def stream():
response.content_type = 'multipart/x-mixed-replace; boundary=frame'
v = VideoCamera()
while True:
r = yield (b'--frame\r\n'
b'Content-Type: image/jpeg\r\n\r\n' + v.get_frame() + b'\r\n\r\n')
def analyse_footage():
return Response(genFrame(VideoCamera()),
mimetype='multipart/x-mixed-replace; boundary=frame')
def video_feed():
return Response(gen(VideoCamera()),
mimetype='multipart/x-mixed-replace; boundary=frame')
def air_canvas():
return Response(gen_canvas(VideoCamera()),
mimetype='multipart/x-mixed-replace; boundary=frame')
import cv2
import sys
#from mail import sendEmail
from flask import Flask, render_template, Response
from camera import VideoCamera
#from flask_basicauth import BasicAuth
import time
import threading
email_update_interval = 600 # sends an email only once in this time interval
video_camera = VideoCamera(
flip=False) # creates a camera object, flip vertically
object_classifier = cv2.CascadeClassifier(
"models/fullbody_recognition_model.xml") # an opencv classifier
# App Globals (do not edit)
app = Flask(__name__)
app.config['BASIC_AUTH_USERNAME'] = '******'
app.config['BASIC_AUTH_PASSWORD'] = '******'
app.config['BASIC_AUTH_FORCE'] = True
#basic_auth = BasicAuth(app)
last_epoch = 0
def check_for_objects():
global last_epoch
while True:
#try:
frame, found_obj = video_camera.get_object(object_classifier)
#if found_obj and (time.time() - last_epoch) > email_update_interval:
def system_video_feed_out():
APP_config_ini = ConfigObj(APP_config_file, encoding='UTF8')
camera_url = APP_config_ini['camera_out']['rtsp']
return Response(gen(VideoCamera(camera_url), camera_url),
mimetype='multipart/x-mixed-replace; boundary=frame')
def video_feed():
#Video streaming route. Put this in the src attribute of an img tag.
return Response(gen(VideoCamera()),
mimetype='multipart/x-mixed-replace; boundary=frame')
def shot_feed():
return Response(image(VideoCamera()), mimetype='image/jpeg')
from clarifai import rest
from clarifai.rest import ClarifaiApp
from clarifai.rest import Image as ClImage
import json
import cv2
from camera import VideoCamera
def pprint(x):
print(json.dumps(x, indent = 2, sort_keys = True))
cam = VideoCamera()
img = None
while True:
jpeg, img = cam.get_frame()
cv2.imshow("my webcam", img)
ch = cv2.waitKey(1)
'''if ch == 27:
break
if ch == 32:
print("taken")
cv2.imwrite("thepic.jpg", img)
break'''
del(cam)
cv2.destroyAllWindows()
app = ClarifaiApp(api_key = "d556e0ea9bd741d98e6fe8f4812f1b44")
model = app.models.get('bd367be194cf45149e75f01d59f77ba7')
# image = ClImage(file_obj=open('pizza.jpg', 'rb'))
img_str = cv2.imencode('.jpg', img)[1].tostring()
w800 x h600
with the first being live video
second to view captured image
By dascondor & Alfren
'''),
epilog="""---------------------------Alls well what ends well------------------------""")
my_parser.version = '1.01'
my_parser.add_argument('-host', '--hosted', action='store_true', default=False)
my_parser.add_argument('-po', '--port', type=int, default='8080')
my_parser.add_argument('-iid', '--HTMLIndexID', default=1, type=int)
app = Flask(__name__)
video_stream = VideoCamera()
@app.route('/')
def index():
return render_template(iid)
def gen(camera):
while True:
frame = camera.get_frame()
yield (b'--frame\r\n'
b'Content-Type: image/jpeg\r\n\r\n' + frame + b'\r\n\r\n')
@app.route('/video_feed')
def video_feed():
return Response(gen(video_stream),
mimetype='multipart/x-mixed-replace; boundary=frame')
# main.py
# import the necessary packages
from flask import Flask, render_template, Response, request
from camera import VideoCamera
import time
import threading
import os
pi_camera = VideoCamera(flip=False) # Flip the camera if needed
# App globals
app = Flask(__name__)
@app.route('/')
def index():
return render_template('index.html') # Simple web template to stream to
#get camera frame
def gen(camera):
while True:
frame = camera.get_frame()
yield (b'--frame\r\n'
b'Content-Type: image/jpeg\r\n\r\n' + frame + b'\r\n\r\n')
@app.route('/video_feed')
def video_feed():
return Response(gen(pi_camera),
mimetype='multipart/x-mixed-replace; boundary=frame')
def video_stream():
video_camera = VideoCamera()
video_camera.start_motion_detector()
# @file cam_test.py
# @brief Used to test the streaming of the camera with flask
# Author : Ackermann Gawen
# Last update : 10.06.2021
from flask import Flask, render_template, Response, request
from camera import VideoCamera
import time
import threading
import os
import cv2
pi_camera = VideoCamera(flip=True) # flip pi camera if upside down.
app = Flask(__name__)
@app.route('/streaming_camera')
def cam_stream():
"""
Route which display the video feed page
"""
global camera_state
return render_template('index.html', name=constants.FRONT_CAM, mode=camera_state, on=constants.STATE_ON, off=constants.STATE_OFF)
def gen(camera):
"""
Convert the frame into a response in bytes format
camera : The camera object
def trainer():
VideoCamera().__del__()
CameraDetect().__del__()
Traindata().train()
return jsonify(result=render_template('trainer.html'))
def video_feed():
global cam
if cam is None:
cam = VideoCamera()
return Response(gen(cam),
mimetype='multipart/x-mixed-replace; boundary=frame')
#Modified by smartbuilds.io
#Date: 27.09.20
#Desc: This web application serves a motion JPEG stream
# main.py
# import the necessary packages
from flask import Flask, render_template, Response, request
from camera import VideoCamera
from audio import PiAudio
import time
import threading
import os
import pyaudio
pi_camera = VideoCamera(flip=False) # flip pi camera if upside down.
pi_audio = PiAudio()
# App Globals (do not edit)
app = Flask(__name__)
@app.route('/')
def index():
return render_template('index.html')
def gen(camera):
#get camera frame
while True:
frame = camera.get_frame()
yield (b'--frame\r\n'
b'Content-Type: image/jpeg\r\n\r\n' + frame + b'\r\n\r\n')
def video_feed():
videoId = request.args.get("videoId")
fileName = "/home/icarus/projects/AgeGender/videos/" + "8427.mp4" #str(videoId)
return Response(gen(VideoCamera(fileName)),
mimetype='multipart/x-mixed-replace; boundary=frame')
def create_dataset():
return Response(create_data(VideoCamera()),
mimetype='multipart/x-mixed-replace; boundary=frame')
from camera import VideoCamera
# Locate dependencies
MODEL_PATH = Path("./models")
MODEL_NAME = "ball-predicter-model.pkl"
CAM_SOURCE = 0 # default capturing device
# GUI Size
WINDOW_WIDTH = 600
WINDOW_HEIGHT = 600
if __name__ == '__main__':
model = BallPredicter(MODEL_PATH, MODEL_NAME)
camera = VideoCamera(CAM_SOURCE, WINDOW_WIDTH, WINDOW_HEIGHT)
while not camera.is_interrupted():
camera.update_frames()
main_frame = camera.get_main_frame()
pred_frame = camera.get_pred_frame()
predicted_class = model.get_predicted_class(pred_frame)
camera.draw_prediction_box(main_frame)
camera.display_class(main_frame, predicted_class)
camera.display_window(main_frame)
# When everything done, release the capture
def train_dataset():
print("training going on................................")
VideoCamera.train()
return redirect(url_for('startpage'))
def pose():
return Response(gen(VideoCamera(),'pose'),
mimetype='multipart/x-mixed-replace; boundary=frame')
def index():
obj=VideoCamera()
mask=obj.mask_status()
return render_template('index.html',mask=mask)
text2 = text.encode('utf-8').strip()
#engine = pyttsx.init()
if (len(text2) > 0):
#os.system(text2.split()[0])
speech = text2
system('say ' + str(speech))
"""
#engine.say(text)
#engine.runAndWait()
"""
time.sleep(5)
"""
#engine = pyttsx.init()
#engine.say(text)
#engine.runAndWait()
#os.remove('temp2.jpg')
#frame = camera.get_frame()
# show the output images
#cv2.imshow("Image", frame)
#cv2.imshow("Output", gray)
#cv2.waitKey(0)
"""
if cv2.waitKey(1) & 0xFF == ord('q'):
break
if __name__ == '__main__':
gen(VideoCamera())
def video_feed():
global color_HexCode
return Response(gen(VideoCamera(hexCode=color_HexCode)),
mimetype='multipart/x-mixed-replace; boundary=frame')
model = None
graph = None
app.secret_key = "secret"
def load_model():
global model
global graph
model = keras.models.load_model("gender_model.h5")
graph = K.get_session().graph
load_model()
video_stream = VideoCamera(model, graph)
@app.route('/')
def index():
return render_template('index.html')
@app.route('/about_us')
def about():
return render_template('about_us.html')
@app.route('/upload_image', methods=['GET', 'POST'])
def load_image_html():
if request.method == 'POST':
def video_feed():
url = 'http://*****:*****@192.168.1.101:7777/video'
test = gen(VideoCamera(url))
return Response(test, mimetype='multipart/x-mixed-replace; boundary=frame')
def analyse_car_video():
currentDir = os.path.dirname(os.path.realpath(__file__))
videoPath = os.path.join(currentDir,
"IP/SecurityCamera/basementFootage.mp4")
return Response(genFrame(VideoCamera(videoPath)),
mimetype='multipart/x-mixed-replace; boundary=frame')
import cv2
import sys
from mail import sendEmail
from flask import Flask, render_template, Response
from camera import VideoCamera
import threading
import netifaces as ni
from gpiozero import Button
# retrieves the ip address of the network on which Raspi is connected
ip = ni.ifaddresses('wlan0')[ni.AF_INET][0]['addr']
video_camera = VideoCamera(flip=True)
app = Flask(__name__)
# this function is run in a thread parallel to the video feed
def button_press():
# getting the button imput from GPIO pin 2 of Raspi
button = Button(2)
while True:
if button.is_pressed:
print("Button is pressed")
# getting the frame from the video_camera at the instant the button is pressed
frame = video_camera.get_frame()
# send an email with the attachment as the image
sendEmail(frame)
print("done!")
def face_detect():
return Response(generate(VideoCamera()),
mimetype='multipart/x-mixed-replace; boundary=frame')
def video_feed():
# vediocamera = VideoCamera.get_instance()
# print(dir(vediocamera))
return Response(gen(VideoCamera()),
mimetype='multipart/x-mixed-replace; boundary=frame')
import ad_retrieval.ad_retrieval as AdSystem
import nearest_neighbor_color
import colorDetection
from PIL import Image
# initialize the HOG descriptor/person detector
hog = cv2.HOGDescriptor()
hog.setSVMDetector(cv2.HOGDescriptor_getDefaultPeopleDetector())
# initialize HAAR pretrained haar cascade classifiers
faceCascade = cv2.CascadeClassifier('./haarcascade_frontalface_default.xml')
genderCascade = cv2.CascadeClassifier("./haarcascade_gender_alt2.xml")
# initialize our camera feed
cam = VideoCamera()
#initialize ad system
ads = AdSystem.create_ads_list()
# while the video stream is open, get the image frame by frame
while cam.video.isOpened():
#Get the image frame
image = cam.get_frame()
image = imutils.resize(image, width=min(400, image.shape[1]))
orig = image.copy()
# detect pedestrians in the image
(rects, weights) = hog.detectMultiScale(image, winStride=(4, 4),
def video_feed():
device_id = request.args['device_id']
access_token = request.args['access_token']
return Response(gen(VideoCamera(device_id, access_token)),
mimetype='multipart/x-mixed-replace; boundary=frame')
