Python cv2.CAP_PROP_FRAME_HEIGHT Examples

The following are 30 code examples of cv2.CAP_PROP_FRAME_HEIGHT(). You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. You may also want to check out all available functions/classes of the module cv2 , or try the search function .
Example #1
Source File: cv2Iterator.py    From dynamic-training-with-apache-mxnet-on-aws with Apache License 2.0 10 votes vote down vote up
def __init__(self, capture=cv2.VideoCapture(0), frame_resize=None):
        self._capture = capture
        self._frame_resize = None
        if frame_resize:
            if isinstance(frame_resize, (tuple, list)) and (len(frame_resize) == 2):
                self._frame_resize = tuple(map(int, frame_resize))
                self._frame_shape = (1, 3, self._frame_resize[0], self._frame_resize[1])
            elif isinstance(frame_resize, float):
                width = int(self._capture.get(cv2.CAP_PROP_FRAME_WIDTH)*frame_resize)
                height = int(self._capture.get(cv2.CAP_PROP_FRAME_HEIGHT)*frame_resize)
                self._frame_shape = (1, 3, width, height)
                self._frame_resize = (width, height)
            else:
                assert False, "frame_resize should be a tuple of (x,y) pixels "
                "or a float setting the scaling factor"
        else:
            self._frame_shape = (1, 3,
                int(self._capture.get(cv2.CAP_PROP_FRAME_WIDTH)),
                int(self._capture.get(cv2.CAP_PROP_FRAME_HEIGHT))) 
Example #2
Source File: rivagan.py    From RivaGAN with MIT License 9 votes vote down vote up
def encode(self, video_in, data, video_out):
        assert len(data) == self.data_dim

        video_in = cv2.VideoCapture(video_in)
        width = int(video_in.get(cv2.CAP_PROP_FRAME_WIDTH))
        height = int(video_in.get(cv2.CAP_PROP_FRAME_HEIGHT))
        length = int(video_in.get(cv2.CAP_PROP_FRAME_COUNT))

        data = torch.FloatTensor([data]).cuda()
        video_out = cv2.VideoWriter(
            video_out, cv2.VideoWriter_fourcc(*'mp4v'), 20.0, (width, height))

        for i in tqdm(range(length)):
            ok, frame = video_in.read()
            frame = torch.FloatTensor([frame]) / 127.5 - 1.0      # (L, H, W, 3)
            frame = frame.permute(3, 0, 1, 2).unsqueeze(0).cuda()  # (1, 3, L, H, W)
            wm_frame = self.encoder(frame, data)                       # (1, 3, L, H, W)
            wm_frame = torch.clamp(wm_frame, min=-1.0, max=1.0)
            wm_frame = (
                (wm_frame[0, :, 0, :, :].permute(1, 2, 0) + 1.0) * 127.5
            ).detach().cpu().numpy().astype("uint8")
            video_out.write(wm_frame)

        video_out.release() 
Example #3
Source File: chapter2.py    From OpenCV-Computer-Vision-Projects-with-Python with MIT License 7 votes vote down vote up
def main():
    device = cv2.CAP_OPENNI
    capture = cv2.VideoCapture(device)
    if not(capture.isOpened()):
        capture.open(device)

    capture.set(cv2.CAP_PROP_FRAME_WIDTH, 640)
    capture.set(cv2.CAP_PROP_FRAME_HEIGHT, 480)

    app = wx.App()
    frame = MyFrame(None, -1, 'chapter2.py', capture)
    frame.Show(True)
#   self.SetTopWindow(frame)
    app.MainLoop()

    # When everything done, release the capture
    capture.release()
    cv2.destroyAllWindows() 
Example #4
Source File: yolo.py    From keras-yolov3-KF-objectTracking with MIT License 7 votes vote down vote up
def detect_video(yolo, video_path, output_path=""):
    import cv2
    vid = cv2.VideoCapture(video_path)
    if not vid.isOpened():
        raise IOError("Couldn't open webcam or video")
    video_FourCC    = int(vid.get(cv2.CAP_PROP_FOURCC))
    video_fps       = vid.get(cv2.CAP_PROP_FPS)
    video_size      = (int(vid.get(cv2.CAP_PROP_FRAME_WIDTH)),
                        int(vid.get(cv2.CAP_PROP_FRAME_HEIGHT)))
    isOutput = True if output_path != "" else False
    if isOutput:
        print("!!! TYPE:", type(output_path), type(video_FourCC), type(video_fps), type(video_size))
        out = cv2.VideoWriter(output_path, video_FourCC, video_fps, video_size)
    accum_time = 0
    curr_fps = 0
    fps = "FPS: ??"
    prev_time = timer()
    while True:
        return_value, frame = vid.read()
        image = Image.fromarray(frame)
        image = yolo.detect_image(image)
        result = np.asarray(image)
        curr_time = timer()
        exec_time = curr_time - prev_time
        prev_time = curr_time
        accum_time = accum_time + exec_time
        curr_fps = curr_fps + 1
        if accum_time > 1:
            accum_time = accum_time - 1
            fps = "FPS: " + str(curr_fps)
            curr_fps = 0
        cv2.putText(result, text=fps, org=(3, 15), fontFace=cv2.FONT_HERSHEY_SIMPLEX,
                    fontScale=0.50, color=(255, 0, 0), thickness=2)
        cv2.namedWindow("result", cv2.WINDOW_NORMAL)
        cv2.imshow("result", result)
        if isOutput:
            out.write(result)
        if cv2.waitKey(1) & 0xFF == ord('q'):
            break
    yolo.close_session() 
Example #5
Source File: videocapturethreading.py    From video-capture-async with Apache License 2.0 6 votes vote down vote up
def _run(self, n_frames=500, width=1280, height=720, with_threading=False):
        if with_threading:
            cap = VideoCaptureTreading(0)
        else:
            cap = cv2.VideoCapture(0)
        cap.set(cv2.CAP_PROP_FRAME_WIDTH, width)
        cap.set(cv2.CAP_PROP_FRAME_HEIGHT, height)
        if with_threading:
            cap.start()
        t0 = time.time()
        i = 0
        while i < n_frames:
            _, frame = cap.read()
            cv2.imshow('Frame', frame)
            cv2.waitKey(1) & 0xFF
            i += 1
        print('[i] Frames per second: {:.2f}, with_threading={}'.format(n_frames / (time.time() - t0), with_threading))
        if with_threading:
            cap.stop()
        cv2.destroyAllWindows() 
Example #6
Source File: preprocess.py    From filmstrip with MIT License 6 votes vote down vote up
def getInfo(sourcePath):
    cap = cv2.VideoCapture(sourcePath)
    info = {
        "framecount": cap.get(cv2.CAP_PROP_FRAME_COUNT),
        "fps": cap.get(cv2.CAP_PROP_FPS),
        "width": int(cap.get(cv2.CAP_PROP_FRAME_WIDTH)),
        "height": int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT)),
        "codec": int(cap.get(cv2.CAP_PROP_FOURCC))
    }
    cap.release()
    return info

#
# Extracts one frame for every second second of video.
# Effectively compresses a video down into much less data.
# 
Example #7
Source File: demo.py    From blueoil with Apache License 2.0 6 votes vote down vote up
def __init__(self, video_source, video_width, video_height, video_fps, queue_size=1):
        self.video_fps = video_fps

        vc = cv2.VideoCapture(video_source)

        if hasattr(cv2, 'cv'):
            vc.set(cv2.cv.CV_CAP_PROP_FRAME_WIDTH, video_width)
            vc.set(cv2.cv.CV_CAP_PROP_FRAME_HEIGHT, video_height)
            vc.set(cv2.cv.CV_CAP_PROP_FPS, video_fps)
        else:
            vc.set(cv2.CAP_PROP_FRAME_WIDTH, video_width)
            vc.set(cv2.CAP_PROP_FRAME_HEIGHT, video_height)
            vc.set(cv2.CAP_PROP_FPS, video_fps)

        self.stream = vc
        self.stopped = False
        self.queue = Queue(maxsize=queue_size)
        self.thread = Thread(target=self.update, args=())
        self.thread.daemon = True
        self.thread.start() 
Example #8
Source File: cv2Iterator.py    From training_results_v0.6 with Apache License 2.0 6 votes vote down vote up
def __init__(self, capture=cv2.VideoCapture(0), frame_resize=None):
        self._capture = capture
        self._frame_resize = None
        if frame_resize:
            if isinstance(frame_resize, (tuple, list)) and (len(frame_resize) == 2):
                self._frame_resize = tuple(map(int, frame_resize))
                self._frame_shape = (1, 3, self._frame_resize[0], self._frame_resize[1])
            elif isinstance(frame_resize, float):
                width = int(self._capture.get(cv2.CAP_PROP_FRAME_WIDTH)*frame_resize)
                height = int(self._capture.get(cv2.CAP_PROP_FRAME_HEIGHT)*frame_resize)
                self._frame_shape = (1, 3, width, height)
                self._frame_resize = (width, height)
            else:
                assert False, "frame_resize should be a tuple of (x,y) pixels "
                "or a float setting the scaling factor"
        else:
            self._frame_shape = (1, 3,
                int(self._capture.get(cv2.CAP_PROP_FRAME_WIDTH)),
                int(self._capture.get(cv2.CAP_PROP_FRAME_HEIGHT))) 
Example #9
Source File: video.py    From visual_dynamics with MIT License 6 votes vote down vote up
def __init__(self, device=None, size=None, fps=None, sync=False):
        self.device = device or 0
        self.size = size or (480, 640)
        fps = fps or 30

        self.cap = cv2.VideoCapture(self.device)
        cap_height, cap_width = self.cap.get(cv2.CAP_PROP_FRAME_HEIGHT), self.cap.get(cv2.CAP_PROP_FRAME_WIDTH)
        if cap_height != self.size[0]:
            self.cap.set(cv2.CAP_PROP_FRAME_HEIGHT, self.size[0])
        if cap_width != self.size[1]:
            self.cap.set(cv2.CAP_PROP_FRAME_WIDTH, self.size[1])
        cap_fps = self.cap.get(cv2.CAP_PROP_FPS)
        if cap_fps != fps:
            self.cap.set(cv2.CAP_PROP_FPS, fps)
        if sync:
            raise ValueError("sync not supported") 
Example #10
Source File: run_estimator_ps.py    From VNect with Apache License 2.0 6 votes vote down vote up
def init():
    # initialize VNect estimator
    global estimator
    estimator = VNectEstimator()
    # catch the video stream
    global camera_capture
    camera_capture = cv2.VideoCapture(video)
    assert camera_capture.isOpened(), 'Video stream not opened: %s' % str(video)
    global W_img, H_img
    W_img, H_img = (int(camera_capture.get(cv2.CAP_PROP_FRAME_WIDTH)),
                    int(camera_capture.get(cv2.CAP_PROP_FRAME_HEIGHT)))


################
### Box Loop ###
################
# use a simple HOG method to initialize bounding box 
Example #11
Source File: utils.py    From ActionAI with GNU General Public License v3.0 6 votes vote down vote up
def source_capture(source):
    source = int(source) if source.isdigit() else source
    cap = cv2.VideoCapture(source)

    fourcc_cap = cv2.VideoWriter_fourcc(*'MJPG')
    cap.set(cv2.CAP_PROP_FOURCC, fourcc_cap)
    cap.set(cv2.CAP_PROP_FRAME_WIDTH, cfg.w)
    cap.set(cv2.CAP_PROP_FRAME_HEIGHT, cfg.h)
    return cap 
Example #12
Source File: webcam_video_stream.py    From AugmentedAutoencoder with MIT License 6 votes vote down vote up
def __init__(self, src, width, height):
        # initialize the video camera stream and read the first frame
        # from the stream
        self.frame_counter = 1
        self.width = width
        self.height = height
        self.stream = cv2.VideoCapture(src)
        self.stream.set(cv2.CAP_PROP_FRAME_WIDTH, self.width)
        self.stream.set(cv2.CAP_PROP_FRAME_HEIGHT, self.height)
        (self.grabbed, self.frame) = self.stream.read()
        # initialize the variable used to indicate if the thread should
        # be stopped
        self.stopped = False
        #Debug stream shape
        self.real_width = int(self.stream.get(3))
        self.real_height = int(self.stream.get(4))
        print("> Start video stream with shape: {},{}".format(self.real_width,self.real_height)) 
Example #13
Source File: helper.py    From AugmentedAutoencoder with MIT License 6 votes vote down vote up
def __init__(self, src, width, height):
        # initialize the video camera stream and read the first frame
        # from the stream
        self.frame_counter = 1
        self.width = width
        self.height = height
        self.stream = cv2.VideoCapture(src)
        self.stream.set(cv2.CAP_PROP_FRAME_WIDTH, self.width)
        self.stream.set(cv2.CAP_PROP_FRAME_HEIGHT, self.height)
        (self.grabbed, self.frame) = self.stream.read()
        # initialize the variable used to indicate if the thread should
        # be stopped
        self.stopped = False
        #Debug stream shape
        self.real_width = int(self.stream.get(3))
        self.real_height = int(self.stream.get(4))
        print("> Start video stream with shape: {},{}".format(self.real_width,self.real_height)) 
Example #14
Source File: agegenderemotion_webcam.py    From libfaceid with MIT License 5 votes vote down vote up
def cam_init(cam_index, width, height): 
    cap = cv2.VideoCapture(cam_index)
    if sys.version_info < (3, 0):
        cap.set(cv2.cv.CV_CAP_PROP_FPS, 30)
        cap.set(cv2.cv.CV_CAP_PROP_FRAME_WIDTH,  width)
        cap.set(cv2.cv.CV_CAP_PROP_FRAME_HEIGHT, height)
    else:
        cap.set(cv2.CAP_PROP_FPS, 30)
        cap.set(cv2.CAP_PROP_FRAME_WIDTH,  width)
        cap.set(cv2.CAP_PROP_FRAME_HEIGHT, height)
    return cap 
Example #15
Source File: app_utils.py    From face-attendance-machine with Apache License 2.0 5 votes vote down vote up
def __init__(self, src, width, height):
        # initialize the video camera stream and read the first frame
        # from the stream
        self.stream = cv2.VideoCapture(src)
        self.stream.set(cv2.CAP_PROP_FRAME_WIDTH, width)
        self.stream.set(cv2.CAP_PROP_FRAME_HEIGHT, height)
        (self.grabbed, self.frame) = self.stream.read()

        # initialize the variable used to indicate if the thread should
        # be stopped
        self.stopped = False 
Example #16
Source File: yolo_matt.py    From keras-yolov3-KF-objectTracking with MIT License 5 votes vote down vote up
def detect_video(yolo, video_path, output_path=""):
    import cv2
    vid = cv2.VideoCapture(video_path)
    if not vid.isOpened():
        raise IOError("Couldn't open webcam or video")
    video_FourCC    = int(vid.get(cv2.CAP_PROP_FOURCC))
    video_fps       = vid.get(cv2.CAP_PROP_FPS)
    video_size      = (int(vid.get(cv2.CAP_PROP_FRAME_WIDTH)),
                        int(vid.get(cv2.CAP_PROP_FRAME_HEIGHT)))
    isOutput = True if output_path != "" else False
    if isOutput:
        print("!!! TYPE:", type(output_path), type(video_FourCC), type(video_fps), type(video_size))
        out = cv2.VideoWriter(output_path, video_FourCC, video_fps, video_size)
    accum_time = 0
    curr_fps = 0
    fps = "FPS: ??"
    prev_time = timer()
    while True:
        return_value, frame = vid.read()
        image = Image.fromarray(frame)
        image = yolo.detect_image(image)
        result = np.asarray(image)
        curr_time = timer()
        exec_time = curr_time - prev_time
        prev_time = curr_time
        accum_time = accum_time + exec_time
        curr_fps = curr_fps + 1
        if accum_time > 1:
            accum_time = accum_time - 1
            fps = "FPS: " + str(curr_fps)
            curr_fps = 0
        cv2.putText(result, text=fps, org=(3, 15), fontFace=cv2.FONT_HERSHEY_SIMPLEX,
                    fontScale=0.50, color=(255, 0, 0), thickness=2)
        cv2.namedWindow("result", cv2.WINDOW_NORMAL)
        cv2.imshow("result", result)
        if isOutput:
            out.write(result)
        if cv2.waitKey(1) & 0xFF == ord('q'):
            break
    yolo.close_session() 
Example #17
Source File: read_camera.py    From AnimalRecognitionDemo with Apache License 2.0 5 votes vote down vote up
def __init__(self, infile=0, fps=15.0):
        self.cam = cv2.VideoCapture(infile)
        self.cam.set(cv2.CAP_PROP_FPS, fps)
        self.cam.set(cv2.CAP_PROP_FRAME_WIDTH, IMAGE_WIDTH)
        self.cam.set(cv2.CAP_PROP_FRAME_HEIGHT, IMAGE_HEIGHT) 
Example #18
Source File: rivagan.py    From RivaGAN with MIT License 5 votes vote down vote up
def decode(self, video_in):
        video_in = cv2.VideoCapture(video_in)
        # width = int(video_in.get(cv2.CAP_PROP_FRAME_WIDTH))
        # height = int(video_in.get(cv2.CAP_PROP_FRAME_HEIGHT))
        length = int(video_in.get(cv2.CAP_PROP_FRAME_COUNT))

        for i in tqdm(range(length)):
            ok, frame = video_in.read()
            frame = torch.FloatTensor([frame]) / 127.5 - 1.0      # (L, H, W, 3)
            frame = frame.permute(3, 0, 1, 2).unsqueeze(0).cuda()  # (1, 3, L, H, W)
            data = self.decoder(frame)[0].detach().cpu().numpy()
            yield data 
Example #19
Source File: datasets.py    From pruning_yolov3 with GNU General Public License v3.0 5 votes vote down vote up
def __init__(self, sources='streams.txt', img_size=416, half=False):
        self.mode = 'images'
        self.img_size = img_size
        self.half = half  # half precision fp16 images

        if os.path.isfile(sources):
            with open(sources, 'r') as f:
                sources = [x.strip() for x in f.read().splitlines() if len(x.strip())]
        else:
            sources = [sources]

        n = len(sources)
        self.imgs = [None] * n
        self.sources = sources
        for i, s in enumerate(sources):
            # Start the thread to read frames from the video stream
            print('%g/%g: %s... ' % (i + 1, n, s), end='')
            cap = cv2.VideoCapture(0 if s == '0' else s)
            assert cap.isOpened(), 'Failed to open %s' % s
            w = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))
            h = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
            fps = cap.get(cv2.CAP_PROP_FPS) % 100
            _, self.imgs[i] = cap.read()  # guarantee first frame
            thread = Thread(target=self.update, args=([i, cap]), daemon=True)
            print(' success (%gx%g at %.2f FPS).' % (w, h, fps))
            thread.start()
        print('')  # newline 
Example #20
Source File: helper.py    From realtime_object_detection with MIT License 5 votes vote down vote up
def __init__(self, src, width, height):
        super(VideoStream, self).__init__()
        # initialize the video camera stream and read the first frame
        # from the stream
        self.frame_counter = 1
        self.width = width
        self.height = height
        self.stream = cv2.VideoCapture(src)
        self.stream.set(cv2.CAP_PROP_FRAME_WIDTH, self.width)
        self.stream.set(cv2.CAP_PROP_FRAME_HEIGHT, self.height)
        (self.grabbed, self.frame) = self.stream.read()
        #Debug stream shape
        self.real_width = int(self.stream.get(3))
        self.real_height = int(self.stream.get(4)) 
Example #21
Source File: testing_webcam_flask.py    From libfaceid with MIT License 5 votes vote down vote up
def cam_init(cam_index, width, height): 
    cap = cv2.VideoCapture(cam_index)
    if sys.version_info < (3, 0):
        cap.set(cv2.cv.CV_CAP_PROP_FPS, 30)
        cap.set(cv2.cv.CV_CAP_PROP_FRAME_WIDTH,  width)
        cap.set(cv2.cv.CV_CAP_PROP_FRAME_HEIGHT, height)
    else:
        cap.set(cv2.CAP_PROP_FPS, 30)
        cap.set(cv2.CAP_PROP_FRAME_WIDTH,  width)
        cap.set(cv2.CAP_PROP_FRAME_HEIGHT, height)
    return cap 
Example #22
Source File: predict.py    From image-segmentation-keras with MIT License 5 votes vote down vote up
def set_video(inp, video_name):
    cap = cv2.VideoCapture(inp)
    fps = int(cap.get(cv2.CAP_PROP_FPS))
    video_width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))
    video_height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
    size = (video_width, video_height)
    fourcc = cv2.VideoWriter_fourcc(*"XVID")
    video = cv2.VideoWriter(video_name, fourcc, fps, size)
    return cap, video, fps 
Example #23
Source File: usb_camera_demo.py    From blueoil with Apache License 2.0 5 votes vote down vote up
def init_camera(camera_width, camera_height):
    if hasattr(cv2, 'cv'):
        vc = cv2.VideoCapture(0)
        vc.set(cv2.cv.CV_CAP_PROP_FRAME_WIDTH, camera_width)
        vc.set(cv2.cv.CV_CAP_PROP_FRAME_HEIGHT, camera_height)
        vc.set(cv2.cv.CV_CAP_PROP_FPS, 60)
    else:
        vc = cv2.VideoCapture(0)
        vc.set(cv2.CAP_PROP_FRAME_WIDTH, camera_width)
        vc.set(cv2.CAP_PROP_FRAME_HEIGHT, camera_height)
        vc.set(cv2.CAP_PROP_FPS, 60)

    return vc 
Example #24
Source File: yolo.py    From keras-yolo3-master with MIT License 5 votes vote down vote up
def detect_video(yolo, video_path, output_path=""):
    import cv2
    vid = cv2.VideoCapture(0)

    if not vid.isOpened():
        raise IOError("Couldn't open webcam or video")
    video_FourCC    = int(vid.get(cv2.CAP_PROP_FOURCC))
    video_fps       = vid.get(cv2.CAP_PROP_FPS)
    video_size      = (int(vid.get(cv2.CAP_PROP_FRAME_WIDTH)),
                        int(vid.get(cv2.CAP_PROP_FRAME_HEIGHT)))
    isOutput = True if output_path != "" else False
    if isOutput:
        print("!!! TYPE:", type(output_path), type(video_FourCC), type(video_fps), type(video_size))
        out = cv2.VideoWriter(output_path, video_FourCC, video_fps, video_size)
    accum_time = 0
    curr_fps = 0
    fps = "FPS: ??"
    prev_time = timer()
    while True:
        return_value, frame = vid.read()
        image = Image.fromarray(frame)
        image = yolo.detect_image(image)
        result = np.asarray(image)
        curr_time = timer()
        exec_time = curr_time - prev_time
        prev_time = curr_time
        accum_time = accum_time + exec_time
        curr_fps = curr_fps + 1
        if accum_time > 1:
            accum_time = accum_time - 1
            fps = "FPS: " + str(curr_fps)
            curr_fps = 0
        cv2.putText(result, text=fps, org=(3, 15), fontFace=cv2.FONT_HERSHEY_SIMPLEX,
                    fontScale=0.50, color=(255, 0, 0), thickness=2)
        cv2.namedWindow("result", cv2.WINDOW_NORMAL)
        cv2.imshow("result", result)
        if isOutput:
            out.write(result)
        if cv2.waitKey(1) & 0xFF == ord('q'):
            break
    yolo.close_session() 
Example #25
Source File: utils.py    From AdaIN-TF with MIT License 5 votes vote down vote up
def __init__(self, src=0, width=None, height=None):
        # initialize the video camera stream and read the first frame
        # from the stream
        self.stream = cv2.VideoCapture(src)

        if width is not None and height is not None: # Both are needed to change default dims
            self.stream.set(cv2.CAP_PROP_FRAME_WIDTH, width)
            self.stream.set(cv2.CAP_PROP_FRAME_HEIGHT, height)

        (self.ret, self.frame) = self.stream.read()

        # initialize the variable used to indicate if the thread should
        # be stopped
        self.stopped = False 
Example #26
Source File: capture_video.py    From pytorch_mpiigaze with MIT License 5 votes vote down vote up
def main():
    parser = argparse.ArgumentParser()
    parser.add_argument('--output', '-o', type=str, default='videos')
    parser.add_argument('--cap-size', type=int, nargs=2, default=(640, 480))
    args = parser.parse_args()

    cap = cv2.VideoCapture(0)
    width, height = args.cap_size
    cap.set(cv2.CAP_PROP_FRAME_WIDTH, width)
    cap.set(cv2.CAP_PROP_FRAME_HEIGHT, height)

    output_dir = pathlib.Path(args.output)
    output_dir.mkdir(exist_ok=True, parents=True)
    output_path = output_dir / f'{create_timestamp()}.mp4'
    writer = cv2.VideoWriter(output_path.as_posix(),
                             cv2.VideoWriter_fourcc(*'H264'), 30,
                             (width, height))

    while True:
        key = cv2.waitKey(1) & 0xff
        if key in QUIT_KEYS:
            break

        ok, frame = cap.read()
        if not ok:
            break

        writer.write(frame)
        cv2.imshow('frame', frame[:, ::-1])

    cap.release()
    writer.release() 
Example #27
Source File: demo.py    From pytorch_mpiigaze with MIT License 5 votes vote down vote up
def _create_capture(self) -> cv2.VideoCapture:
        if self.config.demo.use_camera:
            cap = cv2.VideoCapture(0)
        elif self.config.demo.video_path:
            cap = cv2.VideoCapture(self.config.demo.video_path)
        else:
            raise ValueError
        cap.set(cv2.CAP_PROP_FRAME_WIDTH, self.gaze_estimator.camera.width)
        cap.set(cv2.CAP_PROP_FRAME_HEIGHT, self.gaze_estimator.camera.height)
        return cap 
Example #28
Source File: rtsp2image.py    From lightnet with MIT License 5 votes vote down vote up
def create_capture(args):
    cap = cv.VideoCapture(args.source)
    cap.set(cv.CAP_PROP_FRAME_WIDTH, args.w)
    cap.set(cv.CAP_PROP_FRAME_HEIGHT, args.h)
    if cap is None or not cap.isOpened():
        print('Warning: unable to open video source: ', args.source)
    else:
        print('created capture')
    return cap 
Example #29
Source File: video2video.py    From Photomosaic-generator with MIT License 5 votes vote down vote up
def main(opt):
    cap = cv2.VideoCapture(opt.input)
    width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))
    height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
    if opt.fps == 0:
        fps = int(cap.get(cv2.CAP_PROP_FPS))
    else:
        fps = opt.fps
    out = cv2.VideoWriter(opt.output, cv2.VideoWriter_fourcc(*"XVID"), fps, (width, height))
    images, avg_colors = get_component_images(opt.pool, opt.stride)

    while cap.isOpened():
        flag, frame = cap.read()
        if not flag:
            break
        blank_image = np.zeros((height, width, 3), np.uint8)
        for i, j in product(range(int(width / opt.stride)), range(int(height / opt.stride))):
            partial_input_image = frame[j * opt.stride: (j + 1) * opt.stride,
                                  i * opt.stride: (i + 1) * opt.stride, :]
            partial_avg_color = np.sum(np.sum(partial_input_image, axis=0), axis=0) / (opt.stride ** 2)
            distance_matrix = np.linalg.norm(partial_avg_color - avg_colors, axis=1)
            idx = np.argmin(distance_matrix)
            blank_image[j * opt.stride: (j + 1) * opt.stride, i * opt.stride: (i + 1) * opt.stride, :] = images[idx]
        if opt.overlay_ratio:
            overlay = cv2.resize(frame, (int(width * opt.overlay_ratio), int(height * opt.overlay_ratio)))
            blank_image[height-int(height*opt.overlay_ratio):, width-int(width*opt.overlay_ratio):,:] = overlay
        out.write(blank_image)
    cap.release()
    out.release() 
Example #30
Source File: camera_communicator.py    From SenseAct with BSD 3-Clause "New" or "Revised" License 5 votes vote down vote up
def run(self):
        """Opening the video IO in the child process and invoke parent 'run' """
        self._cap = cv.VideoCapture(self._device_id)

        if not self._cap.isOpened():
            raise IOError("Unable to open camera on device id {}".format(self._device_id))

        self._cap.set(cv.CAP_PROP_FRAME_WIDTH, self._res[0])
        self._cap.set(cv.CAP_PROP_FRAME_HEIGHT, self._res[1])

        # main process loop
        super(CameraCommunicator, self).run()

        # try to close the IO when the process end
        self._cap.release()