不用模型，把字幕下载好，做分词索引更简单的就是 tire 树，然后根据字幕时间轴和关键帧做好映射

github action ，cargo-zigbuild ，cargo-cross ，clang 交叉编译

有 docker kvm 的，你有硬件可以测试吗，同感兴趣能不能跑平板微信 https://github.com/budtmo/docker-android

用 libmpv 启用 hwdec=auto ，或者使用 ffmpeg 硬件加速+libplacebo ，播放器非常复杂，要颜色映射，hdr/sdr ，还要向上向下缩放，还有同步策略和丢帧策略，做不好不是卡就是画面偏色或者资源占用高

@bler docker+qemu+kvm 装 windows, macOS 。https://github.com/dockur/windows ，https://github.com/dockur/macos

我跑 visual studio 2022 和 rust 自动化 runner ，用来编译代码，tiny10/tiny11 没有问题，是在 linux 下 qemu 跑的，不是物理机 https://github.com/dockur/windows

建议用 https://github.com/rust-cross/cargo-zigbuild 或者 https://github.com/cross-rs/cross 静态链接 musl ，不要静态链接 glibc ，可以动态链接 2012 年的 glibc2.17 ，就可以在主流相同指令集的 linux 上跑起来，比如 cargo zigbuild --target aarch64-unknown-linux-gnu.2.17

不是 DLNA ，AirPlay 镜像是屏幕声音录制，编码，加密，传输，显示端接收、解密，解码渲染，加密和编码有硬件加速，具体耗电量还得结合码率、画质看

楼上用的哪里的国补啊，我看北京的用不了啊

@bli22ard 实现在这里，就是很简单的 Arc 和 clone
```rust
/// Owned read half of a [`TcpStream`], created by [`into_split`].
///
/// Reading from an `OwnedReadHalf` is usually done using the convenience methods found
/// on the [`AsyncReadExt`] trait.
///
/// [`TcpStream`]: TcpStream
/// [`into_split`]: TcpStream::into_split()
/// [`AsyncReadExt`]: trait@crate::io::AsyncReadExt
#[derive(Debug)]
pub struct OwnedReadHalf {
inner: Arc<TcpStream>,
}

/// Owned write half of a [`TcpStream`], created by [`into_split`].
///
/// Note that in the [`AsyncWrite`] implementation of this type, [`poll_shutdown`] will
/// shut down the TCP stream in the write direction. Dropping the write half
/// will also shut down the write half of the TCP stream.
///
/// Writing to an `OwnedWriteHalf` is usually done using the convenience methods found
/// on the [`AsyncWriteExt`] trait.
///
/// [`TcpStream`]: TcpStream
/// [`into_split`]: TcpStream::into_split()
/// [`AsyncWrite`]: trait@crate::io::AsyncWrite
/// [`poll_shutdown`]: fn@crate::io::AsyncWrite::poll_shutdown
/// [`AsyncWriteExt`]: trait@crate::io::AsyncWriteExt
#[derive(Debug)]
pub struct OwnedWriteHalf {
inner: Arc<TcpStream>,
shutdown_on_drop: bool,
}

pub(crate) fn split_owned(stream: TcpStream) -> (OwnedReadHalf, OwnedWriteHalf) {
let arc = Arc::new(stream);
let read = OwnedReadHalf {
inner: Arc::clone(&arc),
};
let write = OwnedWriteHalf {
inner: arc,
shutdown_on_drop: true,
};
(read, write)
}
```

使用 into_split 可以分离读写
https://docs.rs/tokio/latest/tokio/net/struct.TcpStream.html#method.into_split
可以参考这里
https://github.com/FutureOrientedGB/gbt_sip_server/blob/09628a99b89038b65257ad3ea3fc29c45337a01a/src/sip/server.rs#L123

你点击控件成功之后，给 A 窗口发送最小化消息 SendMessage(HWND, SC_MINIMIZE)就可以了吧

@capric 6, 8, 10, A4 的相纸都支持，调整进纸仓的卡扣就行

我家用惠普 4160L 喷墨自动双面，打 7 寸彩色照片或者 1 寸证件都很不能，咸鱼上收的，400-500 块，连供墨仓，墨水买兼容的，很便宜

@clevertension 你这个 rtmp 是实时流吗，如果是实时流，一般只有 25/30/60 几种，不会有 7600 那么高，你统计出来 7600 fps ，应该绝大多数 frame 都是 None 。另外可以用 multiprocessing 和 queue 分发。

@capric 还需要重新编译 opencv ，https://blog.csdn.net/jiexijihe945/article/details/125084488