Esempio n. 1
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    def _init_camera(self, orig=True):
        """
        Opens the video capture
        :return:
        True if the camera opens, or it isn't being used
        False if attempting to open the camera fails
        """

        if orig:
            log.info('Using OpenCV version {}.{}'.format(
                cv2.getVersionMajor(), cv2.getVersionMinor()))

            if self.camera_id is not None:
                log.info('Using camera {}'.format(self.camera_id))
                self.camera_instance = cv2.VideoCapture(self.camera_id)

                x, y, fps = self.resolution
                self.camera_instance.set(cv2.CAP_PROP_FRAME_WIDTH, x)
                self.camera_instance.set(cv2.CAP_PROP_FRAME_HEIGHT, y)
                self.camera_instance.set(cv2.CAP_PROP_FPS, fps)

                if not self.camera_instance.isOpened():
                    log.error('Failed to open camera')
                    return False

                self.is_open = True
                x = self.camera_instance.get(cv2.CAP_PROP_FRAME_WIDTH)
                y = self.camera_instance.get(cv2.CAP_PROP_FRAME_HEIGHT)
                fps = self.camera_instance.get(cv2.CAP_PROP_FPS)
                log.warning('x: {}, y: {}, fps: {}'.format(x, y, fps))

            return True
Esempio n. 2
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def version():
    return "Pandas Version: {}" \
           "Numpy Version: {}" \
           "Opencv Version: {}" \
           "Keras Version: {}" \
           "Matplotlib Version: {}" \
           "Scipy Version: {}" \
           "Seaborn Version: {}" \
           "Sklearn Version: {}" \
           "Tensorflow Version: {}".format(pandas.__version__,
                                           numpy.__version__,
                                           cv2.getVersionMinor(),
                                           keras.__version__,
                                           matplotlib.__version__,
                                           scipy.__version__,
                                           seaborn.__version__,
                                           sklearn.__version__,
                                           tensorflow.__version__)
Esempio n. 3
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def check_build_info():
    success = True

    print("OpenCV Version: {}".format(cv2.__version__))
    if (cv2.getVersionMajor() != CURRENT_OPENCV_BUILD_VERSION[0]) and (
            cv2.getVersionMinor() != CURRENT_OPENCV_BUILD_VERSION[1]) and (
            cv2.getVersionRevision() != CURRENT_OPENCV_BUILD_VERSION[2]):
        print("ERROR: OpenCV version is different than the expected.")
        success = False

    print("Available CPUs: ", cv2.getNumberOfCPUs())
    print("Available threads: ", cv2.getNumThreads())
    if cv2.getNumThreads() < cv2.getNumberOfCPUs():
        print("ERROR: TBB is not enabled.")
        success = False

    cv2.CPU_NEON = 100  # Value taken from OpenCV doc. CPU labels don't work correctly in Python
    print("Cpu NEON support: ", cv2.checkHardwareSupport(cv2.CPU_NEON))
    if not cv2.checkHardwareSupport(cv2.CPU_NEON):
        print("ERROR: NEON is not enabled.")
        success = False

    return success
Esempio n. 4
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import cv2
import sys


if __name__ == '__main__':
    # Set up tracker.
    # Instead of MIL, you can also use
    tracker_types = ['BOOSTING', 'MIL', 'KCF', 'TLD', 'MEDIANFLOW', 'GOTURN', 'MOSSE', 'CSRT']
    tracker_type = tracker_types[2]
    if int(cv2.getVersionMinor()) < 3:
        tracker = cv2.Tracker_create(tracker_type)
    else:
        if tracker_type == 'BOOSTING':
            tracker = cv2.TrackerBoosting_create()
        if tracker_type == 'MIL':
            tracker = cv2.TrackerMIL_create()
        if tracker_type == 'KCF':
            tracker = cv2.TrackerKCF_create()
        if tracker_type == 'TLD':
            tracker = cv2.TrackerTLD_create()
        if tracker_type == 'MEDIANFLOW':
            tracker = cv2.TrackerMedianFlow_create()
        if tracker_type == 'GOTURN':
            tracker = cv2.TrackerGOTURN_create()
        if tracker_type == 'MOSSE':
            tracker = cv2.TrackerMOSSE_create()
        if tracker_type == "CSRT":
            tracker = cv2.TrackerCSRT_create()
    # Read video
    video = cv2.VideoCapture("videos/chaplin.mp4")
    # Exit if video not opened.