Pycharm+Flask部分总结

Pycharm+Flask部分总结

一.新建project，注意所在位置，以及配备python版本

二.新建hash.py,进行分镜处理

from flask import Flask,render_template
import os
import cv2
 
 
app=Flask(__name__)
 
def genframe():
    v_path='static/vm1.mp4'
    image_save='static/pic'
 
    if not(os.path.exists(image_save)):
        os.mkdir(image_save)
 
    cap=cv2.VideoCapture(v_path)
    fc=cap.get(cv2.CAP_PROP_frame_COUNT)
 
    for i in range(int(fc)):
        _,img=cap.read()
        cv2.imwrite('static/pic/image{}.jpg'.format(i),img)
 
@app.route('/')
def index():
    #return "Hi,Flask!"
    #genframe()
    pic='static/pic/image'
    framecount=825
    return render_template('index.html',pic1=pic,framecount=framecount)
 
if "__main__"==__name__:
    app.run(port="5008")

三。新建html文件

    
    


视频分镜





帧数：{{framecount}}

{% for i in range(framecount) %}
    {pic1}}{{i}}.jpg" />
{% endfor %}

四。进行hash分镜

import cv2
import numpy as np
import matplotlib.pyplot as plt
import os
print(os.getcwd())
 
 
# 均值哈希算法
def aHash(img):
    # 缩放为8*8
#     plt.imshow(img)
#     plt.axis('off')  #去掉坐标轴
#     plt.show()
    img = cv2.resize(img, (8, 8))
#     plt.imshow(img)
#     plt.axis('off')  #去掉坐标轴
#     plt.show()
 
    # 转换为灰度图
    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
    # s为像素和初值为0，hash_str为hash值初值为''
    s = 0
    hash_str = ''
    # 遍历累加求像素和
    for i in range(8):
        for j in range(8):
            s = s + gray[i, j]
    # 求平均灰度
    avg = s / 64
    # 灰度大于平均值为1相反为0生成图片的hash值
    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
 
# Hash值对比
def cmpHash(hash1, hash2):
    n = 0
    print(hash1)
    print(hash2)
    # hash长度不同则返回-1代表传参出错
    if len(hash1)!=len(hash2):
        return -1
    # 遍历判断
    for i in range(len(hash1)):
        # 不相等则n计数+1，n最终为相似度
        if hash1[i] != hash2[i]:
            n = n + 1
    return n
 
 
# img1 = cv2.imread('./pic/image58.jpg')  #  11--- 16 ----13 ---- 0.43
# img2 = cv2.imread('./pic/image59.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/vm1.mp4'
    image_save='static/hash'
 
    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/hash/image{}.jpg'.format(0), img1)
    for i in range(int(fc)-1):
        _,img2=cap.read()
        hash1 = aHash(img1)
        hash2 = aHash(img2)
        n = cmpHash(hash1, hash2)
        if n>35:
            cv2.imwrite('static/hash/image{}.jpg'.format(i),img2)
            img1=img2
 
genframe()

五。修改html文件

    
    


视频分镜





{{imgcount}}

{% for f in filename %}
{f}}">
{% endfor %}

六。最后修改hash.py

@app.route('/hash')
def hash():
 
    path='static/hash'
    filename=os.listdir(path)
    print(type(filename))
    print(filename)
    imgcount=len(filename)
    return render_template('hash.html',imgcount=imgcount,filename=filename)