这篇文章主要介绍了Python怎么实现视频分解成图片及图片合成视频的相关知识,内容详细易懂,操作简单快捷,具有一定借鉴价值,相信大家阅读完这篇Python怎么实现视频分解成图片及图片合成视频文章都会有所收获,下面我们一起来看看吧。
import cv2 def video2frame(videos_path,frames_save_path,time_interval): ''' :param videos_path: 视频的存放路径 :param frames_save_path: 视频切分成帧之后图片的保存路径 :param time_interval: 保存间隔 :return: ''' vidcap = cv2.VideoCapture(videos_path) success, image = vidcap.read() count = 0 while success: success, image = vidcap.read() count += 1 if count % time_interval == 0: cv2.imencode('.jpg', image)[1].tofile(frames_save_path + "/frame%d.jpg" % count) # if count == 20: # break print(count) if __name__ == '__main__': videos_path = r'E:\py\python3.7\test\test98youhuashiping\shipingchaifen\1.mp4' frames_save_path = r'E:\py\python3.7\test\test98youhuashiping\shipingchaifen' time_interval = 2#隔一帧保存一次 video2frame(videos_path, frames_save_path, time_interval)
import cv2 import os import numpy as np from PIL import Image def frame2video(im_dir,video_dir,fps): im_list = os.listdir(im_dir) im_list.sort(key=lambda x: int(x.replace("frame","").split('.')[0])) #最好再看看图片顺序对不 img = Image.open(os.path.join(im_dir,im_list[0])) img_size = img.size #获得图片分辨率,im_dir文件夹下的图片分辨率需要一致 # fourcc = cv2.cv.CV_FOURCC('M','J','P','G') #opencv版本是2 fourcc = cv2.VideoWriter_fourcc(*'XVID') #opencv版本是3 videoWriter = cv2.VideoWriter(video_dir, fourcc, fps, img_size) # count = 1 for i in im_list: im_name = os.path.join(im_dir+i) frame = cv2.imdecode(np.fromfile(im_name, dtype=np.uint8), -1) videoWriter.write(frame) # count+=1 # if (count == 200): # print(im_name) # break videoWriter.release() print('finish') if __name__ == '__main__': im_dir = r'E:\py\python3.7\test\test98youhuashiping\shipingchaifen\pho/'#帧存放路径 video_dir = r'E:\py\python3.7\test\test98youhuashiping\shipingchaifen/test.mp4' #合成视频存放的路径 fps = 30 #帧率,每秒钟帧数越多,所显示的动作就会越流畅 frame2video(im_dir, video_dir, fps)
提示:路径中不要出现中文和特殊字符,且书写要规范!!
import cv2 import numpy as np import os os.chdir(r'E:\py\python3.7\test\test98youhuashiping\chaifen') ##读取视频,并逐帧分解成图片 cap = cv2.VideoCapture('1.mp4') #打开一个视频 isOpened = cap.isOpened() #判断是否打开 print(isOpened) #获取视频的相关信息,视频的每一帧图片的宽度都是一致的 fps = cap.get(cv2.CAP_PROP_FPS) #帧率,即每秒钟由多少张图片组成 width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH)) #获取宽度 height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT)) #获取高度 print(fps,width,height) #输出相关信息 i = 0 while (isOpened): #读取视频的前两秒的图像,共计2*int(fps)张 if i ==int(fps)*2 : break else: i = i+1 (flag,frame) = cap.read() #读取每一张 flag frame filename = 'image'+str(i)+'.jpg' #将读取的图片写入文件中, if flag == True: cv2.imwrite(filename,frame,[cv2.IMWRITE_JPEG_QUALITY,100]) #确定图片质量,100算是高的 print('end!') ##读取零散图片(上面分解的图片),并将其合成视频 img = cv2.imread('image1.jpg') imginfo = img.shape size = (imginfo[1],imginfo[0]) #与默认不同,opencv使用 height在前,width在后,所有需要自己重新排序 print(size) #创建写入对象,包括 新建视频名称,每秒钟多少帧图片(10张) ,size大小 #一般人眼最低分辨率为19帧/秒 videoWrite = cv2.VideoWriter('2.mp4',-1,10,size) for i in range(1,40): filename = 'image'+str(i)+'.jpg' img = cv2.imread(filename,1) #1 表示彩图,0表示灰度图 #直接写入图片对应的数据 videoWrite.write(img) videoWrite.release() #关闭写入对象 print('end')
import cv2 #导入opencv模块 import os import time def video_split(video_path,save_path): ''' 对视频文件切割成帧 ''' ''' @param video_path:视频路径 @param save_path:保存切分后帧的路径 ''' vc=cv2.VideoCapture(video_path) #一帧一帧的分割 需要几帧写几 c=0 if vc.isOpened(): rval,frame=vc.read() else: rval=False while rval: rval,frame=vc.read() # 每秒提取2帧图片 if c % 2 == 0: cv2.imwrite(save_path + "/" + str('%06d'%c)+'.jpg',frame) cv2.waitKey(1) c=c+1 DATA_DIR = r"E:\py\python3.7\test\test98youhuashiping\ceshi\mp4" #视频数据主目录 SAVE_DIR = r"E:\py\python3.7\test\test98youhuashiping\ceshi\pho2" #帧文件保存目录 start_time = time.time() for parents,dirs,filenames in os.walk(DATA_DIR): #if parents == DATA_DIR: # continue print("正在处理文件夹",parents) path = parents.replace("\\","//") f = parents.split("\\")[1] save_path = SAVE_DIR + "//" + f # 对每视频数据进行遍历 for file in filenames: file_name = file.split(".")[0] save_path_ = save_path + "/" + file_name if not os.path.isdir(save_path_): os.makedirs(save_path_) video_path = path + "/" + file video_split(video_path,save_path_) end_time = time.time() print("Cost time",start_time - end_time)
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