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SPDX-License-Identifier: GPL-2.0 + +.. include:: <isonum.txt> + +=============================================================== +Intel Image Processing Unit 3 (IPU3) Imaging Unit (ImgU) driver +=============================================================== + +Copyright |copy| 2018 Intel Corporation + +Introduction +============ + +This file documents the Intel IPU3 (3rd generation Image Processing Unit) +Imaging Unit drivers located under drivers/media/pci/intel/ipu3 (CIO2) as well +as under drivers/staging/media/ipu3 (ImgU). + +The Intel IPU3 found in certain Kaby Lake (as well as certain Sky Lake) +platforms (U/Y processor lines) is made up of two parts namely the Imaging Unit +(ImgU) and the CIO2 device (MIPI CSI2 receiver). + +The CIO2 device receives the raw Bayer data from the sensors and outputs the +frames in a format that is specific to the IPU3 (for consumption by the IPU3 +ImgU). The CIO2 driver is available as drivers/media/pci/intel/ipu3/ipu3-cio2* +and is enabled through the CONFIG_VIDEO_IPU3_CIO2 config option. + +The Imaging Unit (ImgU) is responsible for processing images captured +by the IPU3 CIO2 device. The ImgU driver sources can be found under +drivers/staging/media/ipu3 directory. The driver is enabled through the +CONFIG_VIDEO_IPU3_IMGU config option. + +The two driver modules are named ipu3_csi2 and ipu3_imgu, respectively. + +The drivers has been tested on Kaby Lake platforms (U/Y processor lines). + +Both of the drivers implement V4L2, Media Controller and V4L2 sub-device +interfaces. The IPU3 CIO2 driver supports camera sensors connected to the CIO2 +MIPI CSI-2 interfaces through V4L2 sub-device sensor drivers. + +CIO2 +==== + +The CIO2 is represented as a single V4L2 subdev, which provides a V4L2 subdev +interface to the user space. There is a video node for each CSI-2 receiver, +with a single media controller interface for the entire device. + +The CIO2 contains four independent capture channel, each with its own MIPI CSI-2 +receiver and DMA engine. Each channel is modelled as a V4L2 sub-device exposed +to userspace as a V4L2 sub-device node and has two pads: + +.. tabularcolumns:: |p{0.8cm}|p{4.0cm}|p{4.0cm}| + +.. flat-table:: + + * - pad + - direction + - purpose + + * - 0 + - sink + - MIPI CSI-2 input, connected to the sensor subdev + + * - 1 + - source + - Raw video capture, connected to the V4L2 video interface + +The V4L2 video interfaces model the DMA engines. They are exposed to userspace +as V4L2 video device nodes. + +Capturing frames in raw Bayer format +------------------------------------ + +CIO2 MIPI CSI2 receiver is used to capture frames (in packed raw Bayer format) +from the raw sensors connected to the CSI2 ports. The captured frames are used +as input to the ImgU driver. + +Image processing using IPU3 ImgU requires tools such as raw2pnm [#f1]_, and +yavta [#f2]_ due to the following unique requirements and / or features specific +to IPU3. + +-- The IPU3 CSI2 receiver outputs the captured frames from the sensor in packed +raw Bayer format that is specific to IPU3. + +-- Multiple video nodes have to be operated simultaneously. + +Let us take the example of ov5670 sensor connected to CSI2 port 0, for a +2592x1944 image capture. + +Using the media contorller APIs, the ov5670 sensor is configured to send +frames in packed raw Bayer format to IPU3 CSI2 receiver. + +# This example assumes /dev/media0 as the CIO2 media device + +export MDEV=/dev/media0 + +# and that ov5670 sensor is connected to i2c bus 10 with address 0x36 + +export SDEV=$(media-ctl -d $MDEV -e "ov5670 10-0036") + +# Establish the link for the media devices using media-ctl [#f3]_ +media-ctl -d $MDEV -l "ov5670:0 -> ipu3-csi2 0:0[1]" + +# Set the format for the media devices +media-ctl -d $MDEV -V "ov5670:0 [fmt:SGRBG10/2592x1944]" + +media-ctl -d $MDEV -V "ipu3-csi2 0:0 [fmt:SGRBG10/2592x1944]" + +media-ctl -d $MDEV -V "ipu3-csi2 0:1 [fmt:SGRBG10/2592x1944]" + +Once the media pipeline is configured, desired sensor specific settings +(such as exposure and gain settings) can be set, using the yavta tool. + +e.g + +yavta -w 0x009e0903 444 $SDEV + +yavta -w 0x009e0913 1024 $SDEV + +yavta -w 0x009e0911 2046 $SDEV + +Once the desired sensor settings are set, frame captures can be done as below. + +e.g + +yavta --data-prefix -u -c10 -n5 -I -s2592x1944 --file=/tmp/frame-#.bin \ + -f IPU3_SGRBG10 $(media-ctl -d $MDEV -e "ipu3-cio2 0") + +With the above command, 10 frames are captured at 2592x1944 resolution, with +sGRBG10 format and output as IPU3_SGRBG10 format. + +The captured frames are available as /tmp/frame-#.bin files. + +ImgU +==== + +The ImgU is represented as two V4L2 subdevs, each of which provides a V4L2 +subdev interface to the user space. + +Each V4L2 subdev represents a pipe, which can support a maximum of 2 streams. +This helps to support advanced camera features like Continuous View Finder (CVF) +and Snapshot During Video(SDV). + +The ImgU contains two independent pipes, each modelled as a V4L2 sub-device +exposed to userspace as a V4L2 sub-device node. + +Each pipe has two sink pads and three source pads for the following purpose: + +.. tabularcolumns:: |p{0.8cm}|p{4.0cm}|p{4.0cm}| + +.. flat-table:: + + * - pad + - direction + - purpose + + * - 0 + - sink + - Input raw video stream + + * - 1 + - sink + - Processing parameters + + * - 2 + - source + - Output processed video stream + + * - 3 + - source + - Output viewfinder video stream + + * - 4 + - source + - 3A statistics + +Each pad is connected to a corresponding V4L2 video interface, exposed to +userspace as a V4L2 video device node. + +Device operation +---------------- + +With ImgU, once the input video node ("ipu3-imgu 0/1":0, in +<entity>:<pad-number> format) is queued with buffer (in packed raw Bayer +format), ImgU starts processing the buffer and produces the video output in YUV +format and statistics output on respective output nodes. The driver is expected +to have buffers ready for all of parameter, output and statistics nodes, when +input video node is queued with buffer. + +At a minimum, all of input, main output, 3A statistics and viewfinder +video nodes should be enabled for IPU3 to start image processing. + +Each ImgU V4L2 subdev has the following set of video nodes. + +input, output and viewfinder video nodes +---------------------------------------- + +The frames (in packed raw Bayer format specific to the IPU3) received by the +input video node is processed by the IPU3 Imaging Unit and are output to 2 video +nodes, with each targeting a different purpose (main output and viewfinder +output). + +Details onand the Bayer format specific to the IPU3 can be found in +:ref:`v4l2-pix-fmt-ipu3-sbggr10`. + +The driver supports V4L2 Video Capture Interface as defined at :ref:`devices`. + +Only the multi-planar API is supported. More details can be found at +:ref:`planar-apis`. + +Parameters video node +--------------------- + +The parameters video node receives the ImgU algorithm parameters that are used +to configure how the ImgU algorithms process the image. + +Details on processing parameters specific to the IPU3 can be found in +:ref:`v4l2-meta-fmt-params`. + +3A statistics video node +------------------------ + +3A statistics video node is used by the ImgU driver to output the 3A (auto +focus, auto exposure and auto white balance) statistics for the frames that are +being processed by the ImgU to user space applications. User space applications +can use this statistics data to compute the desired algorithm parameters for +the ImgU. + +Configuring the Intel IPU3 +========================== + +The IPU3 ImgU pipelines can be configured using the Media Controller, defined at +:ref:`media_controller`. + +Running mode and firmware binary selection +------------------------------------------ + +ImgU works based on firmware, currently the ImgU firmware support run 2 pipes in +time-sharing with single input frame data. Each pipe can run at certain mode - +"VIDEO" or "STILL", "VIDEO" mode is commonly used for video frames capture, and +"STILL" is used for still frame capture. However, you can also select "VIDEO" to +capture still frames if you want to capture images with less system load and +power. For "STILL" mode, ImgU will try to use smaller BDS factor and output +larger bayer frame for further YUV processing than "VIDEO" mode to get high +quality images. Besides, "STILL" mode need XNR3 to do noise reduction, hence +"STILL" mode will need more power and memory bandwidth than "VIDEO" mode. TNR +will be enabled in "VIDEO" mode and bypassed by "STILL" mode. ImgU is running at +“VIDEO” mode by default, the user can use v4l2 control V4L2_CID_INTEL_IPU3_MODE +(currently defined in drivers/staging/media/ipu3/include/intel-ipu3.h) to query +and set the running mode. For user, there is no difference for buffer queueing +between the "VIDEO" and "STILL" mode, mandatory input and main output node +should be enabled and buffers need be queued, the statistics and the view-finder +queues are optional. + +The firmware binary will be selected according to current running mode, such log +"using binary if_to_osys_striped " or "using binary if_to_osys_primary_striped" +could be observed if you enable the ImgU dynamic debug, the binary +if_to_osys_striped is selected for "VIDEO" and the binary +"if_to_osys_primary_striped" is selected for "STILL". + + +Processing the image in raw Bayer format +---------------------------------------- + +Configuring ImgU V4L2 subdev for image processing +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ + +The ImgU V4L2 subdevs have to be configured with media controller APIs to have +all the video nodes setup correctly. + +Let us take "ipu3-imgu 0" subdev as an example. + +media-ctl -d $MDEV -r + +media-ctl -d $MDEV -l "ipu3-imgu 0 input":0 -> "ipu3-imgu 0":0[1] + +media-ctl -d $MDEV -l "ipu3-imgu 0":2 -> "ipu3-imgu 0 output":0[1] + +media-ctl -d $MDEV -l "ipu3-imgu 0":3 -> "ipu3-imgu 0 viewfinder":0[1] + +media-ctl -d $MDEV -l "ipu3-imgu 0":4 -> "ipu3-imgu 0 3a stat":0[1] + +Also the pipe mode of the corresponding V4L2 subdev should be set as desired +(e.g 0 for video mode or 1 for still mode) through the control id 0x009819a1 as +below. + +yavta -w "0x009819A1 1" /dev/v4l-subdev7 + +Certain hardware blocks in ImgU pipeline can change the frame resolution by +cropping or scaling, these hardware blocks include Input Feeder(IF), Bayer Down +Scaler (BDS) and Geometric Distortion Correction (GDC). +There is also a block which can change the frame resolution - YUV Scaler, it is +only applicable to the secondary output. + +RAW Bayer frames go through these ImgU pipeline hardware blocks and the final +processed image output to the DDR memory. + +.. kernel-figure:: ipu3_rcb.svg + :alt: ipu3 resolution blocks image + + IPU3 resolution change hardware blocks + +**Input Feeder** + +Input Feeder gets the Bayer frame data from the sensor, it can enable cropping +of lines and columns from the frame and then store pixels into device's internal +pixel buffer which are ready to readout by following blocks. + +**Bayer Down Scaler** + +Bayer Down Scaler is capable of performing image scaling in Bayer domain, the +downscale factor can be configured from 1X to 1/4X in each axis with +configuration steps of 0.03125 (1/32). + +**Geometric Distortion Correction** + +Geometric Distortion Correction is used to performe correction of distortions +and image filtering. It needs some extra filter and envelop padding pixels to +work, so the input resolution of GDC should be larger than the output +resolution. + +**YUV Scaler** + +YUV Scaler which similar with BDS, but it is mainly do image down scaling in +YUV domain, it can support up to 1/12X down scaling, but it can not be applied +to the main output. + +The ImgU V4L2 subdev has to be configured with the supported resolutions in all +the above hardware blocks, for a given input resolution. +For a given supported resolution for an input frame, the Input Feeder, Bayer +Down Scaler and GDC blocks should be configured with the supported resolutions +as each hardware block has its own alignment requirement. + +You must configure the output resolution of the hardware blocks smartly to meet +the hardware requirement along with keeping the maximum field of view. The +intermediate resolutions can be generated by specific tool - + +https://github.com/intel/intel-ipu3-pipecfg + +This tool can be used to generate intermediate resolutions. More information can +be obtained by looking at the following IPU3 ImgU configuration table. + +https://chromium.googlesource.com/chromiumos/overlays/board-overlays/+/master + +Under baseboard-poppy/media-libs/cros-camera-hal-configs-poppy/files/gcss +directory, graph_settings_ov5670.xml can be used as an example. + +The following steps prepare the ImgU pipeline for the image processing. + +1. The ImgU V4L2 subdev data format should be set by using the +VIDIOC_SUBDEV_S_FMT on pad 0, using the GDC width and height obtained above. + +2. The ImgU V4L2 subdev cropping should be set by using the +VIDIOC_SUBDEV_S_SELECTION on pad 0, with V4L2_SEL_TGT_CROP as the target, +using the input feeder height and width. + +3. The ImgU V4L2 subdev composing should be set by using the +VIDIOC_SUBDEV_S_SELECTION on pad 0, with V4L2_SEL_TGT_COMPOSE as the target, +using the BDS height and width. + +For the ov5670 example, for an input frame with a resolution of 2592x1944 +(which is input to the ImgU subdev pad 0), the corresponding resolutions +for input feeder, BDS and GDC are 2592x1944, 2592x1944 and 2560x1920 +respectively. + +Once this is done, the received raw Bayer frames can be input to the ImgU +V4L2 subdev as below, using the open source application v4l2n [#f1]_. + +For an image captured with 2592x1944 [#f4]_ resolution, with desired output +resolution as 2560x1920 and viewfinder resolution as 2560x1920, the following +v4l2n command can be used. This helps process the raw Bayer frames and produces +the desired results for the main output image and the viewfinder output, in NV12 +format. + +v4l2n --pipe=4 --load=/tmp/frame-#.bin --open=/dev/video4 +--fmt=type:VIDEO_OUTPUT_MPLANE,width=2592,height=1944,pixelformat=0X47337069 +--reqbufs=type:VIDEO_OUTPUT_MPLANE,count:1 --pipe=1 --output=/tmp/frames.out +--open=/dev/video5 +--fmt=type:VIDEO_CAPTURE_MPLANE,width=2560,height=1920,pixelformat=NV12 +--reqbufs=type:VIDEO_CAPTURE_MPLANE,count:1 --pipe=2 --output=/tmp/frames.vf +--open=/dev/video6 +--fmt=type:VIDEO_CAPTURE_MPLANE,width=2560,height=1920,pixelformat=NV12 +--reqbufs=type:VIDEO_CAPTURE_MPLANE,count:1 --pipe=3 --open=/dev/video7 +--output=/tmp/frames.3A --fmt=type:META_CAPTURE,? +--reqbufs=count:1,type:META_CAPTURE --pipe=1,2,3,4 --stream=5 + +You can also use yavta [#f2]_ command to do same thing as above: + +.. code-block:: none + + yavta --data-prefix -Bcapture-mplane -c10 -n5 -I -s2592x1944 \ + --file=frame-#.out-f NV12 /dev/video5 & \ + yavta --data-prefix -Bcapture-mplane -c10 -n5 -I -s2592x1944 \ + --file=frame-#.vf -f NV12 /dev/video6 & \ + yavta --data-prefix -Bmeta-capture -c10 -n5 -I \ + --file=frame-#.3a /dev/video7 & \ + yavta --data-prefix -Boutput-mplane -c10 -n5 -I -s2592x1944 \ + --file=/tmp/frame-in.cio2 -f IPU3_SGRBG10 /dev/video4 + +where /dev/video4, /dev/video5, /dev/video6 and /dev/video7 devices point to +input, output, viewfinder and 3A statistics video nodes respectively. + +Converting the raw Bayer image into YUV domain +---------------------------------------------- + +The processed images after the above step, can be converted to YUV domain +as below. + +Main output frames +~~~~~~~~~~~~~~~~~~ + +raw2pnm -x2560 -y1920 -fNV12 /tmp/frames.out /tmp/frames.out.ppm + +where 2560x1920 is output resolution, NV12 is the video format, followed +by input frame and output PNM file. + +Viewfinder output frames +~~~~~~~~~~~~~~~~~~~~~~~~ + +raw2pnm -x2560 -y1920 -fNV12 /tmp/frames.vf /tmp/frames.vf.ppm + +where 2560x1920 is output resolution, NV12 is the video format, followed +by input frame and output PNM file. + +Example user space code for IPU3 +================================ + +User space code that configures and uses IPU3 is available here. + +https://chromium.googlesource.com/chromiumos/platform/arc-camera/+/master/ + +The source can be located under hal/intel directory. + +Overview of IPU3 pipeline +========================= + +IPU3 pipeline has a number of image processing stages, each of which takes a +set of parameters as input. The major stages of pipelines are shown here: + +.. kernel-render:: DOT + :alt: IPU3 ImgU Pipeline + :caption: IPU3 ImgU Pipeline Diagram + + digraph "IPU3 ImgU" { + node [shape=box] + splines="ortho" + rankdir="LR" + + a [label="Raw pixels"] + b [label="Bayer Downscaling"] + c [label="Optical Black Correction"] + d [label="Linearization"] + e [label="Lens Shading Correction"] + f [label="White Balance / Exposure / Focus Apply"] + g [label="Bayer Noise Reduction"] + h [label="ANR"] + i [label="Demosaicing"] + j [label="Color Correction Matrix"] + k [label="Gamma correction"] + l [label="Color Space Conversion"] + m [label="Chroma Down Scaling"] + n [label="Chromatic Noise Reduction"] + o [label="Total Color Correction"] + p [label="XNR3"] + q [label="TNR"] + r [label="DDR", style=filled, fillcolor=yellow, shape=cylinder] + s [label="YUV Downscaling"] + t [label="DDR", style=filled, fillcolor=yellow, shape=cylinder] + + { rank=same; a -> b -> c -> d -> e -> f -> g -> h -> i } + { rank=same; j -> k -> l -> m -> n -> o -> p -> q -> s -> t} + + a -> j [style=invis, weight=10] + i -> j + q -> r + } + +The table below presents a description of the above algorithms. + +======================== ======================================================= +Name Description +======================== ======================================================= +Optical Black Correction Optical Black Correction block subtracts a pre-defined + value from the respective pixel values to obtain better + image quality. + Defined in :c:type:`ipu3_uapi_obgrid_param`. +Linearization This algo block uses linearization parameters to + address non-linearity sensor effects. The Lookup table + table is defined in + :c:type:`ipu3_uapi_isp_lin_vmem_params`. +SHD Lens shading correction is used to correct spatial + non-uniformity of the pixel response due to optical + lens shading. This is done by applying a different gain + for each pixel. The gain, black level etc are + configured in :c:type:`ipu3_uapi_shd_config_static`. +BNR Bayer noise reduction block removes image noise by + applying a bilateral filter. + See :c:type:`ipu3_uapi_bnr_static_config` for details. +ANR Advanced Noise Reduction is a block based algorithm + that performs noise reduction in the Bayer domain. The + convolution matrix etc can be found in + :c:type:`ipu3_uapi_anr_config`. +DM Demosaicing converts raw sensor data in Bayer format + into RGB (Red, Green, Blue) presentation. Then add + outputs of estimation of Y channel for following stream + processing by Firmware. The struct is defined as + :c:type:`ipu3_uapi_dm_config`. +Color Correction Color Correction algo transforms sensor specific color + space to the standard "sRGB" color space. This is done + by applying 3x3 matrix defined in + :c:type:`ipu3_uapi_ccm_mat_config`. +Gamma correction Gamma correction :c:type:`ipu3_uapi_gamma_config` is a + basic non-linear tone mapping correction that is + applied per pixel for each pixel component. +CSC Color space conversion transforms each pixel from the + RGB primary presentation to YUV (Y: brightness, + UV: Luminance) presentation. This is done by applying + a 3x3 matrix defined in + :c:type:`ipu3_uapi_csc_mat_config` +CDS Chroma down sampling + After the CSC is performed, the Chroma Down Sampling + is applied for a UV plane down sampling by a factor + of 2 in each direction for YUV 4:2:0 using a 4x2 + configurable filter :c:type:`ipu3_uapi_cds_params`. +CHNR Chroma noise reduction + This block processes only the chrominance pixels and + performs noise reduction by cleaning the high + frequency noise. + See struct :c:type:`ipu3_uapi_yuvp1_chnr_config`. +TCC Total color correction as defined in struct + :c:type:`ipu3_uapi_yuvp2_tcc_static_config`. +XNR3 eXtreme Noise Reduction V3 is the third revision of + noise reduction algorithm used to improve image + quality. This removes the low frequency noise in the + captured image. Two related structs are being defined, + :c:type:`ipu3_uapi_isp_xnr3_params` for ISP data memory + and :c:type:`ipu3_uapi_isp_xnr3_vmem_params` for vector + memory. +TNR Temporal Noise Reduction block compares successive + frames in time to remove anomalies / noise in pixel + values. :c:type:`ipu3_uapi_isp_tnr3_vmem_params` and + :c:type:`ipu3_uapi_isp_tnr3_params` are defined for ISP + vector and data memory respectively. +======================== ======================================================= + +Other often encountered acronyms not listed in above table: + + ACC + Accelerator cluster + AWB_FR + Auto white balance filter response statistics + BDS + Bayer downscaler parameters + CCM + Color correction matrix coefficients + IEFd + Image enhancement filter directed + Obgrid + Optical black level compensation + OSYS + Output system configuration + ROI + Region of interest + YDS + Y down sampling + YTM + Y-tone mapping + +A few stages of the pipeline will be executed by firmware running on the ISP +processor, while many others will use a set of fixed hardware blocks also +called accelerator cluster (ACC) to crunch pixel data and produce statistics. + +ACC parameters of individual algorithms, as defined by +:c:type:`ipu3_uapi_acc_param`, can be chosen to be applied by the user +space through struct :c:type:`ipu3_uapi_flags` embedded in +:c:type:`ipu3_uapi_params` structure. For parameters that are configured as +not enabled by the user space, the corresponding structs are ignored by the +driver, in which case the existing configuration of the algorithm will be +preserved. + +References +========== + +.. [#f5] drivers/staging/media/ipu3/include/intel-ipu3.h + +.. [#f1] https://github.com/intel/nvt + +.. [#f2] http://git.ideasonboard.org/yavta.git + +.. [#f3] http://git.ideasonboard.org/?p=media-ctl.git;a=summary + +.. [#f4] ImgU limitation requires an additional 16x16 for all input resolutions |