Add save() API that takes tvg::Animation as a parameter.
This API uses gif.h to create each animation frame as a gif frame.
Gif creation do not support threads because they must be added sequentially.
Please see example/GifSaver.cpp
ex)
auto animation = tvg::Animation::gen();
auto picture = animation->picture();
picture->load(EXAMPLE_DIR"/walker.json");
auto saver = tvg::Saver::gen();
saver->save(std::move(animation), EXAMPLE_DIR"/test.gif");
saver->sync();
New API:
Result Saver::save(std::unique_ptr<Animation> animation, const std::string& path, uint32_t quality = 100, uint32_t fps = 0);
Issue: https://github.com/thorvg/thorvg/issues/1712
../src/loaders/external_png/tvgPngLoader.cpp(110): warning C4244: '=': conversion from 'float' to 'uint32_t', possible loss of data
../src/loaders/external_png/tvgPngLoader.cpp(111): warning C4244: '=': conversion from 'float' to 'uint32_t', possible loss of data
../src/loaders/external_png/tvgPngLoader.cpp(112): warning C4244: '=': conversion from 'float' to 'uint32_t', possible loss of data
- The TVG binary format now consistently compresses the data.
- Removed redundant internal properties as part of this change.
Please note that this change will break compatibility with the TVG file format from version 1.0 onward.
Issue: https://github.com/thorvg/thorvg/issues/1372
The Animation::frame() method has been modified.
It will now return InsufficientCondition,
if the frame value is the same as the previous one.
In addition to this change, we have also updated its usage accordingly.
This change introduces the CanvasEngine::All type to automatically
initialize the engines available on the current system.
These revisions improve the usability of these APIs.
Addtions:
- enum class CanvasEngine::All
Modifications:
- Result Initializer::init(CanvasEngine engine, uint32_t threads) ->
Result Initializer::init(uint32_t threads, CanvasEngine engine = tvg::CanvasEngine::All)
Get rid of the polymorphism function table,
use the switch directly instead.
We profiled, both binary & performance is better than before.
Tested on a local machine (single thread):
- Lottie: 2ms improved
- Binary: -0.5kb
lottie builder doesn't need to rebuild the layer object
if it has no any animation frame data.
That case, we can cache the layer scene in order to reuse it.
Tested on local machine (single thread):
- Lottie: appx. 2ms enhanced.
- Binary: +204
replace the frame count unit from the int32_t to float
since animations could smoothly interpolate key-frames.
This notificably improve the animation smoothness in Lottie
Beta API changes:
Result Animation::frame(uint32_t no) -> Result Animation::frame(float no)
uint32_t Animation::curFrame() const -> float Animation::curFrame() const
uint32_t Animation::totalFrame() const -> float Animation::totalFrame() const
Unified common logic for scaled image raster operations,
Avoid on-spot pixel computation as possible.
Tested on local machine (single thread)
Lottie: 0.057s -> 0.053s (-0.004s)
Try to minimize the use of sqrt() and arctan() calls
when possible. These calls can be relatively expensive
when accumulated within a single frame.
Also repalce the division with shift operation.
since split cubic function is one of the significant hot-spots
in the data processing, we could earn a noticable enhancement.
Tested on single thread local machine:
Lottie: 0.080 -> 0.052s (-0.028s)
Performance: 0.023 -> 0.022 (-0.001s)
Binary: +34
Streamlining computations with floating-point operations in rotation
thereby improving 'thorvg' speed.
Also use the well-optimized posix math functions instead of
custom math.
Test on my local machine.
Lottie: -0.008s (0.073 -> 0.065)
Performance: -0.0013s (0.0154 -> 0.0141)
Binary: -323
Previously, the builder accumulated the outlines and fills
in one paint to reduce the rendering context.
However, this approach won't work for Lottie
if the resource contains multiple strokes with branched groups.
We should apply the optimization
only when the specified condition is satisfied.
WebGPU is a Render Hardware Interface built on top of the various APIs
provided by the driver/OS depending on your platform.
WebGPU exposes an API for performing operations,
such as rendering and computation, on a Graphics Processing Unit.
WebGPU official documentation: https://www.w3.org/TR/webgpu/
The new engine type introduced: tvg::CanvasEngine::Wg
The new canvas type introduced: tvg::WgCanvas
Example:
$meson setup build -Dengines=wg_beta
`
// init engine webgpu
tvg::Initializer::init(tvg::CanvasEngine::Wg, 0);
// create wg canvas
auto canvasWg = tvg::WgCanvas::gen();
canvas_wg->target(glfwGetWin32Window(window), width, height);
// ...
// terminate engine and window
tvg::Initializer::term(tvg::CanvasEngine::Wg);
`
Still this feature is under the beta
Issue: https://github.com/thorvg/thorvg/issues/1479
