def test_overlay_array1(camera, mode):
resolution, framerate = mode
# Draw a cross overlay
w, h = resolution
w = bcm_host.VCOS_ALIGN_UP(w, 32)
h = bcm_host.VCOS_ALIGN_UP(h, 16)
a = np.zeros((h, w, 3), dtype=np.uint8)
a[resolution[1] // 2, :, :] = 0xff
a[:, resolution[0] // 2, :] = 0xff
overlay = camera.add_overlay(a, resolution, alpha=128)
assert len(camera.overlays) == 1
assert camera.overlays[0].alpha == 128
camera.remove_overlay(overlay)
assert not camera.overlays
def __init__(
self,
cam: 'Camera',
contiguous: bool = True,
):
super().__init__()
self._cam = cam
self._contiguous = contiguous
# Initialize reshaping parameters.
# In raw input mode, the sensor sends us data with resolution
# rounded up to nearest multiples of 16 or 32. Find this input,
# which will be used for the initial reshaping of the data.
width, height = cam.resolution
fwidth = bcm_host.VCOS_ALIGN_UP(width, 16)
fheight = bcm_host.VCOS_ALIGN_UP(height, 16)
self._in_shape = (fheight, fwidth, 3)
# Once reshaped, any extraneous rows or columns introduced
# by the rounding up of the frame shape will need to be
# sliced off. Additionally, any unwanted channels will
# need to be removed, so we'll combine the two cropping
# procedures into one.
channels = cam.channels
if channels in ('r', 'g', 'b'):
ch_index = 'rgb'.find(channels)
self._out_shape = (height, width)
else:
ch_index = slice(None)
self._out_shape = (height, width, 3)
if self._in_shape == self._out_shape:
self._out_slice = (slice(None), slice(None), ch_index)
else:
self._out_slice = (slice(height), slice(width), ch_index)
self._n_bytes_in = np.prod(self._in_shape)
self._n_bytes_out = np.prod(self._out_shape)