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')