def testBasic(self):
'''QObject.signalsBlocked() and blockSignals()
The signals aren't blocked by default.
blockSignals returns the previous value'''
obj = QObject()
self.assertTrue(not obj.signalsBlocked())
self.assertTrue(not obj.blockSignals(True))
self.assertTrue(obj.signalsBlocked())
self.assertTrue(obj.blockSignals(False))
blocker = QSignalBlocker(obj)
self.assertTrue(obj.signalsBlocked())
blocker.unblock()
self.assertTrue(not obj.signalsBlocked())
blocker.reblock()
self.assertTrue(obj.signalsBlocked())
del blocker
self.assertTrue(not obj.signalsBlocked())
def update_image(self, cv_img: np.ndarray):
"""
Slot that gets called when a new image is available from the camera
handles the signal :attr:`camera.AbstractCamera.new_image_available`
:param cv_img: the image array from the camera
:type cv_img: np.ndarray, numpy 2D array
.. seealso:: :py:meth:`camera_preview.CameraPreview.update_image`, :attr:`camera.AbstractCamera.new_image_available`
"""
# block image signal to prevent overloading
blocker = QSignalBlocker(self.cam)
if self.cam.is_running:
# evaluate droplet if checkbox checked
eval = self.ui.evalChk.isChecked() or self._oneshot_eval
self._oneshot_eval = False
# display current fps
self.ui.frameInfoLbl.setText('Running | FPS: ' +
str(self.cam.get_framerate()))
# save image frame if recording
if self.ui.record_chk.isChecked():
self.recorder.write_frame(
cv2.cvtColor(cv_img, cv2.COLOR_BGR2RGB))
elif self._oneshot_eval:
# enable evaluate for one frame (eg snapshots)
eval = True
self._oneshot_eval = False
else:
eval = False
# if ROI size changed, cause update of internal variables for new image dimensions
if self.cam._image_size_invalid:
self.ui.camera_prev.invalidate_imagesize()
self.cam._image_size_invalid = False
# update preview image
self.ui.camera_prev.update_image(cv_img, eval)
# display droplet parameters
self.ui.drpltDataLbl.setText(str(self.ui.camera_prev._droplet))
# unblock signals from cam
blocker.unblock()
