[PATCH 3/9] media: docs: ipu3.rst: rely at automarkup extension

From: Mauro Carvalho Chehab
Date: Wed Sep 30 2020 - 02:36:15 EST


There are several :c:type: definitions there, in order to
do cross-references with the driver's documentation.

Those are broken when docs are built with Sphinx 3.x, as
it would require :c:struct: instead.

For Sphinx < 3.x, the automarkup.py extension is able to do the
replacement already, and a future improvement on it should make
it also work with Sphinx 3.x.

So, get rid of the usage of the :c:type: macro there.

Signed-off-by: Mauro Carvalho Chehab <mchehab+huawei@xxxxxxxxxx>
---
Documentation/admin-guide/media/ipu3.rst | 38 ++++++++++++------------
1 file changed, 19 insertions(+), 19 deletions(-)

diff --git a/Documentation/admin-guide/media/ipu3.rst b/Documentation/admin-guide/media/ipu3.rst
index a4cd489fc5dc..07d139bf8459 100644
--- a/Documentation/admin-guide/media/ipu3.rst
+++ b/Documentation/admin-guide/media/ipu3.rst
@@ -488,63 +488,63 @@ 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`.
+ Defined in struct 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`.
+ struct 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`.
+ configured in struct 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.
+ See struct 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`.
+ struct 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`.
+ struct 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
+ struct ipu3_uapi_ccm_mat_config.
+Gamma correction Gamma correction struct 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`
+ struct 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`.
+ configurable filter struct 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`.
+ See struct struct ipu3_uapi_yuvp1_chnr_config.
TCC Total color correction as defined in struct
- :c:type:`ipu3_uapi_yuvp2_tcc_static_config`.
+ struct 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
+ struct ipu3_uapi_isp_xnr3_params for ISP data memory
+ and struct 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
+ values. struct ipu3_uapi_isp_tnr3_vmem_params and
+ struct ipu3_uapi_isp_tnr3_params are defined for ISP
vector and data memory respectively.
======================== =======================================================

@@ -576,9 +576,9 @@ 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
+struct ipu3_uapi_acc_param, can be chosen to be applied by the user
+space through struct struct ipu3_uapi_flags embedded in
+struct 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.
--
2.26.2