<?php

$day= new DateTime();

if (isset($_POST['month']) && ($_POST['month']!="")){
        $month=$_POST['month'];
        $f_month=str_replace("-","",$month);
} else {
        $month="";
}

echo "<div>";
echo "<H2>動画を再生するには、各画像左下の再生ボタンをクリックして下さい。</H2>";
echo "<LI>画像上へマウスオーバーするとファイル名を表示します。<BR>";
echo "ファイル名[カメラ名_検知フレーム数_総フレーム数_YYYYMMDD_HHmmSS.mp4]<BR>";
echo "<form method =\"POST\">\n";
echo "<BR><LABEL Date>月を変更するには年月欄の右端をクリックしてください。</LABEL>";
echo "<input type=\"month\" name=\"month\" value=$month>";
echo "<input type =\"submit\"  value =\"表示\">";
echo "</form></dev>";
//echo "$f_month<BR>\n";
$images = glob('meteor/COMP/*jpg');
$n=0;
foreach($images as $v) {
        if (strpos($v,$f_month)) {
                $tmp=explode(".",$v);
                $mp4=$tmp[0].".mp4";
                $mp4=str_replace("COMP","BEST2",$mp4);
                //echo "$mp4<BR>";
                $tmp=explode("/",$mp4);
                $title=$tmp[2];
                $msg="<video controls muted title=$title width='480' height='280' src=$mp4 poster=$v></video>";
                echo $msg;
                if ($n % 2 == 1){
                        echo "<BR>\n";
                }
                $n++;
        }
}
?>

# -*- coding: utf-8 -*-

import streamlit as st
import time
import datetime
import os
import glob
import cv2
import re
import numpy as np
from PIL import Image
from datetime import datetime, date, time

PATH='/home/metro//DATA/'

def comp_b2(A,B):
# 比較明合成処理
# https://nyanpyou.hatenablog.com/entry/2020/03/20/132937
#
    gray_img1 = cv2.cvtColor(A, cv2.COLOR_BGR2GRAY)
    gray_img2 = cv2.cvtColor(B, cv2.COLOR_BGR2GRAY)
#グレースケールの比較で作成したimg1用のマスク(img1の方が明るい画素を示す)
    mask_img1 = np.where(gray_img1>gray_img2, 255, 0).astype(np.uint8)
#img2用のマスク(0と255を入れ替え)(img2の方が明るい画素を示す)
    mask_img2 = np.where(mask_img1==255, 0, 255).astype(np.uint8)

#作成したマスクを使って元画像から抜き出し
    masked_img1 = cv2.bitwise_and(A, A, mask=mask_img1)
    masked_img2 = cv2.bitwise_and(B, B, mask=mask_img2)

    img3 = masked_img1 + masked_img2
    return img3

def disp(device):
        n=0
        cap = cv2.VideoCapture(device)
        W = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))
        H = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
        W2=int(W/2)
        H2=int(H/2)
        image_loc = st.empty()
        prev=None
        while cap.isOpened:
            ret, img = cap.read()
            if ret:
                if W==1920:
                    img=cv2.resize(img, dsize=(W2, H2))
                #time.sleep(0.01)
                if prev is None:
                    prev = img.copy()
                else:
                    E = comp_b2(prev,img)
                    prev = E
                img = Image.fromarray(cv2.cvtColor(img, cv2.COLOR_BGR2RGB))
                image_loc.image(img)
            else:
                break

        cap.release()
        image_loc = st.empty()
        img = Image.fromarray(cv2.cvtColor(prev, cv2.COLOR_BGR2RGB))
        image_loc.image(img)
    #st.button('Replay')

def main():
    st.header("流星観測データの表示")
    col1, col2, col3 = st.columns([1,1,3])
    with col1:
        date=st.date_input('DATE')
    path=PATH+date.strftime("%Y%m%d")
    selected=[]
    f_name=[]
    TL=[]
    if os.path.exists(path):
        files=glob.glob(path+'/*avi')
        # time filter : m[4] is time field.
        if files is not(None):
            for opt in files:
                m=re.split('[_.]',opt)
                TL.append(int(int(m[4])/10000))
            TL=list(set(TL))                        # sortして重複を削除
            # 処理対象の時間帯を選択するセレクトBOXの表示
            with col2:
                selected_item = st.selectbox('TIME',TL)
            selT = int(selected_item)
            for opt in files:
                m=re.split('[_.]',opt)
                if len(m)>=4:
                    t = int(int(m[4])/10000)
            #if not(t>60000 and t<180000):
                    if t==selT:
                        selected.append(opt)

            if selected is not(None):
                for name in selected:
                    f_name.append(name.rsplit('/',1)[1])
                with col3:
                    option = st.selectbox('FILE to DISPLAY',f_name)
            if option is not(None):
                disp(path+'/'+option)
    else:
        st.write('No data exists!')

if __name__ == '__main__':
    main()

# -*- coding: utf-8 -*-

import streamlit as st
import time
import datetime
import os
import glob
import cv2
from PIL import Image
from datetime import datetime, date, time

PATH='/home/mars/pWork/DATA/'

def disp(device):
    cap = cv2.VideoCapture(device)
    image_loc = st.empty()
    while cap.isOpened:
        ret, img = cap.read()
        if ret:
            img = Image.fromarray(cv2.cvtColor(img, cv2.COLOR_BGR2RGB))
            image_loc.image(img)
        else:
            break

    cap.release()
    st.button('Replay')

def main():
    st.header("流星観測データの表示")
    date=st.date_input('Select date')
    path=PATH+date.strftime("%Y%m%d")
    #st.write(path)
    if os.path.exists(path):
        files=glob.glob(path+'/*avi')
        option = st.selectbox('Select file:',files)
        disp(option)
    else:
        st.write('No data exists!')

if __name__ == '__main__':
    main()

import cv2
import numpy as np
import time
import datetime
import os
import sys
GPU=True
THREAD=True
if len(sys.argv)>1:
    if sys.argv[1]=='A':
        cPATH='rtsp://5173:6703@192.168.68.74/live'
    else:
        cPATH='rtsp://admin:@192.168.68.128:554/1/h264major'
else:
        cPATH='rtsp://5173:6703@192.168.68.74/live'
PATH="/home/mars/pWork/DATA"
#

class ThreadingVideoCapture:
    def __init__(self, src, max_queue_size=256):
        self.video = cv2.VideoCapture(src)
        self.q = queue.Queue(maxsize=max_queue_size)
        self.stopped = False

    def start(self):
        thread = threading.Thread(target=self.update, daemon=True)
        thread.start()
        return self

    def update(self):
        while True:
            if self.stopped:
                return
            if not self.q.full():
                ok, frame = self.video.read()
                self.q.put((ok, frame))
                if not ok:
                    self.stop()
                    return

    def read(self):
        return self.q.get()

    def stop(self):
        self.stopped = True

    def release(self):
        self.stopped = True
        self.video.release()

    def isOpened(self):
        return self.video.isOpened()

    def get(self, i):
        return self.video.get(i)

def key(k):
    global th, tc,track,reverse
    if k == ord('2'):
        th = th - 1
    elif k == ord('3'):
        th = th + 1
    elif k == ord('4'):
        tc = tc -5
    elif k == ord('5'):
        tc = tc +5
    elif k == ord('t'):
        track = not track
    elif k == ord('r'):
        reverse = not reverse

fontFace =cv2.FONT_HERSHEY_SIMPLEX
track, reverse = False,False
avg=None
writer = None
th = 30
tc = 30
x,y=0,0
detect_counts = 0
red,blue,green = (0,0,255),(255,0,0),(0,255,0)
time_start = time.time()
frame=0
log=PATH+'/metro.log'
if cPATH=='rtsp://5173:6703@192.168.68.74/live':
    TITLE="ATOM"
    HEAD ='ATOM'
else:
    TITLE="ONVIF"
    HEAD='ONVIF'

if THREAD:
    import threading
    import queue
    TITLE=TITLE+"-T"
    capture = ThreadingVideoCapture(cPATH)
    capture.start()
    if not capture.isOpened():
        raise RuntimeError
else:
    capture=cv2.VideoCapture(cPATH)

if GPU:
    TITLE=TITLE+"-G"
    img_gpu_src = cv2.cuda_GpuMat() # Allocate device memory only once, as memory allocation seems to take time...
    img_gpu_dst = cv2.cuda_GpuMat()
    img_gpu_gray= cv2.cuda_GpuMat()

W = capture.get(cv2.CAP_PROP_FRAME_WIDTH)
H = capture.get(cv2.CAP_PROP_FRAME_HEIGHT)
W2=int(W/2)
H2=int(H/2)
fourcc = cv2.VideoWriter_fourcc(*"XVID")
print('Camera:',cPATH)
print('Size:',W,H)
while(True):
    ret, img = capture.read()
    if ret:
        org = img.copy()
        if GPU:
            img_gpu_src.upload(img)
            img_gpu_dst = cv2.cuda.resize(img_gpu_src, dsize=(W2, H2))
            img_gpu_dst = cv2.cuda_GpuMat(img_gpu_dst,[0,int(H2*0.85)],[0,W2])
            img_gpu_gray=cv2.cuda.cvtColor(img_gpu_dst,cv2.COLOR_BGR2GRAY)
            org_img=img_gpu_dst.download()
            gray = img_gpu_gray.download()
        else:
            org_img = cv2.resize(img, dsize=(W2, H2))
            org_img=img[0:int(H2*0.85),0:W2]
            gray = cv2.cvtColor(org_img, cv2.COLOR_BGR2GRAY)
        if reverse:
            gray=cv2.bitwise_not(gray)
            avg=cv2.bitwise_not(avg)
        if avg is None:
            avg = gray.copy().astype("float")
            continue

        #wtiter,fname = moving(img,avg)
        cv2.accumulateWeighted(gray, avg, 0.5)
        frameDelta = cv2.absdiff(gray, cv2.convertScaleAbs(avg))
        thresh = cv2.threshold(frameDelta, th, 255, cv2.THRESH_BINARY)[1]

        contours,hierarchy = cv2.findContours(thresh, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
        detect=False
        for i in range(0,len(contours)):
            if len(contours[i]) > 0:
                 if cv2.contourArea(contours[i]) > tc:
                    detect=True
                    time_start = time.time()
                    if writer is None and track:
                        detect_counts = 0
                        now=datetime.datetime.today()
                        date=now.strftime("%Y%m%d")
                        cDIR=PATH+'/'+date
                        if not(os.path.exists(cDIR)):
                            os.mkdir(cDIR)
                        fname=cDIR+'/'+ HEAD + now .strftime("%Y%m%d_%H%M%S")+".avi"
                        writer = cv2.VideoWriter(fname, fourcc, 15, (int(W), int(H)))
                    rect = contours[i]
                    x, y, w, h = cv2.boundingRect(rect)
                    cv2.rectangle(org_img, (x-w, y-h), (x + w*2, y + h*2), red, 3)
        if detect:
            detect_counts=detect_counts + 1
        if time.time() -  time_start  > 5:
            if writer is not None:
                writer.release()
                new_name=fname.replace(HEAD,HEAD+'_' + f'{detect_counts:04}'+'_')
                os.rename(fname,new_name)
                frame=0
                writer = None
        now=datetime.datetime.today()
        text=now.strftime("%Y%m%d %H%M%S")+' No:'+str(frame)+ ' '+" TH:"+str(th)+" SZ:"+str(tc)
        org_img = cv2.putText(org_img, text, (30,50), fontFace,1,color=green)
        org = cv2.putText(org, text, (30,50), fontFace,1,color=green)
        text1="REC:"+str(track) + "  reverse:" + str(reverse)
        if writer is not None:
            frame=frame+1
            text1=fname+' '+text1
        org_img = cv2.putText(org_img, text1, (30,80), fontFace,1,color=green)
        #cv2.imshow('thresh-level',thresh)

        cv2.imshow(TITLE,org_img)

        if writer is not None:
            writer.write(org)
    else:
        now=datetime.datetime.today()
        date=now.strftime("%Y%m%d_%H%M%S")
        print('reconnect:',date)
        capture.release()
        avg=None
        if THREAD:
            capture = ThreadingVideoCapture(cPATH)
            capture.start()
        else:
            capture = cv2.VideoCapture(cPATH)
    k=cv2.waitKey(1) & 0xFF
    key(k)
    if k== ord('q'):
        break

capture.release()
if writer is not None:
    writer.release()
    new_name=fname.replace(HEAD,HEAD+'_' + f'{detect_counts:04}'+'_')
    os.rename(fname,new_name)
cv2.destroyAllWindows()