This redistribution of bits to visually perceptible regions of the frame brings about visual improvement. Spatial AQ exploits this and provides more bits to the low texture and flat regions at the expense of high texture regions. The human eye is more sensitive to regions which are flat and have low texture than regions which have lots of detail and texture. Spatial AQ adjusts the QP within a frame based on the spatial characteristics. Both of these AQ modes are enabled by default, and -qp-mode is set to relative-load when -lookahead_depth >= 1. The Alveo U30 card supports two types of AQ: Spatial Adaptive Quantization and Temporal Adaptive Quantization. It exploits the fact that the human eye is more sensitive to certain regions of a frame and redistributes more bits to those regions. The QP for each frame is determined by the rate control, and adaptive quantization (AQ) adjusts QP on top of that for different regions within a frame. This tool improves the visual quality by changing the quantization parameter (QP) within a frame. Using FFmpeg for Video Scaling on Alveo U30.Considerations for Decoding and Encoding 4K Streams.Using FFmpeg for Video Encoding and Decoding on Alveo U30.This filter receives an array of possible audio inputs as well as an array of possible video inputs. Total number of inputs is determined at runtime. This filter has dynamic inputs: last two arguments are lists of audioĪnd video inputs. Likewise, with dynamic inputs: % liquidsoap -h įfmpeg filter: Merge two or more audio streams into a single multi-channel This filter returns a tuple (audio, video) of possible dynamic outputs. Number of outputs is determined at runtime. This filter hasĭynamic outputs: returned value is a tuple of audio and video outputs. Here’s an example for dynamic outputs: % liquidsoap -h įfmpeg filter: Pass on the audio input to N audio outputs. Typically, splits a video stream into multiple streams and merges multiple video streams into a single one.įor these filters, the operators’ signature is a little different. Filters with dynamic inputs or outputsįilters with dynamic inputs or outputs can have multiple inputs or outputs, decided at run-time. provides a more straight forward API to filters. The API is intended for advanced use if you want to use filter commands. Then, we apply the expected input to the filter and return the pair (s, set_volume) of source and function. The filter instance has a process_command, which we use to create the set_volume function. Here’s an example:ĭef dynamic_volume(s) = def mkfilter(graph) = filter = (graph) def set_volume(v) = ignore( filter.process_command( "volume", "#")) end s = (graph, s) t_input(s) s = filter.output s = (graph, s) (s, set_volume) end (mkfilter) end let (s, set_volume) = dynamic_volume(s)įirst, we instantiate a volume filter via. Conversely, sources can be created from them using and .įilters are configured within the closure of a function. * (unlabeled) : (default: None)įilters input and output are abstract values of type and. For instance: Ffmpeg filter: Add echoing to the audio. If enabled, the filters should appear as operators, prefixed with ffmpeg.filter.
They are enabled in liquidsoap when compiled with the optional ffmpeg-avfilter. FFmpeg filters provide audio and video filters that can be used to transform content using the ffmpeg library.