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keep_p = 1- dropout_p
a = np.sqrt(target_var / (keep_p *((1-keep_p) * np.power(alpha-target_mean,2) + target_var)))
b = target_mear - a * (keep_p * target_mean + (1 - keep_p) * alpha)
def alpha_dropout(x, alpha_p=-1.758, dropout_p=0.05):
mask = np.random.rand(*x.shape) > dropout_p
x[mask] = alpha_p
output = a*x + b
return output
def selu(x):
alpha = 1.6732632423543772848170429916717
lambdaa = 1.0507009873554804934193349852946
return lambdaa*np.where(x>=0.0, x, alpha*np.exp(x)-alpha)
import subprocess
from flask import Flask, render_template
app = Flask(__name__)
# keep runnign process global
proc = None
@app.route("/")
def hello():
<!doctype html>
<html lang="en">
<head>
<meta charset="utf-8">
<!-- Be Mobile Friendly -->
<meta name="viewport" content="width=device-width,height=device-height initial-scale=1">
<title>TalkingRaspi</title>
<meta name="description" content="Talkingraspi interface">
<meta name="author" content="Eren Golge">
import json
import smtplib
import uuid
import os
import glob
from os.path import basename
from email.mime.application import MIMEApplication
from email.mime.multipart import MIMEMultipart
from email.mime.text import MIMEText
###################################################################################
# LOGIC
###################################################################################
# check to see if the room is occupied
if text == "Occupied":
# save occupied frame
cv2.imwrite("/tmp/talkingraspi_{}.jpg".format(motionCounter), frame);
# check to see if enough time has passed between uploads
# thresholding difference frame for filling holes and noise reduction
# finding contours of moving regions
thresh = cv2.threshold(frameDelta, conf["delta_thresh"], 255,
cv2.THRESH_BINARY)[1]
thresh = cv2.dilate(thresh, None, iterations=2)
im2 ,cnts, _ = cv2.findContours(thresh.copy(), cv2.RETR_EXTERNAL,
cv2.CHAIN_APPROX_SIMPLE)
# loop over the contours
for c in cnts:
# capture frames from the camera
for f in camera.capture_continuous(rawCapture, format="bgr", use_video_port=True):
# grab the raw NumPy array representing the image and initialize
# the timestamp and occupied/unoccupied text
frame = f.array
timestamp = datetime.datetime.now()
text = "Unoccupied"
######################################################################
# COMPUTER VISION
# allow the camera to warmup, then initialize the average frame, last
# uploaded timestamp, and frame motion counter
print "[INFO] warming up..."
time.sleep(conf["camera_warmup_time"])
avg = None
lastUploaded = datetime.datetime.now()
motionCounter = 0
print('[INFO] talking raspi started !!')
from picamera.array import PiRGBArray
from picamera import PiCamera
from utils import send_email, TempImage
import argparse
import warnings
import datetime
import json
import time
import cv2