SDD-Webcam-CustomVision/WebcamCounter.py at master · socialdistancingdashboard/SDD-Webcam-CustomVision · GitHub

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#!/usr/bin/env python
# coding: utf-8

# Einkommentieren, falls nur CPU genutzt werden soll

#import os
#os.environ["CUDA_VISIBLE_DEVICES"] = "-1"

import predict
import numpy as np
import cv2
import urllib
from datetime import datetime
import boto3
import json
import ssl
import os
import gc
import socket
from PIL import Image
import hashlib

ssl._create_default_https_context = ssl._create_unverified_context


class PeopleCounter:
    def get_image(self, url, id):
        req = urllib.request.Request(
           url,
           data=None,
           headers={
           'User-Agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_9_3) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/35.0.1916.47 Safari/537.36'
           }
        )
        resp = urllib.request.urlopen(req, timeout=10)
        #resp = urllib.request.urlopen(url, timeout=10)
        self.image = np.asarray(bytearray(resp.read()), dtype="uint8")
        #if self.img is not None:
        self.image = cv2.imdecode(self.image, -1)
        filename = "/tmp/"+ str(id) + ".jpg"
        status = cv2.imwrite(filename, self.image)
        print("Image written to file-system : ",status)
        directory = r'/tmp'
        h, w, c = self.image.shape
        print('width:  ', w)
        print('height: ', h)
        print('channel:', c)
        md5_hash = hashlib.md5()
        with open(os.path.join(directory, filename), "rb") as a_file:
            content = a_file.read()
            md5_hash.update(content)
        hash = md5_hash.hexdigest()
        print("image hash : ",hash)
        pred = predict.main(os.path.join(directory, filename))
        print(pred)
        os.remove(os.path.join(directory, filename))
        peoplecount = len([x for x in pred if x["probability"]>0.5])
        print("count of people : ",peoplecount)
        gc.collect()
        return peoplecount, pred, w, h, hash

    def get_video(self, url, id):
        cap = cv2.VideoCapture(url)
        ret, frame_bgr = cap.read()
        cap.release()
        #unkommentieren falls rgb gewünscht
        #frame_rgb = cv2.cvtColor(frame_bgr, cv2.COLOR_BGR2RGB)
        #image = frame_rgb.flatten()
        # Zum überprüfen...
        #cv2.imwrite("C://test.jpg",frame_bgr)
        #self.image = np.asarray(bytearray(resp.read()), dtype="uint8")
        #if self.img is not None:
        #self.image = cv2.imdecode(self.image, -1)
        h, w, c = frame_bgr
        print('width:  ', w)
        print('height: ', h)
        print('channel:', c)
        filename = "/tmp/"+ str(id) + ".jpg"
        status = cv2.imwrite(filename, frame_bgr)
        print("Image written to file-system : ",status)
        directory = r'/tmp'
        md5_hash = hashlib.md5()
        with open(os.path.join(directory, filename), "rb") as a_file:
            content = a_file.read()
            md5_hash.update(content)
        hash = md5_hash.hexdigest()
        pred = predict.main(os.path.join(directory, filename))
        print(pred)
        os.remove(os.path.join(directory, filename))
        peoplecount = len([x for x in pred if x["probability"]>0.5])
        print("count of people : ",peoplecount)
        gc.collect()
        return peoplecount, pred,  w, h, hash


if __name__ == '__main__':
    with open("webcam_list_2.json","r") as f:
        webcams = json.load(f)
    pc = PeopleCounter()
    for cam in webcams:
        print(cam)
        if cam['Video'] == True:
           print('Camera is stream')
           try:
               cam['Personenzahl'], cam['pred'], cam['width'], cam['high'], cam['hash'] = pc.get_video(cam['URL'], cam['ID'])
               #cam['Personenzahl'] =  pc.get_video(cam['URL'], cam['ID'])
               cam['Stand'] = datetime.now().strftime("%Y-%m-%d %H:%M")
               print(cam["Name"]+" :"+str(cam["Personenzahl"]))
           except:
               pass
               #print("Unexpected error:", sys.exc_info()[0])
        else:
           try:
               print('Camera is Image')
               cam['Personenzahl'], cam['pred'], cam['width'], cam['high'], cam['hash'] = pc.get_image(cam['URL'], cam['ID'])
               #cam['Personenzahl'], cam['pred'] = pc.get_image(cam['URL'], cam['ID'])
               #cam['Personenzahl'] =  pc.get_image(cam['URL'], cam['ID'])
               cam['Stand'] = datetime.now().strftime("%Y-%m-%d %H:%M")
               print(cam["Name"]+" :"+str(cam["Personenzahl"]))
           except urllib.error.HTTPError as e:
               print(cam["Name"]+" :"+'The server couldn\'t fulfill the request.')
               print('Error code: ', e.code)
           except urllib.error.URLError as e:
               print(cam["Name"]+" :"+'We failed to reach a server.')
               print('Reason: ', e.reason)
           except:
               pass
               #print("Unexpected error:", sys.exc_info()[0])

    client_s3 = boto3.client("s3" )

    response = client_s3.put_object(
        Bucket="sdd-s3-bucket",
        Body=json.dumps(webcams),
       Key=f"webcamdaten/{datetime.now().strftime('%Y/%m/%d/%H')}webcamdaten-customvision.json"
     )