认运行“main”文件

html文件写：

    
    




均值哈希帧数:{{framecount}}

{% for i in range(framecount)%}
{filename[i]}}"/>
{{filename[i]}}
{% endfor%}

然后再在“main”文件中加入一个新的路由器程序

@app.route('/shot')
def shot():
    path='static/Hash2021'
    filename=os.listdir(path)
    framecount=len(filename)
    filename.sort(key=lambda x:int(x[5:-4]))
    print(filename)
    print(type(filename))

    print(filename)
    return render_template('hash.html',filename=filename,framecount=framecount)

将右上角改回“main”并运行

得到的页面需要在网址后面加上‘/shot’

​​​​​​​

2. 聚类色彩提取

先在jupyternotebook上进行分段写，最后再拼在pycharm里

import numpy as np
import os
from PIL import Image
import matplotlib.pyplot as plt

im=np.array(Image.open('IMG_7433.JPG'))

def colorz(filename,n=3):
    img=Image.open(filename)
    img=img.rotate(-90)
    img.thumbnail((200,200))
    w,h=img.size
    print(w,h)
    print('w*h=',w*h)
    plt.axis('off')
    plt.imshow(img)
    plt.show()
    points=[]
    for count,color in img.getcolors(w*h):
        points.append(color)
    return points
colorz('IMG_7433.JPG',3)

通过以上代码将图片颜色进行提取：

import numpy as np
from scipy.cluster.vq import vq, kmeans, whiten
import matplotlib.pyplot as plt

points=colorz('IMG_7433.JPG',3)
print(points[0:10])
fe=np.array(points,dtype=float)
print(fe[0:10])
book=np.array((fe[100],fe[1],fe[8],fe[8]))
print(type(book))
print("book:n",book)

codebook,distortion=kmeans(fe,7)
print("codebook:",codebook)
centers=np.array(codebook,dtype=int)
print(centers)
print("distortion:",distortion)

fe=np.array(points)
plt.scatter(fe[:,0],fe[:,2],c='b')
plt.scatter(codebook[:,0],codebook[:,2],c='r')
plt.show()

生成色彩聚类图

 

然后将以上片段粘贴到pycharm的imageColor文件里

import numpy as np
from scipy.cluster.vq import vq, kmeans, whiten
from PIL import Image

def colorz(filename,n=3):
    img=Image.open(filename)
    img=img.rotate(-90)
    img.thumbnail((200,200))
    w,h=img.size
    print(w,h)
    print('w*h=',w*h)
    points=[]
    for count,color in img.getcolors(w*h):
        points.append(color)
    return points
def kmeansColor(img,n):
    points=colorz(img,3)
    fe=np.array(points,dtype=float)
    codebook,distortion=kmeans(fe,n)
    centers=np.array(codebook,dtype=int)
    return centers

main文件中加入

from flask import Flask, render_template
import os
import cv2
import imageColor

@app.route('/')#这是路由器
def index():
    #return "Hi,Flask!"
    #genframe()
    pic = 'static/pic/image'
    framecount = 254
    imgcolors=imageColor.kmeansColor('static/pic/image0.jpg',5)
    return render_template('index.html', pic1=pic, framecount=framecount,imgcolors=imgcolors)

一定要注意拼写！拼写！拼写！

index中其他内容都不用删掉，加入： 

帧数：{{framecount}}

{{imgcolors}}

{% for c in imgcolors %}
video
{% endfor %}

运行结果：

​​​​​​​