diff options
Diffstat (limited to 'src')
| -rw-r--r-- | src/ipa/libipa/awb.cpp | 5 | ||||
| -rw-r--r-- | src/ipa/libipa/awb_bayes.cpp | 8 |
2 files changed, 9 insertions, 4 deletions
diff --git a/src/ipa/libipa/awb.cpp b/src/ipa/libipa/awb.cpp index 62b69dd9..6157bd43 100644 --- a/src/ipa/libipa/awb.cpp +++ b/src/ipa/libipa/awb.cpp @@ -57,8 +57,9 @@ namespace ipa { * applied. To keep the actual implementations computationally inexpensive, * the squared colour error shall be returned. * - * If the awb statistics provide multiple zones, the sum over all zones needs to - * calculated. + * If the awb statistics provide multiple zones, the average of the individual + * squared errors shall be returned. Averaging/normalizing is necessary so that + * the numeric dimensions are the same on all hardware platforms. * * \return The computed error value */ diff --git a/src/ipa/libipa/awb_bayes.cpp b/src/ipa/libipa/awb_bayes.cpp index c3e0b69b..e75bfcd6 100644 --- a/src/ipa/libipa/awb_bayes.cpp +++ b/src/ipa/libipa/awb_bayes.cpp @@ -234,6 +234,10 @@ int AwbBayes::readPriors(const YamlObject &tuningData) auto &pwl = priors[lux]; for (const auto &[ct, prob] : ctToProbability) { + if (prob < 1e-6) { + LOG(Awb, Error) << "Prior probability must be larger than 1e-6"; + return -EINVAL; + } pwl.append(ct, prob); } } @@ -323,7 +327,7 @@ double AwbBayes::coarseSearch(const ipa::Pwl &prior, const AwbStats &stats) cons double b = ctB_.eval(t, &spanB); RGB<double> gains({ 1 / r, 1.0, 1 / b }); double delta2Sum = stats.computeColourError(gains); - double priorLogLikelihood = prior.eval(prior.domain().clamp(t)); + double priorLogLikelihood = log(prior.eval(prior.domain().clamp(t))); double finalLogLikelihood = delta2Sum - priorLogLikelihood; errorLimits.record(delta2Sum); @@ -406,7 +410,7 @@ void AwbBayes::fineSearch(double &t, double &r, double &b, ipa::Pwl const &prior for (int i = -nsteps; i <= nsteps; i++) { double tTest = t + i * step; double priorLogLikelihood = - prior.eval(prior.domain().clamp(tTest)); + log(prior.eval(prior.domain().clamp(tTest))); priorLogLikelihoodLimits.record(priorLogLikelihood); Pwl::Point rbStart{ { ctR_.eval(tTest, &spanR), ctB_.eval(tTest, &spanB) } }; |