python 视频图片转换 分辨率处理

 

• 单个视频转图片
• 所有图片转视频
• 视频压缩 - ffmpeg
• 图片降低分辨率
• 图像处理

 

这是最近无聊的想法，对视频进行处理，其实也就是对图片的处理。

对视频进行后期处理，思路就是，视频转图片，然后对图片进行处理，再把图片转视频。

图片处理的多么奇怪，视频就多么奇怪，我当时想了想觉得挺好玩就做了玩玩。

视频可能很大，对视频处理要花好长时间，所以还进行了视频压缩等操作。

用到的代码如下。

单个视频转图片

'''
提取单个视频的所有帧
'''
import cv2
import numpy as np
def save_image(image,addr,num):
    #存储的图片路径
    address=addr+str(num)+'.jpg'
    #存储图片
    cv2.imwrite(address,image)
#读入视频
videoCapture=cv2.VideoCapture("./video/snowman.mp4")
#读取视频帧
success,frame=videoCapture.read()
i=0
while success:
    i=i+1
    #保存图片
    save_image(frame,'./img/',i)
    if success:
        print('save image:',i)
    #读取视频帧
    sucess,frame=videoCapture.read()

所有图片转视频

import cv2
import os
fps = 29#帧速率
fourcc = cv2.VideoWriter_fourcc(*'mp4v')
video_writer = cv2.VideoWriter(filename='./c.mp4', fourcc=fourcc, fps=fps, frameSize=(1080, 1920))  # 图片实际尺寸，不然生成的视频会打不开
for i in range(1,258):
  p = i
  if os.path.exists('./img/'+str(p)+'.jpg'):  #判断图片是否存在
    img = cv2.imread(filename='./img/'+str(p)+'.jpg')
    #cv2.waitKey(100)
    video_writer.write(img)
video_writer.release()

视频压缩 - ffmpeg

在命令行输入：python ZIP.py ./ c.mp4 c2.mp4

import sys
import os
import zlib
import threading
import platform
from PIL import Image

# python press.py ./ 12.mp4 23.mp4
# python 文件名  路径 要压缩的文件 压缩之后的文件名

# python ZIP.py ./ c.mp4 c2.mp4
#filePath = "./"
#inputName = "c.mp4"
#outName = "c2.mp4"

class Compress_Pic_or_Video(object):
    def __init__(self,filePath,inputName,outName=""):
        self.filePath = filePath  #文件地址
        self.inputName = inputName  #输入的文件名字
        self.outName = outName  #输出的文件名字
        self.system_ = platform.platform().split("-",1)[0]
        if  self.system_ ==  "Windows":
            self.filePath = (self.filePath + "\\") if self.filePath.rsplit("\\",1)[-1] else self.filePath
        elif self.system_ == "Linux":
            self.filePath = (self.filePath + "/") if self.filePath.rsplit("/",1)[-1] else self.filePath
        self.fileInputPath = self.filePath + inputName
        self.fileOutPath = self.filePath + outName

    @property
    def is_video(self):
        videoSuffixSet = {"WMV","ASF","ASX","RM","RMVB","MP4","3GP","MOV","M4V","AVI","DAT","MKV","FIV","VOB"}
        suffix = self.fileInputPath.rsplit(".",1)[-1].upper()
        if suffix in videoSuffixSet:
            return True
        else:
            return False

    def SaveVideo(self):
        fpsize = os.path.getsize(self.fileInputPath) / 1024
        if fpsize >= 150.0: #大于150KB的视频需要压缩
            if self.outName:
                compress = "ffmpeg -i {} -r 10 -pix_fmt yuv420p -vcodec libx264 -preset veryslow -profile:v baseline  -crf 23 -acodec aac -b:a 32k -strict -5 {}".format(self.fileInputPath,self.fileOutPath)
                isRun = os.system(compress)
            else:
                compress = "ffmpeg -i {} -r 10 -pix_fmt yuv420p -vcodec libx264 -preset veryslow -profile:v baseline  -crf 23 -acodec aac -b:a 32k -strict -5 {}".format(self.fileInputPath, self.fileInputPath)
                isRun = os.system(compress)
            if isRun != 0:
                return (isRun,"没有安装ffmpeg")
            return True
        else:
            return True

    def Compress_Video(self):
        # 异步保存打开下面的代码，注释同步保存的代码
        # thr = threading.Thread(target=self.SaveVideo)
        # thr.start()
        #下面为同步代码
        fpsize = os.path.getsize(self.fileInputPath) / 1024
        if fpsize >= 150.0:  # 大于150KB的视频需要压缩
            compress = "ffmpeg -i {} -r 10 -pix_fmt yuv420p -vcodec libx264 -preset veryslow -profile:v baseline  -crf 23 -acodec aac -b:a 32k -strict -5 {}".format(
                self.fileInputPath, self.fileOutPath)
            isRun = os.system(compress)
            if isRun != 0:
                return (isRun, "没有安装ffmpeg")
            return True
        else:
            return True

if __name__ == "__main__":
    b = sys.argv[1:]	#测试压缩
    savevideo = Compress_Pic_or_Video(b[0],b[1],b[2])
    print(savevideo.Compress_Video())

图片降低分辨率

#coding=utf-8
import os  #打开文件时需要
from PIL import Image
import re

Start_path='C:/Users/jym/PycharmProjects/video2picture/img/'
end_path='C:/Users/jym/PycharmProjects/video2picture/img2/'
new_width=281
new_depth=500
list=os.listdir(Start_path)
#print list
count=0
for pic in list:
    path=Start_path+pic
    im=Image.open(path)
    w,h=im.size
    h_new=new_depth
    w_new=new_width
    count=count+1
    out = im.resize((w_new,h_new),Image.ANTIALIAS)
    #new_pic=re.sub(pic[:-4],pic[:-4]+'_new',pic)
    new_pic=pic
    new_path=end_path+new_pic
    out.save(new_path)

count=str(count)

图像处理

import cv2
import os
import numpy as np
from matplotlib import pyplot as plt


def read_path(file_pathname):
    #遍历该目录下的所有图片文件
    for filename in os.listdir(file_pathname):
        print(filename)
        img = cv2.imread(file_pathname+'/'+filename)

        #插入图像处理代码
        
        cv2.imwrite('./img3/'+"/"+filename,img)

#注意*处如果包含家目录（home）不能写成~符号代替
#必须要写成"/home"的格式，否则会报错说找不到对应的目录
#读取的目录
read_path('./img2/')
#print(os.getcwd())

这里面图像处理代码根据自己需要进行编写，比如下面。

import cv2
import os
import numpy as np
from matplotlib import pyplot as plt


def gasuss_noise(image, mean=0, var=0.001):
    '''
        添加高斯噪声
        mean : 均值
        var : 方差
    '''

    image = np.array(image / 255, dtype=float)
    noise = np.random.normal(mean, var ** 0.5, image.shape)
    out = image + noise
    if out.min() < 0:
        low_clip = -1.
    else:
        low_clip = 0.
    out = np.clip(out, low_clip, 1.0)
    out = np.uint8(out * 255)

    return out


def read_path(file_pathname):
    #遍历该目录下的所有图片文件
    for filename in os.listdir(file_pathname):
        print(filename)
        img = cv2.imread(file_pathname+'/'+filename)


        #out2 = cv2.erode(img,None,iterations=3)
        hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)

        # 分别设置HSV颜色空间中，红色、黄色、蓝色、绿色的阈值
        lower_red = np.array([0, 43, 46])
        upper_red = np.array([10, 255, 255])

        lower_yellow = np.array([26, 43, 46])
        upper_yellow = np.array([34, 255, 255])

        lower_blue = np.array([100, 43, 46])
        upper_blue = np.array([124, 255, 255])

        lower_green = np.array([35, 43, 46])
        upper_green = np.array([77, 255, 255])

        # 使用inRange函数获取图像中目标颜色的索引
        mask_red = cv2.inRange(hsv, lower_red, upper_red)
        mask_blue = cv2.inRange(hsv, lower_blue, upper_blue)
        mask_green = cv2.inRange(hsv, lower_green, upper_green)
        mask_yellow = cv2.inRange(hsv, lower_yellow, upper_yellow)

        img_mask = np.copy(img)

        color_1 = [128, 9, 21]
        color_2 = [50, 14, 77]
        color_3 = [61, 154, 124]
        color_4 = [59, 170, 246]

        # 给目标像素赋值
        img_mask[mask_red != 0] = color_1
        img_mask[mask_blue != 0] = color_2
        img_mask[mask_green != 0] = color_3
        img_mask[mask_yellow != 0] = color_4

        #out2 = gasuss_noise(img, mean=0, var=0.01)
        ####change to gray
      #（下面第一行是将RGB转成单通道灰度图，第二步是将单通道灰度图转成3通道灰度图）

        #img=cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
        #image_np=cv2.cvtColor(img,cv2.COLOR_GRAY2BGR)
        #####save figure
        cv2.imwrite('./img3/'+"/"+filename,img_mask)

#注意*处如果包含家目录（home）不能写成~符号代替
#必须要写成"/home"的格式，否则会报错说找不到对应的目录
#读取的目录
read_path('./img2/')
#print(os.getcwd())