showing video on the entire screen using OpenCV and Tkiner

It's not a hard task if you don't care about execution time! We knew that resizing of an image isn't a rocket science for common user, but under the hood it takes some time to resize each frame. And if you really wonder about time and options - there're many options to play around from numpy/scipy to skimage/skvideo.

But let's try to do something with your code "as is" so we have two options to play with: cv2 and Image. For testing I grabbed 20 secs of "Keyboard Cat" video from youtube (480p) and resize each frame upto 1080p, and GUI looks like this (fullscreen 1920x1080):

Resize Methods / timeit elapsed time of showing frames:

• cv2.resize() / ~81.377 s.
• Image.resize() / ~82.98 s.

As you see - no big difference between theese two so here's a code (only Application class and video_loop changed):

#importstry:    import tkinter as tkexcept:    import Tkinter as tkfrom PIL import Image, ImageTkimport argparseimport datetimeimport cv2import osclass Application:    def __init__(self, output_path = "./"):        """ Initialize application which uses OpenCV + Tkinter. It displays            a video stream in a Tkinter window and stores current snapshot on disk """        self.vs = cv2.VideoCapture('KeyCat.mp4') # capture video frames, 0 is your default video camera        self.output_path = output_path  # store output path        self.current_image = None  # current image from the camera        self.root = tk.Tk()  # initialize root window        self.root.title("PyImageSearch PhotoBooth")  # set window title        # self.destructor function gets fired when the window is closed        self.root.protocol('WM_DELETE_WINDOW', self.destructor)        self.root.attributes("-fullscreen", True)        # getting size to resize! 30 - space for button        self.size = (self.root.winfo_screenwidth(), self.root.winfo_screenheight() - 30)        self.panel = tk.Label(self.root)  # initialize image panel        self.panel.pack(fill='both', expand=True)        # create a button, that when pressed, will take the current frame and save it to file        self.btn = tk.Button(self.root, text="Snapshot!", command=self.take_snapshot)        self.btn.pack(fill='x', expand=True)        # start a self.video_loop that constantly pools the video sensor        # for the most recently read frame        self.video_loop()    def video_loop(self):        """ Get frame from the video stream and show it in Tkinter """        ok, frame = self.vs.read()  # read frame from video stream        if ok:  # frame captured without any errors            cv2image = cv2.cvtColor(frame, cv2.COLOR_BGR2RGBA)  # convert colors from BGR to RGBA            cv2image = cv2.resize(cv2image, self.size, interpolation=cv2.INTER_NEAREST)            self.current_image = Image.fromarray(cv2image) #.resize(self.size, resample=Image.NEAREST)  # convert image for PIL            self.panel.imgtk = ImageTk.PhotoImage(image=self.current_image)            self.panel.config(image=self.panel.imgtk)  # show the image            self.root.after(1, self.video_loop)  # call the same function after 30 milliseconds

But you knew - do such a things "on fly" isn't a good idea, so lets try to resize all frames first and then do all stuff(only Application class and video_loop method changed, resize_video method added):

class Application:    def __init__(self, output_path = "./"):        """ Initialize application which uses OpenCV + Tkinter. It displays            a video stream in a Tkinter window and stores current snapshot on disk """        self.vs = cv2.VideoCapture('KeyCat.mp4') # capture video frames, 0 is your default video camera        ...        # init frames        self.frames = self.resize_video()        self.video_loop()def resize_video(self):    temp = list()    try:        temp_count_const = cv2.CAP_PROP_FRAME_COUNT    except AttributeError:        temp_count_const = cv2.cv.CV_CAP_PROP_FRAME_COUNT    frames_count = self.vs.get(temp_count_const)    while self.vs.isOpened():        ok, frame = self.vs.read()  # read frame from video stream        if ok:  # frame captured without any errors            cv2image = cv2.cvtColor(frame, cv2.COLOR_BGR2RGBA)  # convert colors from BGR to RGBA            cv2image = cv2.resize(cv2image, self.size, interpolation=cv2.INTER_NEAREST)            cv2image = Image.fromarray(cv2image)  # convert image for PIL            temp.append(cv2image)            # simple progress print w/o sys import            print('%d/%d\t%d%%' % (len(temp), frames_count, ((len(temp)/frames_count)*100)))        else:            return tempdef video_loop(self):    """ Get frame from the video stream and show it in Tkinter """    if len(self.frames) != 0:        self.current_image = self.frames.pop(0)        self.panel.imgtk = ImageTk.PhotoImage(self.current_image)        self.panel.config(image=self.panel.imgtk)        self.root.after(1, self.video_loop)  # call the same function after 30 milliseconds

timeit elapsed time of showing pre-resized frames: ~78.78 s.

As you see - resizing isn't a main problem of your script, but a good option!