Python cv2.namedWindow方法代码示例

# 需要导入模块: import cv2 [as 别名]
# 或者: from cv2 import namedWindow [as 别名]
def createFigureAndSlider(name, state_dim):
    """
    Creating a window for the latent space visualization, an another for the slider to control it
    :param name: name of model (str)
    :param state_dim: (int)
    :return:
    """
    # opencv gui setup
    cv2.namedWindow(name, cv2.WINDOW_NORMAL)
    cv2.resizeWindow(name, 500, 500)
    cv2.namedWindow('slider for ' + name)
    # add a slider for each component of the latent space
    for i in range(state_dim):
        # the sliders MUST be between 0 and max, so we placed max at 100, and start at 50
        # So that when we substract 50 and divide 10 we get [-5,5] for each component
        cv2.createTrackbar(str(i), 'slider for ' + name, 50, 100, (lambda a: None)) 

# 需要导入模块: import cv2 [as 别名]
# 或者: from cv2 import namedWindow [as 别名]
def run(self):
        print("VEDIO server starts...")
        self.sock.bind(self.ADDR)
        self.sock.listen(1)
        conn, addr = self.sock.accept()
        print("remote VEDIO client success connected...")
        data = "".encode("utf-8")
        payload_size = struct.calcsize("L")
        cv2.namedWindow('Remote', cv2.WINDOW_AUTOSIZE)
        while True:
            while len(data) < payload_size:
                data += conn.recv(81920)
            packed_size = data[:payload_size]
            data = data[payload_size:]
            msg_size = struct.unpack("L", packed_size)[0]
            while len(data) < msg_size:
                data += conn.recv(81920)
            zframe_data = data[:msg_size]
            data = data[msg_size:]
            frame_data = zlib.decompress(zframe_data)
            frame = pickle.loads(frame_data)
            cv2.imshow('Remote', frame)
            if cv2.waitKey(1) & 0xFF == 27:
                break 

# 需要导入模块: import cv2 [as 别名]
# 或者: from cv2 import namedWindow [as 别名]
def run(self):
        window_name = "Olympe Streaming Example"
        cv2.namedWindow(window_name, cv2.WINDOW_NORMAL)
        main_thread = next(
            filter(lambda t: t.name == "MainThread", threading.enumerate())
        )
        while main_thread.is_alive():
            with self.flush_queue_lock:
                try:
                    yuv_frame = self.frame_queue.get(timeout=0.01)
                except queue.Empty:
                    continue
                try:
                    self.show_yuv_frame(window_name, yuv_frame)
                except Exception:
                    # We have to continue popping frame from the queue even if
                    # we fail to show one frame
                    traceback.print_exc()
                finally:
                    # Don't forget to unref the yuv frame. We don't want to
                    # starve the video buffer pool
                    yuv_frame.unref()
        cv2.destroyWindow(window_name) 

# 需要导入模块: import cv2 [as 别名]
# 或者: from cv2 import namedWindow [as 别名]
def display_multiple(images: List[Tuple[List, Optional[str]]]):
    """Displays one or more captures in a CV2 window. Useful for debugging

    Args:
        images: List of tuples containing MxNx3 pixel arrays and optional titles OR
            list of image data
    """
    for image in images:
        if isinstance(image, tuple):
            image_data = image[0]
        else:
            image_data = image

        if isinstance(image, tuple) and len(image) > 1:
            title = image[1]
        else:
            title = "Camera Output"

        cv2.namedWindow(title)
        cv2.moveWindow(title, 500, 500)
        cv2.imshow(title, image_data)
    cv2.waitKey(0)
    cv2.destroyAllWindows() 

# 需要导入模块: import cv2 [as 别名]
# 或者: from cv2 import namedWindow [as 别名]
def preview(self):
        """ Blocking function. Opens OpenCV window to display stream. """
        self.connect()
        win_name = 'RTSP'
        cv2.namedWindow(win_name, cv2.WINDOW_AUTOSIZE)
        cv2.moveWindow(win_name, 20, 20)

        while True:
            cv2.imshow(win_name, self.get_frame())
            # if self._latest is not None:
            #    cv2.imshow(win_name,self._latest)
            if cv2.waitKey(25) & 0xFF == ord('q'):
                break
        cv2.waitKey()
        cv2.destroyAllWindows()
        cv2.waitKey() 

# 需要导入模块: import cv2 [as 别名]
# 或者: from cv2 import namedWindow [as 别名]
def prepare(self):
    if self.save_folder and not os.path.exists(self.save_folder):
      try:
        os.makedirs(self.save_folder)
      except OSError:
        assert os.path.exists(self.save_folder),\
            "Error creating "+self.save_folder
    self.cam = Camera.classes[self.camera]()
    self.cam.open(**self.cam_kwargs)
    config = DISConfig(self.cam)
    config.main()
    self.bbox = config.box
    t,img0 = self.cam.get_image()
    self.correl = DIS(img0,bbox=self.bbox)
    if self.show_image:
      try:
        flags = cv2.WINDOW_NORMAL | cv2.WINDOW_KEEPRATIO
      except AttributeError:
        flags = cv2.WINDOW_NORMAL
      cv2.namedWindow("DISCorrel",flags)
    self.loops = 0
    self.last_fps_print = 0
    self.last_fps_loops = 0 

# 需要导入模块: import cv2 [as 别名]
# 或者: from cv2 import namedWindow [as 别名]
def prepare(self):
    if self.save_folder and not os.path.exists(self.save_folder):
      try:
        os.makedirs(self.save_folder)
      except OSError:
        assert os.path.exists(self.save_folder),\
            "Error creating "+self.save_folder
    self.cam = Camera.classes[self.camera]()
    self.cam.open(**self.cam_kwargs)
    self.ve = VE(**self.ve_kwargs)
    config = VE_config(self.cam,self.ve)
    config.main()
    self.ve.start_tracking()
    if self.show_image:
      try:
        flags = cv2.WINDOW_NORMAL | cv2.WINDOW_KEEPRATIO
      except AttributeError:
        flags = cv2.WINDOW_NORMAL
      cv2.namedWindow("Videoextenso",flags)
    self.loops = 0
    self.last_fps_print = 0
    self.last_fps_loops = 0 

# 需要导入模块: import cv2 [as 别名]
# 或者: from cv2 import namedWindow [as 别名]
def main():
    """Test code"""
    global mp
    mp = np.array((2, 1), np.float32)  # measurement

    def onmouse(k, x, y, s, p):
        global mp
        mp = np.array([[np.float32(x)], [np.float32(y)]])

    cv2.namedWindow("kalman")
    cv2.setMouseCallback("kalman", onmouse)
    kalman = Stabilizer(4, 2)
    frame = np.zeros((480, 640, 3), np.uint8)  # drawing canvas

    while True:
        kalman.update(mp)
        point = kalman.prediction
        state = kalman.filter.statePost
        cv2.circle(frame, (state[0], state[1]), 2, (255, 0, 0), -1)
        cv2.circle(frame, (point[0], point[1]), 2, (0, 255, 0), -1)
        cv2.imshow("kalman", frame)
        k = cv2.waitKey(30) & 0xFF
        if k == 27:
            break 

# 需要导入模块: import cv2 [as 别名]
# 或者: from cv2 import namedWindow [as 别名]
def parse_grid(path):
    original = cv2.imread(path, cv2.IMREAD_GRAYSCALE)
    processed = pre_process_image(original)
    
#    cv2.namedWindow('processed',cv2.WINDOW_AUTOSIZE)
#    processed_img = cv2.resize(processed, (500, 500))          # Resize image
#    cv2.imshow('processed', processed_img)
    
    corners = find_corners_of_largest_polygon(processed)
    cropped = crop_and_warp(original, corners)
    
#    cv2.namedWindow('cropped',cv2.WINDOW_AUTOSIZE)
#    cropped_img = cv2.resize(cropped, (500, 500))              # Resize image
#    cv2.imshow('cropped', cropped_img)
    
    squares = infer_grid(cropped)
#    print(squares)
    digits = get_digits(cropped, squares, 28)
#    print(digits)
    final_image = show_digits(digits)
    return final_image 

# 需要导入模块: import cv2 [as 别名]
# 或者: from cv2 import namedWindow [as 别名]
def train_generator(self, image_generator, mask_generator):
        # cv2.namedWindow('show', 0)
        # cv2.resizeWindow('show', 1280, 640)
        while True:
            image = next(image_generator)
            mask = next(mask_generator)
            label = self.make_regressor_label(mask).astype(np.float32)
            # print (image.dtype, label.dtype)
            # print (image.shape, label.shape)
            # exit()
            # cv2.imshow('show', image[0].astype(np.uint8))
            # cv2.imshow('label', label[0].astype(np.uint8))
            # mask = self.select_labels(mask)
            # print (image.shape)
            # print (mask.shape)
            # image = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)
            # mask = (mask.astype(np.float32)*255/33).astype(np.uint8)
            # mask_color = cv2.applyColorMap(mask, cv2.COLORMAP_JET)
            # print (mask_color.shape)
            # show = cv2.addWeighted(image, 0.5, mask_color, 0.5, 0.0)
            # cv2.imshow("show", show)
            # key = cv2.waitKey()
            # if key == 27:
            #     exit()
            yield (image, label) 

# 需要导入模块: import cv2 [as 别名]
# 或者: from cv2 import namedWindow [as 别名]
def cv2_show_image(window_name, image,
                   size_wh=None, location_xy=None):
    """Helper function for specifying window size and location when
    displaying images with cv2.

    Args:
        window_name: str window name
        image: ndarray image to display
        size_wh: window size (w, h)
        location_xy: window location (x, y)
    """

    if size_wh is not None:
        cv2.namedWindow(window_name,
                        cv2.WINDOW_KEEPRATIO | cv2.WINDOW_GUI_NORMAL)
        cv2.resizeWindow(window_name, *size_wh)
    else:
        cv2.namedWindow(window_name, cv2.WINDOW_AUTOSIZE)

    if location_xy is not None:
        cv2.moveWindow(window_name, *location_xy)

    cv2.imshow(window_name, image) 

# 需要导入模块: import cv2 [as 别名]
# 或者: from cv2 import namedWindow [as 别名]
def _init_trackbars(self):
        trackbars_window_name = "hsv settings"
        cv2.namedWindow(trackbars_window_name, cv2.WINDOW_NORMAL)

        # HSV Lower Bound
        h_min_trackbar = _Trackbar("H min", trackbars_window_name, 0, 255)
        s_min_trackbar = _Trackbar("S min", trackbars_window_name, 0, 255)
        v_min_trackbar = _Trackbar("V min", trackbars_window_name, 0, 255)

        # HSV Upper Bound
        h_max_trackbar = _Trackbar("H max", trackbars_window_name, 255, 255)
        s_max_trackbar = _Trackbar("S max", trackbars_window_name, 255, 255)
        v_max_trackbar = _Trackbar("V max", trackbars_window_name, 255, 255)

        # Kernel for morphology
        kernel_x = _Trackbar("kernel x", trackbars_window_name, 0, 30)
        kernel_y = _Trackbar("kernel y", trackbars_window_name, 0, 30)

        self._trackbars = [h_min_trackbar, s_min_trackbar, v_min_trackbar, h_max_trackbar, s_max_trackbar,
                           v_max_trackbar, kernel_x, kernel_y] 

# 需要导入模块: import cv2 [as 别名]
# 或者: from cv2 import namedWindow [as 别名]
def cvCaptureVideo():
    capture = cv2.VideoCapture(0)

    if capture.isOpened() is False:
        raise("IO Error")

    cv2.namedWindow("Capture", cv2.WINDOW_NORMAL)

    while True:
        ret, image = capture.read()

        if ret == False:
            continue

        cv2.imshow("Capture", image)

        if cv2.waitKey(1) & 0xFF == ord('q'):
            break

    capture.release()
    cv2.destroyAllWindows()


# MatplotによるWebカメラのキャプチャと表示 

# 需要导入模块: import cv2 [as 别名]
# 或者: from cv2 import namedWindow [as 别名]
def main():
    image = data.astronaut()

    cv2.namedWindow("aug", cv2.WINDOW_NORMAL)
    cv2.imshow("aug", image)
    cv2.waitKey(TIME_PER_STEP)

    # for value in cycle(np.arange(-255, 255, VAL_PER_STEP)):
    for value in np.arange(-255, 255, VAL_PER_STEP):
        aug = iaa.AddToHueAndSaturation(value=value)
        img_aug = aug.augment_image(image)
        img_aug = iaa.pad(img_aug, bottom=40)
        img_aug = ia.draw_text(img_aug, x=0, y=img_aug.shape[0]-38, text="value=%d" % (value,), size=30)

        cv2.imshow("aug", img_aug)
        cv2.waitKey(TIME_PER_STEP)

    images_aug = iaa.AddToHueAndSaturation(value=(-255, 255), per_channel=True).augment_images([image] * 64)
    ia.imshow(ia.draw_grid(images_aug))

    image = ia.quokka_square((128, 128))
    images_aug = []
    images_aug.extend(iaa.AddToHue().augment_images([image] * 10))
    images_aug.extend(iaa.AddToSaturation().augment_images([image] * 10))
    ia.imshow(ia.draw_grid(images_aug, rows=2)) 

# 需要导入模块: import cv2 [as 别名]
# 或者: from cv2 import namedWindow [as 别名]
def main():
    image = data.astronaut()[..., ::-1]  # rgb2bgr
    print(image.shape)

    cv2.namedWindow("aug", cv2.WINDOW_NORMAL)
    cv2.imshow("aug", image)
    cv2.waitKey(TIME_PER_STEP)

    for n_segments in cycle(reversed(np.arange(1, 200, SEGMENTS_PER_STEP))):
        aug = iaa.Superpixels(p_replace=0.75, n_segments=n_segments)
        time_start = time.time()
        img_aug = aug.augment_image(image)
        print("augmented %d in %.4fs" % (n_segments, time.time() - time_start))
        img_aug = ia.draw_text(img_aug, x=5, y=5, text="%d" % (n_segments,))

        cv2.imshow("aug", img_aug)
        cv2.waitKey(TIME_PER_STEP)