BaseTransform#

class BaseTransform(**properties: Any)#

Superclasses: Element, Object, InitiallyUnowned, Object

This base class is for filter elements that process data. Elements that are suitable for implementation using BaseTransform are ones where the size and caps of the output is known entirely from the input caps and buffer sizes. These include elements that directly transform one buffer into another, modify the contents of a buffer in-place, as well as elements that collate multiple input buffers into one output buffer, or that expand one input buffer into multiple output buffers. See below for more concrete use cases.

It provides for:

  • one sinkpad and one srcpad

  • Possible formats on sink and source pad implemented with custom transform_caps function. By default uses same format on sink and source.

  • Handles state changes

  • Does flushing

  • Push mode

  • Pull mode if the sub-class transform can operate on arbitrary data

Use Cases#

Passthrough mode#

  • Element has no interest in modifying the buffer. It may want to inspect it,

    in which case the element should have a transform_ip function. If there is no transform_ip function in passthrough mode, the buffer is pushed intact.

  • The GstBaseTransformClass.passthrough_on_same_caps variable

    will automatically set/unset passthrough based on whether the element negotiates the same caps on both pads.

  • GstBaseTransformClass.passthrough_on_same_caps on an element that

    doesn’t implement a transform_caps function is useful for elements that only inspect data (such as level)

  • Example elements

  • Level

  • Videoscale, audioconvert, videoconvert, audioresample in certain modes.

Modifications in-place - input buffer and output buffer are the same thing.#

  • The element must implement a transform_ip function.

  • Output buffer size must <= input buffer size

  • If the always_in_place flag is set, non-writable buffers will be copied and passed to the transform_ip function, otherwise a new buffer will be created and the transform function called.

  • Incoming writable buffers will be passed to the transform_ip function immediately.

  • only implementing transform_ip and not transform implies always_in_place = True

  • Example elements:

  • Volume

  • Audioconvert in certain modes (signed/unsigned conversion)

  • videoconvert in certain modes (endianness swapping)

Modifications only to the caps/metadata of a buffer#

  • The element does not require writable data, but non-writable buffers should be subbuffered so that the meta-information can be replaced.

  • Elements wishing to operate in this mode should replace the prepare_output_buffer method to create subbuffers of the input buffer and set always_in_place to True

  • Example elements

  • Capsfilter when setting caps on outgoing buffers that have

    none.

  • identity when it is going to re-timestamp buffers by

    datarate.

Normal mode#

  • always_in_place flag is not set, or there is no transform_ip function

  • Element will receive an input buffer and output buffer to operate on.

  • Output buffer is allocated by calling the prepare_output_buffer function.

  • Example elements:- Videoscale, videoconvert, audioconvert when doing

scaling/conversions

Special output buffer allocations#

  • Elements which need to do special allocation of their output buffers

    beyond allocating output buffers via the negotiated allocator or buffer pool should implement the prepare_output_buffer method.

  • Example elements:

  • efence

Sub-class settable flags on GstBaseTransform#

  • passthrough

  • Implies that in the current configuration, the sub-class is not interested in modifying the buffers.

  • Elements which are always in passthrough mode whenever the same caps has been negotiated on both pads can set the class variable passthrough_on_same_caps to have this behaviour automatically.

  • always_in_place

  • Determines whether a non-writable buffer will be copied before passing

    to the transform_ip function.

  • Implied True if no transform function is implemented.

  • Implied False if ONLY transform function is implemented.

Methods#

class BaseTransform
do_accept_caps(self, direction: PadDirection, caps: Caps) → bool#
Parameters:

  • direction

  • caps

do_before_transform(self, buffer: Buffer) → None#
Parameters:

buffer

do_decide_allocation(self, query: Query) → bool#
Parameters:

query

do_filter_meta(self, query: Query, api: GType, params: Structure) → bool#
Parameters:

  • query

  • api

  • params

do_fixate_caps(self, direction: PadDirection, caps: Caps, othercaps: Caps) → Caps#
Parameters:

  • direction

  • caps

  • othercaps

do_generate_output(self) → Tuple[FlowReturn, Buffer]#
do_get_unit_size(self, caps: Caps) → Tuple[bool, int]#
Parameters:

caps

do_prepare_output_buffer(self, input: Buffer) → Tuple[FlowReturn, Buffer]#
Parameters:

input

do_propose_allocation(self, decide_query: Query, query: Query) → bool#
Parameters:

  • decide_query

  • query

do_query(self, direction: PadDirection, query: Query) → bool#
Parameters:

  • direction

  • query

do_set_caps(self, incaps: Caps, outcaps: Caps) → bool#
Parameters:

  • incaps

  • outcaps

do_sink_event(self, event: Event) → bool#
Parameters:

event

do_src_event(self, event: Event) → bool#
Parameters:

event

do_start(self) → bool#
do_stop(self) → bool#
do_submit_input_buffer(self, is_discont: bool, input: Buffer) → FlowReturn#
Parameters:

  • is_discont

  • input

do_transform(self, inbuf: Buffer, outbuf: Buffer) → FlowReturn#
Parameters:

  • inbuf

  • outbuf

do_transform_caps(self, direction: PadDirection, caps: Caps, filter: Caps) → Caps#
Parameters:

  • direction

  • caps

  • filter

do_transform_ip(self, buf: Buffer) → FlowReturn#
Parameters:

buf

do_transform_meta(self, outbuf: Buffer, meta: Meta, inbuf: Buffer) → bool#
Parameters:

  • outbuf

  • meta

  • inbuf

do_transform_size(self, direction: PadDirection, caps: Caps, size: int, othercaps: Caps) → Tuple[bool, int]#
Parameters:

  • direction

  • caps

  • size

  • othercaps

get_allocator() → Tuple[Allocator | None, AllocationParams]#

Lets BaseTransform sub-classes know the memory allocator used by the base class and its params.

Unref the allocator after use.

get_buffer_pool() → BufferPool | None#
is_in_place() → bool#

See if trans is configured as a in_place transform.

is_passthrough() → bool#

See if trans is configured as a passthrough transform.

is_qos_enabled() → bool#

Queries if the transform will handle QoS.

reconfigure() → bool#

Negotiates src pad caps with downstream elements if the source pad is marked as needing reconfiguring. Unmarks GST_PAD_FLAG_NEED_RECONFIGURE in any case. But marks it again if negotiation fails.

Do not call this in the GstBaseTransformClass::transform or GstBaseTransformClass::transform_ip vmethod. Call this in GstBaseTransformClass::submit_input_buffer, GstBaseTransformClass::prepare_output_buffer or in GstBaseTransformClass::generate_output before any output buffer is allocated.

It will be default be called when handling an ALLOCATION query or at the very beginning of the default GstBaseTransformClass::submit_input_buffer implementation.

Added in version 1.18.

reconfigure_sink() → None#

Instructs trans to request renegotiation upstream. This function is typically called after properties on the transform were set that influence the input format.

reconfigure_src() → None#

Instructs trans to renegotiate a new downstream transform on the next buffer. This function is typically called after properties on the transform were set that influence the output format.

set_gap_aware(gap_aware: bool) → None#

If gap_aware is False (the default), output buffers will have the %GST_BUFFER_FLAG_GAP flag unset.

If set to True, the element must handle output buffers with this flag set correctly, i.e. it can assume that the buffer contains neutral data but must unset the flag if the output is no neutral data.

MT safe.

Parameters:

gap_aware – New state

set_in_place(in_place: bool) → None#

Determines whether a non-writable buffer will be copied before passing to the transform_ip function.

  • Always True if no transform function is implemented.

  • Always False if ONLY transform function is implemented.

MT safe.

Parameters:

in_place – Boolean value indicating that we would like to operate on in_place buffers.

set_passthrough(passthrough: bool) → None#

Set passthrough mode for this filter by default. This is mostly useful for filters that do not care about negotiation.

Always True for filters which don’t implement either a transform or transform_ip or generate_output method.

MT safe.

Parameters:

passthrough – boolean indicating passthrough mode.

set_prefer_passthrough(prefer_passthrough: bool) → None#

If prefer_passthrough is True (the default), trans will check and prefer passthrough caps from the list of caps returned by the transform_caps vmethod.

If set to False, the element must order the caps returned from the transform_caps function in such a way that the preferred format is first in the list. This can be interesting for transforms that can do passthrough transforms but prefer to do something else, like a capsfilter.

MT safe.

Added in version 1.0.1.

Parameters:

prefer_passthrough – New state

set_qos_enabled(enabled: bool) → None#

Enable or disable QoS handling in the transform.

MT safe.

Parameters:

enabled – new state

update_qos(proportion: float, diff: int, timestamp: int) → None#

Set the QoS parameters in the transform. This function is called internally when a QOS event is received but subclasses can provide custom information when needed.

MT safe.

Parameters:

  • proportion – the proportion

  • diff – the diff against the clock

  • timestamp – the timestamp of the buffer generating the QoS expressed in running_time.

update_src_caps(updated_caps: Caps) → bool#

Updates the srcpad caps and sends the caps downstream. This function can be used by subclasses when they have already negotiated their caps but found a change in them (or computed new information). This way, they can notify downstream about that change without losing any buffer.

Added in version 1.6.

Parameters:

updated_caps – An updated version of the srcpad caps to be pushed downstream

Properties#

class BaseTransform
props.qos: bool#

The type of the None singleton.

Virtual Methods#

class BaseTransform
do_accept_caps(direction: PadDirection, caps: Caps) → bool#

The type of the None singleton.

Parameters:

  • direction

  • caps

do_before_transform(buffer: Buffer) → None#

The type of the None singleton.

Parameters:

buffer

do_copy_metadata(input: Buffer, outbuf: Buffer) → bool#

The type of the None singleton.

Parameters:

  • input

  • outbuf

do_decide_allocation(query: Query) → bool#

The type of the None singleton.

Parameters:

query

do_filter_meta(query: Query, api: GType, params: Structure) → bool#

The type of the None singleton.

Parameters:

  • query

  • api

  • params

do_fixate_caps(direction: PadDirection, caps: Caps, othercaps: Caps) → Caps#

The type of the None singleton.

Parameters:

  • direction

  • caps

  • othercaps

do_generate_output() → Tuple[FlowReturn, Buffer]#

The type of the None singleton.

do_get_unit_size(caps: Caps) → Tuple[bool, int]#

The type of the None singleton.

Parameters:

caps

do_prepare_output_buffer(input: Buffer) → Tuple[FlowReturn, Buffer]#

The type of the None singleton.

Parameters:

input

do_propose_allocation(decide_query: Query, query: Query) → bool#

The type of the None singleton.

Parameters:

  • decide_query

  • query

do_query(direction: PadDirection, query: Query) → bool#
Optional.

Handle a requested query. Subclasses that implement this must chain up to the parent if they didn’t handle the query

Parameters:

  • direction

  • query

do_set_caps(incaps: Caps, outcaps: Caps) → bool#

The type of the None singleton.

Parameters:

  • incaps

  • outcaps

do_sink_event(event: Event) → bool#

The type of the None singleton.

Parameters:

event

do_src_event(event: Event) → bool#

The type of the None singleton.

Parameters:

event

do_start() → bool#

The type of the None singleton.

do_stop() → bool#

The type of the None singleton.

do_submit_input_buffer(is_discont: bool, input: Buffer) → FlowReturn#

The type of the None singleton.

Parameters:

  • is_discont

  • input

do_transform(inbuf: Buffer, outbuf: Buffer) → FlowReturn#

The type of the None singleton.

Parameters:

  • inbuf

  • outbuf

do_transform_caps(direction: PadDirection, caps: Caps, filter: Caps) → Caps#

The type of the None singleton.

Parameters:

  • direction

  • caps

  • filter

do_transform_ip(buf: Buffer) → FlowReturn#

The type of the None singleton.

Parameters:

buf

do_transform_meta(outbuf: Buffer, meta: Meta, inbuf: Buffer) → bool#

The type of the None singleton.

Parameters:

  • outbuf

  • meta

  • inbuf

do_transform_size(direction: PadDirection, caps: Caps, size: int, othercaps: Caps) → Tuple[bool, int]#

The type of the None singleton.

Parameters:

  • direction

  • caps

  • size

  • othercaps

Fields#

class BaseTransform
element#
have_segment#
priv#
queued_buf#
segment#
sinkpad#
srcpad#
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