python 视频处理，提取视频相关帧，读取Excel

一共这几个模块：

class videoReader 读取视频

class videoFramesExtractor(videoReader):继承了读取视频，主要是用来限制读取视频中的哪些帧，并保存。

read_excel_single(excel_path,event_instance): 处理Excel中的数组，找到事件的帧数范围：

Excel内容是这样的，需要的只是第二列的帧范围，另外第二列中的这些值还有重复的所以需要去除重复：

每一个范围，例如:23450:23461之内的帧要存放在一个文件夹里。

</pre><pre name="code" class="python"># -*- coding: cp936 -*-import cv2.cv as cvimport osimport cv2import numpyimport Imageimport xlrdclass videoReader:    frame_count=0    def __init__(self,videoPath):        self.videoPath=videoPath    def video_init(self):        self.capture = cv.CaptureFromFile(self.videoPath)        self.win_name = "test"        cv.NamedWindow(self.win_name, cv.CV_WINDOW_AUTOSIZE)            def read(self):        self.video_init()        while 1:            self.frame_count+=1            image = cv.QueryFrame(self.capture )                       cv.ShowImage(self.win_name, image)            print self.frame_count            c = cv.WaitKey(10)            if c == 27:                break                    cv.DestroyWindow(self.win_name)class videoFramesExtractor(videoReader):    save_path='d:/'    def __init__(self,videoPath,frameSpan,image_prefix):#image_prefix=event_name        videoReader.__init__(self,videoPath)        self.frameSpan=frameSpan        self.image_prefix=image_prefix            def read(self):        capture = cv2.VideoCapture(self.videoPath)        win_name = "test"        cv.NamedWindow(win_name, cv.CV_WINDOW_AUTOSIZE)        success,frame = capture.read()                init_row=0        while success:                        self.frame_count+=1            success,frame = capture.read()            #cv2.imshow(win_name,frame) #显示照片浪费时间            time_duration=self.frameSpan[init_row][1]-self.frameSpan[init_row][0]+1            if self.frame_count>=self.frameSpan[init_row][0] and \              self.frame_count<=self.frameSpan[init_row][1] :                                                                       self.image_save(frame,init_row,time_duration)                                                    if self.frame_count==self.frameSpan[init_row][1]:                    init_row+=1                if init_row==len(self.frameSpan):                    cv.DestroyWindow(win_name)                    return 0                            c = cv.WaitKey(10)            if c == 27:                break                    cv.DestroyWindow(win_name)    def image_save(self,frame,init_row,time_duration):        save_path=self.make_folder(init_row,time_duration)            #frame=Image.fromarray(frame)        #frame.resize((300,300))        #frame.save('%s//%s.jpg' % (save_path,self.frame_count))        frame=cv2.resize(frame,(300,300))#        cv2.imwrite( '%s//%s.jpg' % (save_path,self.frame_count), frame)            def make_folder(self,init_row,time_duration):        temp= self.image_prefix+'_'+str(init_row)+'_'+str(time_duration)#事件名称_事件顺序_        new_path = os.path.join(self.save_path,temp)        if not os.path.isdir(new_path):            os.makedirs(new_path)        return new_path        def read_excel_single(excel_path,event_instance):                data=[]        data=xlrd.open_workbook(excel_path)        #read the first sheets        table = data.sheets()[0]        #read the num fo cols        nrows = table.nrows        rowmsg=[]#用来存储帧的范围，及事件的类别，描述。        for i in xrange(nrows):            start_frame,end_frame=table.row_values(i)[1].split(':')            rowmsg.append([int(start_frame),int(end_frame),table.row_values(i)[3]])        rowmsg.sort(lambda x,y:cmp(x[0],y[0]))#按照数字大小排序~                event_id=[]        event_id=event_instance        #print event_id                    event=[]        for item in xrange(len(rowmsg)):            if rowmsg[item][2]==event_id:#                event.append(rowmsg[item])        if event==[]:            print ("there is no %s occurs" % event_instance)            return 0        #去除重复                              cur_pos=1        new_rowmsg=[]        pre_s=event[0][0]        pre_e=event[0][1]        cur_s=event[cur_pos][0]        cur_e=event[cur_pos][1]        while cur_pos<len(event)-1:             while not (cur_s>pre_e):                if cur_s>pre_s:                    cur_s=pre_s                if cur_e<pre_e:                    cur_e=pre_e                still_pos=[cur_s,cur_e,event_id]                cur_pos+=1                if cur_pos==len(event)-1:                    break                                            pre_s=cur_s                pre_e=cur_e                cur_s=event[cur_pos][0]                cur_e=event[cur_pos][1]            new_rowmsg.append(still_pos)            if cur_pos==len(event)-1:                break                cur_pos+=1            pre_s=cur_s            pre_e=cur_e            cur_s=event[cur_pos][0]            cur_e=event[cur_pos][1]                return new_rowmsg                 excel_source='E:/08ann/dev_20071101/LGW_20071101_E1_CAM1.mpeg.xlsx'event_instance='CellToEar'row_msg=read_excel_single(excel_source,event_instance)new_row=[ item[0:2] for item in row_msg ] filename = "G:/TrecvidData/08/DEV/LGW_20071101_E1_CAM1.mpg"            videoread=videoFramesExtractor(filename,new_row,'CellToEar')videoread.read()

有几点发现：

cv2.的函数输出的数据类型基本都是numpy，而cv.不行。所以尽量在python中使用cv2.的函数。

通过numpy转换后的图片会在颜色上有些失真，不过影响不大，如果是灰度图的话则完全没有影响。