video split opencv in python

video.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import cv2\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import os,glob\n",
    "import pandas as pd\n",
    "from pandas import DataFrame\n",
    "from tqdm import tqdm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['100m over head.mp4', '100m under.mp4', 'headon.mp4']"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "video_list=glob.glob('*.mp4')\n",
    "video_list.sort()\n",
    "video_list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['100m over head.txt', '100m under.txt', 'headon.txt']"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "meta_data=list(map(lambda x:x.strip().replace('mp4','txt'),video_list))\n",
    "meta_data.sort()\n",
    "meta_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[0.3, 0.5, 0.8, 1, 2]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "size=[2,1,0.8,0.5,0.3]\n",
    "size.sort()\n",
    "size"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "videos_save_path='/video/subtitle/videos'\n",
    "images_save_path='/video/subtitle/images'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "\n",
      "\n",
      "0it [00:00, ?it/s]\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
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      "\n",
      "\n",
      "  0%|          | 0/5 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "/home/jaehun/video/subtitle/videos/0.3/100m over head.mp4\n"
     ]
    },
    {
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     "text": [
      "\n",
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      "\n",
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      "\n",
      " 20%|██        | 1/5 [00:15<01:02, 15.55s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "/home/jaehun/video/subtitle/videos/0.5/100m over head.mp4\n"
     ]
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      "\n",
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      " 40%|████      | 2/5 [00:37<00:52, 17.55s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "/home/jaehun/video/subtitle/videos/0.8/100m over head.mp4\n"
     ]
    },
    {
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     "text": [
      "\n",
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      " 60%|██████    | 3/5 [01:12<00:45, 22.57s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "/home/jaehun/video/subtitle/videos/1/100m over head.mp4\n"
     ]
    },
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     "text": [
      "\n",
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      "\n",
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      " 80%|████████  | 4/5 [01:52<00:27, 27.91s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "/home/jaehun/video/subtitle/videos/2/100m over head.mp4\n"
     ]
    }
   ],
   "source": [
    "\n",
    "for video,txt in tqdm(zip(video_list,meta_data)):\n",
    "    for j in tqdm(size):\n",
    "        # txt 파일 읽기\n",
    "        df=pd.read_csv(txt,names=['times','r'],sep=\" \", header=None)\n",
    "        # video 파일 읽기\n",
    "        cap = cv2.VideoCapture(video)\n",
    "        # 저장할 video의 크기를 정해준다.\n",
    "        width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH)*j)\n",
    "        height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT)*j)\n",
    "        # 아래는 동영상과 txt데이터를 보간하기 위한 로직\n",
    "        n_frames = int(cap.get(cv2.CAP_PROP_FRAME_COUNT))\n",
    "        while df.index.stop!=n_frames:\n",
    "            df=df.append(pd.Series(), ignore_index=True)\n",
    "        df['times']=df.index+1\n",
    "        df['r'].interpolate(method ='linear',inplace=True) \n",
    "        # 기존의 video에서 fps 정보를 가져온다\n",
    "        fps = cap.get(cv2.CAP_PROP_FPS)\n",
    "        # 코덱을 정한다.\n",
    "        fourcc = cv2.VideoWriter_fourcc(*'XVID')\n",
    "        # 저장할 이름을 정한다. \n",
    "        outname='/home/jaehun'+videos_save_path+'/'+str(j)+'/'+video\n",
    "        os.makedirs('/home/jaehun'+videos_save_path+'/'+str(j),exist_ok=True)\n",
    "        os.makedirs('/home/jaehun'+images_save_path+'/'+video.split('.')[0]+'/'+str(j),exist_ok=True)\n",
    "        print(outname)\n",
    "        out = cv2.VideoWriter(outname, fourcc, fps, (width,height))\n",
    "        count=0\n",
    "        time=''\n",
    "        r=''\n",
    "        while(cap.isOpened()):\n",
    "            ret,frame = cap.read()\n",
    "            if ret:\n",
    "                time=str(df['times'][count])\n",
    "                r=str(df['r'][count])\n",
    "                # 크기를 조정한다.\n",
    "                frame=cv2.resize(frame,tuple(map (lambda x:(int)(x*j),frame.shape[:2][::-1])),interpolation=cv2.INTER_CUBIC )\n",
    "                #str1 시간 정보를 삽입한다.\n",
    "                cv2.putText(frame,\"time: \"+ time, ((int)(250*j), height-(int)(250*j)), cv2.FONT_HERSHEY_PLAIN, (int)(5*j), (0, 0 ,255))\n",
    "                #str2 거리 정보를 삽입한다.\n",
    "                cv2.putText(frame, \"r: \"+ r, (width-(int)(450*j), height-(int)(250*j)), cv2.FONT_HERSHEY_PLAIN, (int)(5*j), (0, 0, 255))\n",
    "                out.write(frame)\n",
    "                cv2.imwrite('/home/jaehun'+images_save_path+'/'+video.split('.')[0]+'/'+str(j)+\"/%d.png\" % count, frame)    # save frame as JPEG file      \n",
    "            else:\n",
    "                break\n",
    "            count+=1\n",
    "        cap.release()\n",
    "        out.release()\n",
    "        cv2.destroyAllWindows()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "videos_save_path='/video/split/videos'\n",
    "images_save_path='/video/split/images'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "for video,txt in tqdm(zip(video_list,meta_data)):\n",
    "    for j in tqdm(size):\n",
    "        # txt 파일 읽기\n",
    "        # video 파일 읽기\n",
    "        cap = cv2.VideoCapture(video)\n",
    "        # 저장할 video의 크기를 정해준다.\n",
    "        width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH)*j)\n",
    "        height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT)*j)\n",
    "        \n",
    "        # 기존의 video에서 fps 정보를 가져온다\n",
    "        fps = cap.get(cv2.CAP_PROP_FPS)\n",
    "        # 코덱을 정한다.\n",
    "        fourcc = cv2.VideoWriter_fourcc(*'XVID')\n",
    "        # 저장할 이름을 정한다. \n",
    "        outname='/home/jaehun'+videos_save_path+'/'+str(j)+'/'+video\n",
    "        os.makedirs('/home/jaehun'+videos_save_path+'/'+str(j),exist_ok=True)\n",
    "        os.makedirs('/home/jaehun'+images_save_path+'/'+video.split('.')[0]+'/'+str(j),exist_ok=True)\n",
    "        print(outname)\n",
    "        out = cv2.VideoWriter(outname, fourcc, fps, (width,height))\n",
    "        count=0\n",
    "        while(cap.isOpened()):\n",
    "            ret,frame = cap.read()\n",
    "            if ret:\n",
    "\n",
    "                # 크기를 조정한다.\n",
    "                frame=cv2.resize(frame,tuple(map (lambda x:(int)(x*j),frame.shape[:2][::-1])),interpolation=cv2.INTER_CUBIC )\n",
    "                out.write(frame)\n",
    "                cv2.imwrite('/home/jaehun'+images_save_path+'/'+video.split('.')[0]+'/'+str(j)+\"/%d.png\" % count, frame)    # save frame as JPEG file      \n",
    "            else:\n",
    "                break\n",
    "            count+=1\n",
    "        cap.release()\n",
    "        out.release()\n",
    "        cv2.destroyAllWindows()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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