def do_transform_ip(self, buf):
try:
with buf.map(Gst.MapFlags.READ | Gst.MapFlags.WRITE) as info:
# Create a NumPy ndarray from the memoryview and modify it in place.
A = np.ndarray(shape=(self.height, self.width),
dtype=np.uint8,
buffer=info.data)
Gst.trace("A=%s" % (str(A)))
A[:] = A * 0.1
Gst.trace("A=%s" % (str(A)))
return Gst.FlowReturn.OK
except Gst.MapError as e:
Gst.error("Mapping error: %s" % e)
return Gst.FlowReturn.ERROR
def do_transform_ip(self, buf):
try:
with buf.map(Gst.MapFlags.READ | Gst.MapFlags.WRITE) as info:
Gst.trace('info=%s, size=%d' % (str(info), info.size))
# Create a NumPy ndarray from the memoryview and modify it in place.
buf_np = np.ndarray(shape=(self.height, self.width),
dtype=np.uint8,
buffer=info.data)
Gst.trace("buf_np=%s" % (str(buf_np)))
# Create tensors.
t1 = tf.constant(buf_np)
Gst.trace("t1=%s" % (str(t1)))
t2 = t1 / 4
Gst.trace("t2=%s" % (str(t2)))
# Copy tensor to overwrite input/output buffer.
buf_np[:] = t2
return Gst.FlowReturn.OK
except Gst.MapError as e:
Gst.error("Mapping error: %s" % e)
return Gst.FlowReturn.ERROR
