Video is freezed while video streaming - javascript

I find the following code for streaming video over a socket in python2.7. When I run it, the video will be freeze at the beginning in the server-side (It shows the video in a web browser). I debugged the code and understood that in the streamer.py, the third while loop condition creates an infinite loop because of the condition while len(data) < msg_size: is always satisfied. In other words, len(data) is always less than msg_size.So, the streamer.py does not return the image to the server.py. Could anyone help me to solve this issue?
The server.py is:
from flask import Flask, render_template, Response
from streamer import Streamer
app = Flask(__name__)
def gen():
streamer = Streamer('localhost', 8089)
streamer.start()
while True:
if streamer.client_connected():
yield (b'--frame\r\n'b'Content-Type: image/jpeg\r\n\r\n' +
streamer.get_jpeg() + b'\r\n\r\n')
#app.route('/')
def index():
return render_template('index.html')
#app.route('/video_feed')
def video_feed():
return Response(gen(), mimetype='multipart/x-mixed-replace;
boundary=frame')
if __name__ == '__main__':
app.run(host='localhost', threaded=True)
The streamer.py is:
import threading
import socket
import struct
import StringIO
import json
import numpy
class Streamer (threading.Thread):
def __init__(self, hostname, port):
threading.Thread.__init__(self)
self.hostname = hostname
self.port = port
self.connected = False
self.jpeg = None
def run(self):
self.isRunning = True
s = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
print 'Socket created'
s.bind((self.hostname, self.port))
print 'Socket bind complete'
data = ""
payload_size = struct.calcsize("L")
s.listen(10)
print 'Socket now listening'
while self.isRunning:
conn, addr = s.accept()
print 'while 1...'
while True:
data = conn.recv(4096)
print 'while 2...'
if data:
packed_msg_size = data[:payload_size]
data = data[payload_size:]
msg_size = struct.unpack("L", packed_msg_size)[0]
while len(data) < msg_size:# the infinite loop is here(my problem)!
data += conn.recv(4096)
print ("lenght of data is " , len(data) )
print ("message size is " , msg_size )
frame_data = data[:msg_size]
#frame_data = data[:len(data)]
memfile = StringIO.StringIO()
memfile.write(json.loads(frame_data).encode('latin-1'))
memfile.seek(0)
frame = numpy.load(memfile)
ret, jpeg = cv2.imencode('.jpg', frame)
self.jpeg = jpeg
self.connected = True
print 'recieving...'
else:
conn.close()
self.connected = False
print 'connected=false...'
break
self.connected = False
def stop(self):
self.isRunning = False
def client_connected(self):
return self.connected
def get_jpeg(self):
return self.jpeg.tobytes()
Client.py is:
import socket
import sys
import pickle
import struct
import StringIO
import json
import time
cap=cv2.VideoCapture(0)
clientsocket=socket.socket(socket.AF_INET,socket.SOCK_STREAM)
clientsocket.connect(('localhost',8089))
while(cap.isOpened()):
ret,frame=cap.read()
memfile = StringIO.StringIO()
np.save(memfile, fravidme)
memfile.seek(0)
data = json.dumps(memfile.read().decode('latin-1'))
clientsocket.sendall(struct.pack("L", len(data))+data)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
cap.release()
I want to show the video captured by my laptop's camera on a client machine in the same network. I expect video stream but in the browser, I just watch an image and it does not update continuously.


As I analyzed this code I noticed that the default implementation for sending OpenCV frames over the network was not working. I decided to replace it with ZeroMQ implementation I have used before. You can check out the linked question for a deeper explanation of how the streaming works. I have neatly packaged it into classes, with unit tests and documentation as SmoothStream check it out too.
Coming back to the question, here is the working code.
client.py
import base64
import cv2
import zmq
context = zmq.Context()
footage_socket = context.socket(zmq.PUB)
footage_socket.connect('tcp://localhost:5555')
camera = cv2.VideoCapture(0) # init the camera
while True:
try:
grabbed, frame = camera.read() # grab the current frame
frame = cv2.resize(frame, (640, 480)) # resize the frame
encoded, buffer = cv2.imencode('.jpg', frame)
jpg_as_text = base64.b64encode(buffer)
footage_socket.send(jpg_as_text)
except KeyboardInterrupt:
camera.release()
cv2.destroyAllWindows()
break
server.py
from flask import Flask, render_template, Response
from streamer import Streamer
app = Flask(__name__)
def gen():
streamer = Streamer('*', 5555)
streamer.start()
while True:
if streamer.client_connected():
yield (b'--frame\r\n'b'Content-Type: image/jpeg\r\n\r\n' + streamer.get_jpeg() + b'\r\n\r\n')
#app.route('/')
def index():
return render_template('index.html')
#app.route('/video_feed')
def video_feed():
return Response(gen(), mimetype='multipart/x-mixed-replace; boundary=frame')
if __name__ == '__main__':
app.run(host='localhost', threaded=True)
streamer.py
import base64
import threading
import cv2
import numpy as np
import zmq
class Streamer(threading.Thread):
def __init__(self, hostname, port):
threading.Thread.__init__(self)
self.hostname = hostname
self.port = port
self.connected = False
self.jpeg = None
def run(self):
self.isRunning = True
context = zmq.Context()
footage_socket = context.socket(zmq.SUB)
footage_socket.bind('tcp://{}:{}'.format(self.hostname, self.port))
footage_socket.setsockopt_string(zmq.SUBSCRIBE, np.unicode(''))
while self.isRunning:
frame = footage_socket.recv_string()
img = base64.b64decode(frame)
npimg = np.fromstring(img, dtype=np.uint8)
source = cv2.imdecode(npimg, 1)
ret, jpeg = cv2.imencode('.jpg', source)
self.jpeg = jpeg
self.connected = True
self.connected = False
def stop(self):
self.isRunning = False
def client_connected(self):
return self.connected
def get_jpeg(self):
return self.jpeg.tobytes()
I understand that copy-pasting entire .py files are probably not the best way to post an answer here, but this is a complex question with a lot of moving parts and I honestly could not think of a better way to help the OP.

Related

Websocket closes immediately

https://github.com/tiasimoneriley/pulse
So i am trying to make this code run to get the pulses, however the connection to Websocket is immediatly closed and I don't understand why.
It closing right away is not letting the frames of the video get computed to get the pulses.
Also, I am new to this whole thing so if anyone can figure it out please tell me whats wrong.
Thank you.
This is what my console shows
websocket open! websocket.js:5
closed websocket.js:22
T1 camera.js:70
T2 camera.js:76
T3 camera.js:82
T4 camera.js:84
T5 camera.js:86
begin startCapture() camera.js:397
T6 camera.js:88
WebSocket is already in CLOSING or CLOSED state. websocket.js:18
WebSocket is already in CLOSING or CLOSED state. websocket.js:18
Here is the
app.py
import json
import os
from flask import Flask, render_template
from flask_sockets import Sockets
import model
app = Flask(__name__)
sockets = Sockets(app)
#app.route("/")
def index():
return render_template("splash.html")
#app.route("/begin")
def get_heartrate():
return render_template("index.html")
#sockets.route('/echo')
def echo_socket(ws):
while True:
message = json.loads(ws.receive())
signals = model.parse_RGB(message)
ws.send(signals)
if __name__ == "__main__":
from gevent import pywsgi
from geventwebsocket.handler import WebSocketHandler
port = int(os.environ.get('PORT', 5000))
print("Hosting on port {}".format(port))
server = pywsgi.WSGIServer(('', port), app, handler_class=WebSocketHandler)
server.serve_forever()
and this is the websocket.js
var dataSocket = new WebSocket(location.protocol.replace("http", "ws") + location.host + "/echo");
dataSocket.onopen = function(){
console.log("websocket open!");
console.log(dataSocket);
}
dataSocket.onmessage = function(e){
var data = JSON.parse(e.data);
if (data.id === "ICA"){
camera.cardiac(data.array, data.bufferWindow);
}
}
function sendData(data){
dataSocket.send(data);
}
dataSocket.onclose = function(){
console.log('closed');
}

How do I add a js map to Pyqt5?

I want to add the map provided by Marinetraffic to pyqt5. When I add the HTML codes provided by MarineTraffic to my own program, it doesn't work.
The map I want to add:
MarineTraffic Map JS
from PyQt5 import QtCore, QtGui, QtWidgets, QtWebEngineWidgets, QtWebChannel
class Backend(QtCore.QObject):
valueChanged = QtCore.pyqtSignal(str)
def __init__(self, parent=None):
super().__init__(parent)
self._value = ""
#QtCore.pyqtProperty(str)
def value(self):
return self._value
#value.setter
def value(self, v):
self._value = v
self.valueChanged.emit(v)
class Widget(QtWidgets.QWidget):
def __init__(self, parent=None):
super().__init__(parent)
self.webEngineView = QtWebEngineWidgets.QWebEngineView()
self.label = QtWidgets.QLabel(alignment=QtCore.Qt.AlignCenter)
lay = QtWidgets.QVBoxLayout(self)
lay.addWidget(self.webEngineView, stretch=1)
lay.addWidget(self.label, stretch=1)
backend = Backend(self)
backend.valueChanged.connect(self.label.setText)
backend.valueChanged.connect(self.foo_function)
self.channel = QtWebChannel.QWebChannel()
self.channel.registerObject("backend", backend)
self.webEngineView.page().setWebChannel(self.channel)
path = "index.html"
self.webEngineView.setUrl(QtCore.QUrl.fromLocalFile(path))
#QtCore.pyqtSlot(str)
def foo_function(self, value):
print(value)
if __name__ == "__main__":
import sys
app = QtWidgets.QApplication(sys.argv)
w = Widget()
w.show()
sys.exit(app.exec_())
When I run it, I get a connection failed error.
As a result of my searches, I get the same error in all the methods I tried, where am I doing wrong, can you help?

Read the documentation for QtCore.QUrl.fromLocalFile :
QtCore.QUrl.fromLocalFile
"A file URL with a relative path only makes sense if there is a base URL to resolve it against."
So we add the base path:
import os
...
path = os.getcwd() + "\\index.html"
self.webEngineView.setUrl(QtCore.QUrl.fromLocalFile(path))
Added path compatibility between os (edited)
from pathlib import Path
...
base_path = Path(Path.cwd())
full_path = base_path.joinpath('index.html')
self.webEngineView.setUrl(QtCore.QUrl.fromLocalFile(str(full_path)))

Node js Child Process Spawn runs whole python code every time I call

I have this code which connects Nodejs to Python script. The script contains ML models with Tensor flow backend and so on.., it basically gives a string output. I send an image URL from node js via.child process spawn to python and it gives back its recognised expression as a string. Basically I am doing facial recognition, coded in python but calling through Node js and send the string to response as JSON data(Rest API).
The problem I am facing is whenever I call spawn, it runs whole code of python and its taking so long as the python script has to load all modules if we start from the top and finally giving output.
Here is the python code
from gtts import gTTS
language = 'en'
#myobj = gTTS(text='Do you know the person? Yes or No', lang=language, slow=True)
#myobj.save("question1.mp3")
#myobj = gTTS(text='What is his or her name', lang=language, slow=True)
#myobj.save("question2.mp3")
import csv
import pandas as pd
import numpy as np
#with open('database.csv','w') as f:
# writer=csv.writer(f)
# writer.writerow(['Chinmay',embedded])
face_embeddings=np.array(pd.read_csv('database.csv',header=None))
face_names=np.array(pd.read_csv('database_names.csv',header=None))
from cv2 import cv2
import matplotlib.pyplot as plt
import matplotlib.patches as patches
from align import AlignDlib
import numpy as np
import matplotlib.pyplot as plt
from PIL import Image
import torch
import torch.nn as nn
import torch.nn.functional as F
import os
from torch.autograd import Variable
from model import create_model
import transforms as transforms
from skimage import io
from skimage.transform import resize
from models import *
import matplotlib.pyplot as plt
from keras.models import load_model
from keras.preprocessing.image import load_img, img_to_array
from util.model import CNNModel, generate_caption_beam_search
import os
from config import config
from pickle import load
import sys
cut_size = 44
transform_test = transforms.Compose([
transforms.TenCrop(cut_size),
transforms.Lambda(lambda crops: torch.stack([transforms.ToTensor()(crop) for crop in crops])),
])
class_names = ['Angry', 'Disgust', 'Fear', 'Happy', 'Sad', 'Surprise', 'Neutral']
final_text=''
nn4_small2_pretrained = create_model()
nn4_small2_pretrained.load_weights('weights/nn4.small2.v1.h5')
def rgb2gray(rgb):
return np.dot(rgb[...,:3], [0.299, 0.587, 0.114])
def load_image(path):
img = cv2.imread(path, 1)
# OpenCV loads images with color channels
# in BGR order. So we need to reverse them
return img[...,::-1]
def extract_features(filename, model, model_type):
if model_type == 'inceptionv3':
from keras.applications.inception_v3 import preprocess_input
target_size = (299, 299)
elif model_type == 'vgg16':
from keras.applications.vgg16 import preprocess_input
target_size = (224, 224)
# Loading and resizing image
image = load_img(filename, target_size=target_size)
# Convert the image pixels to a numpy array
image = img_to_array(image)
# Reshape data for the model
image = image.reshape((1, image.shape[0], image.shape[1], image.shape[2]))
# Prepare the image for the CNN Model model
image = preprocess_input(image)
# Pass image into model to get encoded features
features = model.predict(image, verbose=0)
return features
def getrecogstr( imgurl ):
# Path of Image
#image_file=imgurl
image_file = sys.argv[1]
# Initialize the OpenFace face alignment utility
alignment = AlignDlib('models/landmarks.dat')
# Load an image
jc_orig = load_image(image_file)
# Detect face and return bounding box -
bb = alignment.getAllFaceBoundingBoxes(jc_orig)
net = VGG('VGG19')
checkpoint = torch.load(os.path.join('FER2013_VGG19', 'PrivateTest_model.t7'),map_location='cpu')
net.load_state_dict(checkpoint['net'])
# Load the tokenizer
tokenizer_path = config['tokenizer_path']
tokenizer = load(open(tokenizer_path, 'rb'))
# Max sequence length (from training)
max_length = config['max_length']
caption_model = load_model('model.hdf5')
image_model = CNNModel(config['model_type'])
for i in bb:
# Transform image using specified face landmark indices and crop image to 96x96
jc_aligned = alignment.align(96, jc_orig, i, landmarkIndices=AlignDlib.OUTER_EYES_AND_NOSE)
location=(i.height()+i.width())/(jc_orig.shape[0]+jc_orig.shape[1])
# Finding the emotion of cropped image
gray = rgb2gray(jc_aligned)
gray = resize(gray, (48,48), mode='symmetric').astype(np.uint8)
img = gray[:, :, np.newaxis]
img = np.concatenate((img, img, img), axis=2)
img = Image.fromarray(img)
inputs = transform_test(img)
#net.cuda()
net.eval()
ncrops, c, h, w = np.shape(inputs)
inputs = inputs.view(-1, c, h, w)
#inputs = inputs.cuda()
inputs = Variable(inputs, volatile=True)
outputs = net(inputs)
outputs_avg = outputs.view(ncrops, -1).mean(0) # avg over crops
score = F.softmax(outputs_avg)
_, predicted = torch.max(outputs_avg.data, 0)
# Find the name of the person in the image
jc_aligned = (jc_aligned / 255.).astype(np.float32)
embeddings = nn4_small2_pretrained.predict(np.expand_dims(jc_aligned, axis=0))[0]
print("##")
print(embeddings)
matched_embeddings=1000
for j in range(len(face_embeddings)):
temp=np.sum(np.square(embeddings-face_embeddings[j]))
if (temp<=0.56 and temp <matched_embeddings):
matched_embeddings=np.sum(np.square(embeddings-face_embeddings[j]))
face_index=j
print(temp)
print('above')
if matched_embeddings!=1000:
face_name=face_names[face_index][0]
print("##known")
else:
face_name='Unknown'
print("##unknown")
#print("Unknown Person detected. Do you know this person yes or no ?")
#Play welcome1.mp3
#Play welcome2.mp3 if input is yes
final_text+= face_name+' expression is '+class_names[int(predicted.cpu().numpy())] + "."
print("##"+final_text)
sys.stdout.flush()
getrecogstr()
Here is the Node code
const express = require('express');
const app = express();
const bodyParser = require('body-parser');
const port = 1000;
const spawn = require("child_process").spawn;
app.use(bodyParser.json()); // application/json
app.use((req, res, next) => {
res.setHeader('Access-Control-Allow-Origin', '*');
res.setHeader('Access-Control-Allow-Methods', 'OPTIONS, GET, POST, PUT, PATCH, DELETE');
res.setHeader('Access-Control-Allow-Headers', 'Content-Type, Authorization');
next();
});
app.get('/test', (req, res, next) => {
const imgurl = req.query.imgurl;
var process = spawn('python', ["./final.py",
imgurl,
]);
process.stdout.on('data', function (data) {
const recog_str = data.toString().split('##')[3];
console.log(recog_str);
res.json(recog_str)
})
})
server.listen(port, () => {
console.log("Ok");
})
I just want to skip that part of loading modules every time. I know we have to run the modules for them to be in memory but it's taking so long. Can do like the python script is running all the time and we can send arguments from node js in the middle of that running and call a function which can return that string?

You could use a global variable and message communication between node and spawned python process.
I got the idea from this tutorial which is regarding the message queue, but the same method can be applied here.
app.js
const app = require('express')();
const uuid = require('uuid');
const spawn = require("child_process").spawn;
var py = spawn('python', ["./face.py"]);
var globalobj = {}
//whenever any data arrives, it will be stored in globalobj.
py.stdout.on('data', function (data) {
try {
const { id, msg } = JSON.parse(data.toString());
globalobj[id] = msg;
} catch (err) {
//If data chunk received is incomplete(child process sent large output) json parse fails.
}
});
const delay = () => new Promise(resolve => {
setTimeout(() => {
resolve();
}, 4000);
});
app.get('/test', async (req, res, next) => {
const url = req.query.imgurl;
const id = uuid.v4();
py.stdin.write(JSON.stringify({ id, url }) + "\n");
await delay();
//If no response has arrived from the child process, globalobj wont have id key.
if (globalobj[id] != undefined) {
res.send(globalobj[id]);
delete globalobj[id];
} else {
res.status(500).send('No response from child process');
}
});
app.listen(3000, 'localhost', () => {
console.log(`server started on port 3000`);
});
The downsides are the messages which get a response after the delay will be accumulated in the global object. Also the py.stdout.on('data', function(data){}) returns the data in stream, so if message is larger it will be split into chunks by nodejs. See this post
Reason for using \n when writing to child stdin can be found here.
main.py
import sys, json
while True:
stdin = sys.stdin.readline().replace("\n", "")
if stdin:
data = json.loads(stdin)
#do your computation here
print(json.dumps({'id': data['id'], 'msg': 'your message'}), flush=True)
stdin = None
When I quickly tested, it worked, but it may not work in all cases. Test this method well before using it.

Splash (+scrapy) does not render web page correctly

Im' using Scrapy + Splash, I have problems downloading this page: http://new.abb.com/jobs/it/center#JobCountry=IT&JobCity=any&JobFunction=any&JobRole=any&JobText='http://new.abb.com/jobs/it/center#JobCountry=IT&JobCity=any&JobFunction=any&JobRole=any&JobText=
It seems that Splash cannot execute the javascript correctly.
Here is a stripped down, working, self contanied, version of my program (sorry if not stripped down at best)
# -*- coding: utf-8 -*- import scrapy from scrapy_splash import SplashRequest from scrapy.selector import Selector from scrapy.http import HtmlResponse import sys import io import os import base64
def saveFile(ss, fileNameExt, folderName):
f = open(folderName + '/' + fileNameExt, 'w')
f.write(ss)
f.close()
return fileNameExt
def savePng(png_bytes, fileNameExt, folderName):
f = open( folderName +'/' + fileNameExt, 'wb')
f.write(png_bytes)
f.close()
return fileNameExt
def savePageOriginalInFolder(response, folderName, chiave='pag1'):
fileName = "site.html"
testo = response.data[chiave].decode('utf8')
return saveFile(testo, fileName, folderName) def savePagePng(response, folderName, pngDataName):
fileName = 'site.png'
if hasattr(response, 'data'):
png_bytes = base64.b64decode(response.data[pngDataName])
return savePng(png_bytes, fileName, folderName)
class GenericoSpider(scrapy.Spider):
name = 'provaAbb'
def asSplashRequest(self, url, callback, id_elenco="no_id", id_sessione="no_id_sessione"):
return SplashRequest(
url = url,
endpoint='execute',
args={'lua_source': self.script, 'id_elenco': id_elenco, 'id_sessione': id_sessione},
callback=callback,
)
outDir = name # prendo in nome della cartella dal nome dello spider
db_name = ""
def start_requests(self):
sito = 'http://new.abb.com/jobs/it/center#JobCountry=IT&JobCity=any&JobFunction=any&JobRole=any&JobText='
yield self.asSplashRequest(sito, self.parse_list, 'id_mio_elenco')
script = """
function main(splash)
local url = splash.args.url
splash:set_viewport_size(1280, 2500)
splash:init_cookies(splash.args.cookies)
assert(splash:go(url))
assert(splash:wait(10))
return {
url = splash:url(),
pag1 = splash:html(),
png1 = splash:png(),
id_elenco = splash.args.id_elenco,
id_sessione = splash.args.id_sessione,
cookies = splash:get_cookies(),
tt = splash.args
}
end
"""
def parse_list(self, response):
for ss in response.data:
if len(ss) >= 4:
if ss[0:3] == 'pag':
fileName = savePageOriginalInFolder(response, self.outDir, ss)
elif ss[0:3] == 'png':
fileName = savePagePng(response, self.outDir,ss)
A part of the settings.py
DOWNLOADER_MIDDLEWARES = {
'scrapy_splash.SplashCookiesMiddleware': 723,
'scrapy_splash.SplashMiddleware': 725,
'scrapy.downloadermiddlewares.httpcompression.HttpCompressionMiddleware': 810, }
SPIDER_MIDDLEWARES = {
'scrapy_splash.SplashDeduplicateArgsMiddleware': 100, }
DUPEFILTER_CLASS = 'scrapy_splash.SplashAwareDupeFilter'
HTTPCACHE_STORAGE = 'scrapy_splash.SplashAwareFSCacheStorage'
Result, as you can see there is the spinner in the list area and page numbers are not loaded. (augmenting wait time in lua did not solve the problem)

Scraping a website with content added via javascript with PySide in Python

I am trying to scrape data from a website using PyQt4 in python. However, this website is adding the data I'm interested in via javascript. Is there a way to ask Selnium to wait for the data before return it? So far, we've tried:
import sys
from PySide.QtGui import *
from PySide.QtCore import *
from PySide.QtWebKit import *
from BeautifulSoup import BeautifulSoup
def test():
print "coucou"
class Render(QWebPage):
def __init__(self, url):
self.app = QApplication(sys.argv)
QWebPage.__init__(self)
self.loadFinished.connect(self._loadFinished)
self.timerScreen = QTimer()
self.timerScreen.setInterval(10000)
self.timerScreen.setSingleShot(True)
self.timerScreen.timeout.connect(test)
self.mainFrame().load(QUrl(url))
self.app.exec_()
def _loadFinished(self, result):
self.frame = self.mainFrame()
self.app.quit()
def main():
url = '[redacted]'
r = Render(url)
html = r.frame.toHtml()
page = QWebPage()
page.settings().setAttribute(QWebSettings.AutoLoadImages, False)
page.settings().setAttribute(QWebSettings.PluginsEnabled, False)
page.mainFrame().setHtml(html)
dom = page.mainFrame().documentElement()
li = dom.findFirst("body")
print html
if not li.isNull():
classe = li.attribute("class")
text = li.toPlainText()
main()
Unfortunately, the content of the page doesn't show the relevant data.
We're using Python 2.7.5 and PySide 1.2.2.
Thanks in advance.

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