# SPDX-License-Identifier: BSD-2-Clause
#
# Copyright (C) 2019, Raspberry Pi Ltd
#
# ctt_awb.py - camera tuning tool for AWB
from ctt_image_load import *
import matplotlib.pyplot as plt
from bisect import bisect_left
from scipy.optimize import fmin
"""
obtain piecewise linear approximation for colour curve
"""
def awb(Cam, cal_cr_list, cal_cb_list, plot):
imgs = Cam.imgs
"""
condense alsc calibration tables into one dictionary
"""
if cal_cr_list is None:
colour_cals = None
else:
colour_cals = {}
for cr, cb in zip(cal_cr_list, cal_cb_list):
cr_tab = cr['table']
cb_tab = cb['table']
"""
normalise tables so min value is 1
"""
cr_tab = cr_tab/np.min(cr_tab)
cb_tab = cb_tab/np.min(cb_tab)
colour_cals[cr['ct']] = [cr_tab, cb_tab]
"""
obtain data from greyscale macbeth patches
"""
rb_raw = []
rbs_hat = []
for Img in imgs:
Cam.log += '\nProcessing '+Img.name
"""
get greyscale patches with alsc applied if alsc enabled.
Note: if alsc is disabled then colour_cals will be set to None and the
function will just return the greyscale patches
"""
r_patchs, b_patchs, g_patchs = get_alsc_patches(Img, colour_cals)
"""
calculate ratio of r, b to g
"""
r_g = np.mean(r_patchs/g_patchs)
b_g = np.mean(b_patchs/g_patchs)
Cam.log += '\n r : {:.4f} b : {:.4f}'.format(r_g, b_g)
"""
The curve tends to be better behaved in so-called hatspace.
R, B, G represent the individual channels. The colour curve is plotted in
r, b space, where:
r = R/G
b = B/G
This will be referred to as dehatspace... (sorry)
Hatspace is defined as:
r_hat = R/(R+B+G)
b_hat = B/(R+B+G)
To convert from dehatspace to hastpace (hat operation):
r_hat = r/(1+r+b)
b_hat = b/(1+r+b)
To convert from hatspace to dehatspace (dehat operation):
r = r_hat/(1-r_hat-b_hat)
b = b_hat/(1-r_hat-b_hat)
Proof is left as an excercise to the reader...
Throughout the code, r and b are sometimes referred to as r_g and b_g
as a reminder that they are ratios
"""
r_g_hat = r_g/(1+r_g+b_g)
b_g_hat = b_g/(1+r_g+b_g)
Cam.log += '\n r_hat : {:.4f} b_hat : {:.4f}'.format(r_g_hat, b_g_hat)
rbs_hat.append((r_g_hat, b_g_hat, Img.col))
rb_raw.append((r_g, b_g))
Cam.log += '\n'
Cam.log += '\nFinished processing images'
"""
sort all lits simultaneously by r_hat
"""
rbs_zip = list(zip(rbs_hat, rb_raw))
rbs_zip.sort(key=lambda x: x[0][0])
rbs_hat, rb_raw = list(zip(*rbs_zip))
"""
unzip tuples ready for processing
"""
rbs_hat = list(zip(*rbs_hat))
rb_raw = list(zip(*rb_raw))
"""
fit quadratic fit to r_g hat and b_g_hat
"""
a, b, c = np.polyfit(rbs_hat[0], rbs_hat[1], 2)
Cam.log += '\nFit quadratic curve in hatspace'
"""
the algorithm now approximates the shortest distance from each point to the
curve in dehatspace. Since the fit is done in hatspace, it is easier to
find the actual shortest distance in hatspace and use the projection back
into dehatspace as an overestimate.
The distance will be used for two things:
1) In the case that colour temperature does not strictly decrease with
increasing r/g, the closest point to the line will be chosen out of an
increasing pair of colours.
2) To calculate transverse negative an dpositive, the maximum positive
and negative distance from the line are chosen. This benefits from the
overestimate as the transverse pos/neg are upper bound values.
"""
"""
define fit function
"""
def f(x):
return a*x**2 + b*x + c
"""
iterate over points (R, B are x and y coordinates of points) and calculate
distance to line in dehatspace
"""
dists = []
for i, (R, B) in enumerate(zip(rbs_hat[0], rbs_hat[1])):
"""
define function to minimise as square distance between datapoint and
point on curve. Squaring is monotonic so minimising radius squared is
equivalent to minimising radius
"""
def f_min(x):
y = f(x)
return((x-R)**2+(y-B)**2)
"""
perform optimisation with scipy.optmisie.fmin
"""
x_hat = fmin(f_min, R, disp=0)[0]
y_hat = f(x_hat)
"""
dehat
"""
x = x_hat/(1-x_hat-y_hat)
y = y_hat/(1-x_hat-y_hat)
rr = R/(1-R-B)
bb = B/(1-R-B)
"""
calculate euclidean distance in dehatspace
"""
dist = ((x-rr)**2+(y-bb)**2)**0.5
"""
return negative if point is below the fit curve
"""
if (x+y) > (rr+bb):
dist *= -1
dists.append(dist)
Cam.log += '\nFound closest point on fit line to each point in dehatspace'
"""
calculate wiggle factors in awb. 10% added since this is an upper bound
"""
transverse_neg = - np.min(dists) * 1.1
transverse_pos = np.max(dists) * 1.1
Cam.log += '\nTransverse pos : {:.5f}'.format(transverse_pos)
Cam.log += '\nTransverse neg : {:.5f}'.format(transverse_neg)
"""
set minimum transverse wiggles to 0.1 .
Wiggle factors dictate how far off of the curve the algorithm searches. 0.1
is a suitable minimum that gives better results for lighting conditions not
within calibration dataset. Anything less will generalise poorly.
"""
if transverse_pos < 0.01:
transverse_pos = 0.01
Cam.log += '\nForced transverse pos to 0.01'
if transverse_neg < 0.01:
transverse_neg = 0.01
Cam.log += '\nForced transverse neg to 0.01'
"""
generate new b_hat values at each r_hat according to fit
"""
r_hat_fit = np.array(rbs_hat[0])
b_hat_fit = a*r_hat_fit**2 + b*r_hat_fit + c
"""
transform from hatspace to dehatspace
"""
r_fit = r_hat_fit/(1-r_hat_fit-b_hat_fit)
b_fit = b_hat_fit/(1-r_hat_fit-b_hat_fit)
c_fit = np.round(rbs_hat[2], 0)
"""
round to 4dp
"""
r_fit = np.where((1000*r_fit) % 1 <= 0.05, r_fit+0.0001, r_fit)
r_fit = np.where((1000*r_fit) % 1 >= 0.95, r_fit-0.0001, r_fit)
b_fit = np.where((1000*b_fit) % 1 <= 0.05, b_fit+0.0001, b_fit)
b_fit = np.where((1000*b_fit) % 1 >= 0.95, b_fit-0.0001, b_fit)
r_fit = np.round(r_fit, 4)
b_fit = np.round(b_fit, 4)
"""
The following code ensures that colour temperature decreases with
increasing r/g
"""
"""
iterate backwards over list for easier indexing
"""
i = len(c_fit) - 1
while i > 0:
if c_fit[i] > c_fit[i-1]:
Cam.log += '\nColour temperature increase found\n'
Cam.log += '{} K at r = {} to '.format(c_fit[i-1], r_fit[i-1])
Cam.log += '{} K at r = {}'.format(c_fit[i], r_fit[i])
"""
if colour temperature increases then discard point furthest from
the transformed fit (dehatspace)
"""
error_1 = abs(dists[i-1])
error_2 = abs(dists[i])
Cam.log += '\nDistances from fit:\n'
Cam.log += '{} K : {:.5f} , '.format(c_fit[i], error_1)
Cam.log += '{} K : {:.5f}'.format(c_fit[i-1], error_2)
"""
find bad index
note that in python false = 0 and true = 1
"""
bad = i - (error_1 < error_2)
Cam.log += '\nPoint at {} K deleted as '.format(c_fit[bad])
Cam.log += 'it is furthest from fit'
"""
delete bad point
"""
r_fit = np.delete(r_fit, bad)
b_fit = np.delete(b_fit, bad)
c_fit = np.delete(c_fit, bad).astype(np.uint16)
"""
note that if a point has been discarded then the length has decreased
by one, meaning that decreasing the index by one will reassess the kept
point against the next point. It is therefore possible, in theory, for
two adjacent points to be discarded, although probably rare
"""
i -= 1
"""
return formatted ct curve, ordered by increasing colour temperature
"""
ct_curve = list(np.array(list(zip(b_fit, r_fit, c_fit))).flatten())[::-1]
Cam.log += '\nFinal CT curve:'
for i in range(len(ct_curve)//3):
j = 3*i
Cam.log += '\n ct: {} '.format(ct_curve[j])
Cam.log += ' r: {} '.format(ct_curve[j+1])
Cam.log += ' b: {} '.format(ct_curve[j+2])
"""
plotting code for debug
"""
if plot:
x = np.linspace(np.min(rbs_hat[0]), np.max(rbs_hat[0]), 100)
y = a*x**2 + b*x + c
plt.subplot(2, 1, 1)
plt.title('hatspace')
plt.plot(rbs_hat[0], rbs_hat[1], ls='--', color='blue')
plt.plot(x, y, color='green', ls='-')
plt.scatter(rbs_hat[0], rbs_hat[1], color='red')
for i, ct in enumerate(rbs_hat[2]):
plt.annotate(str(ct), (rbs_hat[0][i], rbs_hat[1][i]))
plt.xlabel('$\\hat{r}$')
plt.ylabel('$\\hat{b}$')
"""
optional set axes equal to shortest distance so line really does
looks perpendicular and everybody is happy
"""
# ax = plt.gca()
# ax.set_aspect('equal')
plt.grid()
plt.subplot(2, 1, 2)
plt.title('dehatspace - indoors?')
plt.plot(r_fit, b_fit, color='blue')
plt.scatter(rb_raw[0], rb_raw[1], color='green')
plt.scatter(r_fit, b_fit, color='red')
for i, ct in enumerate(c_fit):
plt.annotate(str(ct), (r_fit[i], b_fit[i]))
plt.xlabel('$r$')
plt.ylabel('$b$')
"""
optional set axes equal to shortest distance so line really does
looks perpendicular and everybody is happy
"""
# ax = plt.gca()
# ax.set_aspect('equal')
plt.subplots_adjust(hspace=0.5)
plt.grid()
plt.show()
"""
end of plotting code
"""
return(ct_curve, np.round(transverse_pos, 5), np.round(transverse_neg, 5))
"""
obtain greyscale patches and perform alsc colour correction
"""
def get_alsc_patches(Img, colour_cals, grey=True):
"""
get patch centre coordinates, image colour and the actual
patches for each channel, remembering to subtract blacklevel
If grey then only greyscale patches considered
"""
if grey:
cen_coords = Img.cen_coords[3::4]
col = Img.col
patches = [np.array(Img.patches[i]) for i in Img.order]
r_patchs = patches[0][3::4] - Img.blacklevel_16
b_patchs = patches[3][3::4] - Img.blacklevel_16
"""
note two green channels are averages
"""
g_patchs = (patches[1][3::4]+patches[2][3::4])/2 - Img.blacklevel_16
else:
cen_coords = Img.cen_coords
col = Img.col
patches = [np.array(Img.patches[i]) for i in Img.order]
r_patchs = patches[0] - Img.blacklevel_16
b_patchs = patches[3] - Img.blacklevel_16
g_patchs = (patches[1]+patches[2])/2 - Img.blacklevel_16
if colour_cals is None:
return r_patchs, b_patchs, g_patchs
"""
find where image colour fits in alsc colour calibration tables
"""
cts = list(colour_cals.keys())
pos = bisect_left(cts, col)
"""
if img colour is below minimum or above maximum alsc calibration colour, simply
pick extreme closest to img colour
"""
if pos % len(cts) == 0:
"""
this works because -0 = 0 = first and -1 = last index
"""
col_tabs = np.array(colour_cals[cts[-pos//len(cts)]])
"""
else, perform linear interpolation between existing alsc colour
calibration tables
"""
else:
bef = cts[pos-1]
aft = cts[pos]
da = col-bef
db = aft-col
bef_tabs = np.array(colour_cals[bef])
aft_tabs = np.array(colour_cals[aft])
col_tabs = (bef_tabs*db + aft_tabs*da)/(da+db)
col_tabs = np.reshape(col_tabs, (2, 12, 16))
"""
calculate dx, dy used to calculate alsc table
"""
w, h = Img.w/2, Img.h/2
dx, dy = int(-(-(w-1)//16)), int(-(-(h-1)//12))
"""
make list of pairs of gains for each patch by selecting the correct value
in alsc colour calibration table
"""
patch_gains = []
for cen in cen_coords:
x, y = cen[0]//dx, cen[1]//dy
# We could probably do with some better spatial interpolation here?
col_gains = (col_tabs[0][y][x], col_tabs[1][y][x])
patch_gains.append(col_gains)
"""
multiply the r and b channels in each patch by the respective gain, finally
performing the alsc colour correction
"""
for i, gains in enumerate(patch_gains):
r_patchs[i] = r_patchs[i] * gains[0]
b_patchs[i] = b_patchs[i] * gains[1]
"""
return greyscale patches, g channel and correct r, b channels
"""
return r_patchs, b_patchs, g_patchs
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/* SPDX-License-Identifier: LGPL-2.1-or-later */
/*
* Copyright (C) 2018, Google Inc.
*
* device_enumerator.cpp - Enumeration and matching
*/
#include "libcamera/internal/device_enumerator.h"
#include <string.h>
#include <libcamera/base/log.h>
#include "libcamera/internal/device_enumerator_sysfs.h"
#include "libcamera/internal/device_enumerator_udev.h"
#include "libcamera/internal/media_device.h"
/**
* \file device_enumerator.h
* \brief Enumeration and matching of media devices
*
* The purpose of device enumeration and matching is to find media devices in
* the system and map them to pipeline handlers.
*
* At the core of the enumeration is the DeviceEnumerator class, responsible
* for enumerating all media devices in the system. It handles all interactions
* with the operating system in a platform-specific way. For each media device
* found an instance of MediaDevice is created to store information about the
* device gathered from the kernel through the Media Controller API.
*
* The DeviceEnumerator can enumerate all or specific media devices in the
* system. When a new media device is added the enumerator creates a
* corresponding MediaDevice instance.
*
* The enumerator supports searching among enumerated devices based on criteria
* expressed in a DeviceMatch object.
*/
namespace libcamera {
LOG_DEFINE_CATEGORY(DeviceEnumerator)
/**
* \class DeviceMatch
* \brief Description of a media device search pattern
*
* The DeviceMatch class describes a media device using properties from the
* Media Controller struct media_device_info, entity names in the media graph
* or other properties that can be used to identify a media device.
*
* The description is meant to be filled by pipeline managers and passed to a
* device enumerator to find matching media devices.
*
* A DeviceMatch is created with a specific Linux device driver in mind,
* therefore the name of the driver is a required property. One or more Entity
* names can be added as match criteria.
*
* Pipeline handlers are recommended to add entities to DeviceMatch as
* appropriare to ensure that the media device they need can be uniquely
* identified. This is useful when the corresponding kernel driver can produce
* different graphs, for instance as a result of different driver versions or
* hardware configurations, and not all those graphs are suitable for a pipeline
* handler.
*/
/**
* \brief Construct a media device search pattern
* \param[in] driver The Linux device driver name that created the media device
*/
DeviceMatch::DeviceMatch(const std::string &driver)
: driver_(driver)
{
}
/**
* \brief Add a media entity name to the search pattern
* \param[in] entity The name of the entity in the media graph
*/
void DeviceMatch::add(const std::string &entity)
{
entities_.push_back(entity);
}
/**
* \brief Compare a search pattern with a media device
* \param[in] device The media device
*
* Matching is performed on the Linux device driver name and entity names from
* the media graph. A match is found if both the driver name matches and the
* media device contains all the entities listed in the search pattern.
*
* \return true if the media device matches the search pattern, false otherwise
*/
bool DeviceMatch::match(const MediaDevice *device) const
{
if (driver_ != device->driver())
return false;
for (const std::string &name : entities_) {
bool found = false;
for (const MediaEntity *entity : device->entities()) {
if (name == entity->name()) {
found = true;
break;
}
}
if (!found)
return false;
}
return true;
}
/**
* \class DeviceEnumerator
* \brief Enumerate, store and search media devices
*
* The DeviceEnumerator class is responsible for all interactions with the
* operating system related to media devices. It enumerates all media devices
* in the system, and for each device found creates an instance of the
* MediaDevice class and stores it internally. The list of media devices can
* then be searched using DeviceMatch search patterns.
*
* The enumerator also associates media device entities with device node paths.
*/
/**
* \brief Create a new device enumerator matching the systems capabilities
*
* Depending on how the operating system handles device detection, hot-plug
* notification and device node lookup, different device enumerator
* implementations may be needed. This function creates the best enumerator for
* the operating system based on the available resources. Not all different
* enumerator types are guaranteed to support all features.
*
* \return A pointer to the newly created device enumerator on success, or
* nullptr if an error occurs
*/
std::unique_ptr<DeviceEnumerator> DeviceEnumerator::create()
{
std::unique_ptr<DeviceEnumerator> enumerator;
#ifdef HAVE_LIBUDEV
enumerator = std::make_unique<DeviceEnumeratorUdev>();
if (!enumerator->init())
return enumerator;
#endif
/*
* Either udev is not available or udev initialization failed. Fall back
* on the sysfs enumerator.
*/
enumerator = std::make_unique<DeviceEnumeratorSysfs>();
if (!enumerator->init())
return enumerator;
return nullptr;
}
DeviceEnumerator::~DeviceEnumerator()
{
for (const std::shared_ptr<MediaDevice> &media : devices_) {
if (media->busy())
LOG(DeviceEnumerator, Error)
<< "Removing media device " << media->deviceNode()
<< " while still in use";
}
}
/**
* \fn DeviceEnumerator::init()
* \brief Initialize the enumerator
* \return 0 on success or a negative error code otherwise
* \retval -EBUSY the enumerator has already been initialized
* \retval -ENODEV the enumerator can't enumerate devices
*/
/**
* \fn DeviceEnumerator::enumerate()
* \brief Enumerate all media devices in the system
*
* This function finds and add all media devices in the system to the
* enumerator. It shall be implemented by all subclasses of DeviceEnumerator
* using system-specific methods.
*
* Individual media devices that can't be properly enumerated shall be skipped
* with a warning message logged, without returning an error. Only errors that
* prevent enumeration altogether shall be fatal.
*
* \context This function is \threadbound.
*
* \return 0 on success or a negative error code otherwise
*/
/**
* \brief Create a media device instance
* \param[in] deviceNode path to the media device to create
*
* Create a media device for the \a deviceNode, open it, and populate its
* media graph. The device enumerator shall then populate the media device by
* associating device nodes with entities using MediaEntity::setDeviceNode().
* This process is specific to each device enumerator, and the device enumerator
* shall ensure that device nodes are ready to be used (for instance, if
* applicable, by waiting for device nodes to be created and access permissions
* to be set by the system). Once done, it shall add the media device to the
* system with addDevice().
*
* \return Created media device instance on success, or nullptr otherwise
*/
std::unique_ptr<MediaDevice> DeviceEnumerator::createDevice(const std::string &deviceNode)
{
std::unique_ptr<MediaDevice> media = std::make_unique<MediaDevice>(deviceNode);
int ret = media->populate();
if (ret < 0) {
LOG(DeviceEnumerator, Info)
<< "Unable to populate media device " << deviceNode
<< " (" << strerror(-ret) << "), skipping";
return nullptr;
}
LOG(DeviceEnumerator, Debug)
<< "New media device \"" << media->driver()
<< "\" created from " << deviceNode;
return media;
}
/**
* \var DeviceEnumerator::devicesAdded
* \brief Notify of new media devices being found
*
* This signal is emitted when the device enumerator finds new media devices in
* the system. It may be emitted for every newly detected device, or once for
* multiple devices, at the discretion of the device enumerator. Not all device
* enumerator types may support dynamic detection of new devices.
*/
/**
* \brief Add a media device to the enumerator
* \param[in] media media device instance to add
*
* Store the media device in the internal list for later matching with
* pipeline handlers. \a media shall be created with createDevice() first.
* This function shall be called after all members of the entities of the
* media graph have been confirmed to be initialized.
*/
void DeviceEnumerator::addDevice(std::unique_ptr<MediaDevice> media)
{
LOG(DeviceEnumerator, Debug)
<< "Added device " << media->deviceNode() << ": " << media->driver();
devices_.push_back(std::move(media));
/* \todo To batch multiple additions, emit with a small delay here. */
devicesAdded.emit();
}
/**
* \brief Remove a media device from the enumerator
* \param[in] deviceNode Path to the media device to remove
*
* Remove the media device identified by \a deviceNode previously added to the
* enumerator with addDevice(). The media device's MediaDevice::disconnected
* signal is emitted.
*/
void DeviceEnumerator::removeDevice(const std::string &deviceNode)
{
std::shared_ptr<MediaDevice> media;
for (auto iter = devices_.begin(); iter != devices_.end(); ++iter) {
if ((*iter)->deviceNode() == deviceNode) {
media = std::move(*iter);
devices_.erase(iter);
break;
}
}
if (!media) {
LOG(DeviceEnumerator, Warning)
<< "Media device for node " << deviceNode
<< " not found";
return;
}
LOG(DeviceEnumerator, Debug)
<< "Media device for node " << deviceNode << " removed.";
media->disconnected.emit();
}
/**
* \brief Search available media devices for a pattern match
* \param[in] dm Search pattern
*
* Search in the enumerated media devices that are not already in use for a
* match described in \a dm. If a match is found and the caller intends to use
* it the caller is responsible for acquiring the MediaDevice object and
* releasing it when done with it.
*
* \return pointer to the matching MediaDevice, or nullptr if no match is found
*/
std::shared_ptr<MediaDevice> DeviceEnumerator::search(const DeviceMatch &dm)
{
for (std::shared_ptr<MediaDevice> &media : devices_) {
if (media->busy())
continue;
if (dm.match(media.get())) {
LOG(DeviceEnumerator, Debug)
<< "Successful match for media device \""
<< media->driver() << "\"";
return media;
}
}
return nullptr;
}
} /* namespace libcamera */
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