buffers and textures. ● Swapchain management. ● Synchronization. ● Command list / buffer recording. ○ Ownership transfers. ○ Memory barriers, image layout transitions. ● Compute dispatches.

External Internal • iPad • Rotation • Call & Recording Bar • Screen Size Layout Blind Spot External Internal • iPad • Rotation • Call & Recording Bar • Screen Size • Content Change • Internationalization Multimedia Multimedia • Live Video Filter • Video background playback Live Image Filter • Capture in separated threads • Processing by Core Image • Preview on GLKView Video Flow Delegate Core Image to User AVCaptureSession 420YpCbCr AVCaptureVideoDataOutput Processing Thread Video Background Playback Video Background Delegate Core Image Filter CIContext GLKView Display to User AVPlayerItem

ffmpeg -i video_no_subtitle.mp4 -i subtitle.srt -codec copy -map 0 获取 6 video_with_soft_subtitle.mp4 ass字幕 硬字幕 内嵌字幕=嵌⼊ass字幕到视频中 ffmpeg -i input_video.mp4 -vf ass=subtitle.ass input_video_with_ass_subtitle input_video_with_ass_subtitle.mp4 从视频中提取出字幕 ffmpeg -i video_with_soft_subtitle.mp4 -map 0:s:0 extracted_subtitle.srt 字幕类型转换 srt转换为ass ffmpeg -i subtitle.srt subtitle.ass 另外还有： ffmpeg 被其他⼯具调⽤：⽤于解析和操作⾳视频 Python的⾳频处理库： ffserver：搭建流媒体服务器 -》⽤来⽀持其他端去播放⾳视频 ffplay -f lavfi -i ffplay -f lavfi -i "movie=course_59485_video_no "movie=course_59485_video_no 获取 8 crifan.com，使⽤署名4.0国际(CC BY 4.0)协议发布 all right reserved， powered by Gitbook最后更新：

ffmpeg -i video_no_subtitle.mp4 -i subtitle.srt -codec copy -map 0 video_with_soft_subtitle.mp4 ass字幕 硬字幕 内嵌字幕=嵌入ass字幕到视频中 ffmpeg -i input_video.mp4 -vf ass=subtitle.ass input_video_with_ass_subtitle subtitle.mp4 从视频中提取出字幕 ffmpeg -i video_with_soft_subtitle.mp4 -map 0:s:0 extracted_subtitle.srt 字幕类型转换 srt转换为ass ffmpeg -i subtitle.srt subtitle.ass 另外还有： ffmpeg 被其他工具调用：用于解析和操作音视频 Python的音频处理库： 播放视频并显示水印位置：便于发现水印位置是否准确 ffplay -f lavfi -i ffplay -f lavfi -i "movie=course_59485_video_normalWatermark.m "movie=course_59485_video_normalWatermark.m p4,delogo=x=490:y=30:w=130:h=50:show=1" p4,delogo=x=490:

look at an example: Let’s pretend we have an application with lot of different tasks: some process video, others process images, and some gather collective intelligence about its users. Some of these tasks stock.nasdaq. We create three queues, video, image and lowpri that binds to the tasks exchange. For the queues we use the following binding keys: video: video.# image: image.# lowpri: misc.# Now we making the workers listen to different queues: >>> add.apply_async(args=[filename], ... routing_key="video.compress") >>> add.apply_async(args=[filename, 360], ... routing_key="image.rotate") >>> add.ap

look at an example: Let’s pretend we have an application with lot of different tasks: some process video, others process images, and some gather collective intelligence about its users. Some of these tasks stock.nasdaq. We create three queues, video, image and lowpri that binds to the tasks exchange. For the queues we use the following binding keys: video: video.# image: image.# lowpri: misc.# Now we different queues: >>> add.apply_async(args=[filename], ... routing_key="video.compress") >>> add.apply_async(args=[filename, 360], ... routing_key="image

look at an example: Let’s pretend we have an application with lot of different tasks: some process video, others process images, and some gather collective intelligence about its users. Some of these tasks stock.nasdaq. We create three queues, video, image and lowpri that binds to the tasks exchange. For the queues we use the following binding keys: video: video.# image: image.# lowpri: misc.# Now we making the workers listen to different queues: >>> add.apply_async(args=[filename], ... routing_key="video.compress") >>> add.apply_async(args=[filename, 360], ... routing_key="image.rotate") >>> add.ap

look at an example: Let’s pretend we have an application with lot of different tasks: some process video, others process images, and some gather collective intelligence about its users. Some of these tasks stock.nasdaq. We create three queues, video, image and lowpri that binds to the tasks exchange. For the queues we use the following binding keys: video: video.# image: image.# lowpri: misc.# Now we making the workers listen to different queues: >>> add.apply_async(args=[filename], ... routing_key="video.compress") >>> add.apply_async(args=[filename, 360], ... routing_key="image.rotate") >>> add.ap

look at an example: Let’s pretend we have an application with lot of different tasks: some process video, others process images, and some gather collective intelligence about its users. Some of these tasks stock.nasdaq. We create three queues, video, image and lowpri that binds to the tasks exchange. For the queues we use the following binding keys: video: video.# image: image.# lowpri: misc.# Now we different queues: >>> add.apply_async(args=[filename], ... routing_key="video.compress") >>> add.apply_async(args=[filename, 360], ... routing_key="image

ffmpeg -i video_no_subtitle.mp4 -i subtitle.srt -codec copy -map 0 video_with_soft_subtitle.mp4 ass字幕 硬字幕 内嵌字幕=嵌入ass字幕到视频中 ffmpeg -i input_video.mp4 -vf ass=subtitle.ass input_video_with_ass_subtitle _subtitle.mp4 从视频中提取出字幕 ffmpeg -i video_with_soft_subtitle.mp4 -map 0:s:0 extracted_subtitle.srt 字幕类型转换 srt转换为ass ffmpeg -i subtitle.srt subtitle.ass 另外还有： ffmpeg 被其他工具调用：用于解析和操作音视频 Python的音频处理库： ffplay：播放音视频及其他一些辅助功能 辅助功能举例： 播放视频并显示水印位置：便于发现水印位置是否准确 ffplay -f lavfi - i "movie=course_59485_video_normalWatermar k.mp4,delogo=x=490:y=30:w=130:h=50:show=1" 播放效果： -》方便看出要去除的水印的位置有偏差 可以后续再调整参数值，让去除水印的区域更加准确