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From 241b4b17d83285eb4bf4151dd77198427ac9fde4 Mon Sep 17 00:00:00 2001
From: Mario Haustein <mario.haustein@hrz.tu-chemnitz.de>
Date: Sun, 28 Apr 2024 14:09:19 +0200
Subject: [PATCH] Fix multiple definition of struct options
Upstream: https://gitlab.com/free-astro/siril/-/merge_requests/668
Bug: https://bugs.gentoo.org/927345
--- a/src/filters/deconvolution/estimate_kernel.cpp
+++ b/src/filters/deconvolution/estimate_kernel.cpp
@@ -33,7 +33,7 @@ extern "C" float *estimate_kernel(estk_data *args, int max_threads) {
if (!cppfftwmultithreaded)
max_threads = 1;
img_t<float>::use_threading(max_threads);
- options opts;
+ estimate_kernel_options opts;
opts.ks = args->ks;
opts.lambda = args->lambda;
opts.lambda_ratio = args->lambda_ratio;
--- a/src/filters/deconvolution/estimate_kernel.hpp
+++ b/src/filters/deconvolution/estimate_kernel.hpp
@@ -56,7 +56,7 @@ void gaussian_downsample(img_t<float>& out, const img_t<float>& _in, float facto
}
}
-struct options {
+struct estimate_kernel_options {
bool verbose;
int ks;
float lambda;
@@ -81,7 +81,7 @@ template <typename T>
class ImagePredictor {
public:
virtual void solve(img_t<T>& u, const img_t<T>& K, T lambda, T beta_init, T beta_rate, T beta_max,
- const options& opts) = 0;
+ const estimate_kernel_options& opts) = 0;
virtual ~ImagePredictor() {}
};
@@ -114,7 +114,7 @@ public:
}
void solve(img_t<T>& u, const img_t<T>& K,
- T lambda, T beta_init, T beta_rate, T beta_max, const options& opts) {
+ T lambda, T beta_init, T beta_rate, T beta_max, const estimate_kernel_options& opts) {
assert(K.w % 2);
assert(K.h % 2);
@@ -177,7 +177,7 @@ public:
template <typename T>
class KernelEstimator {
public:
- virtual void solve(img_t<T>& k, const img_t<T>& u, const struct options& opts) = 0;
+ virtual void solve(img_t<T>& k, const img_t<T>& u, const struct estimate_kernel_options& opts) = 0;
virtual ~KernelEstimator() {}
};
@@ -198,7 +198,7 @@ public:
}
// implements Algorithm 3
- void solve(img_t<T>& k, const img_t<T>& u, const struct options& opts) {
+ void solve(img_t<T>& k, const img_t<T>& u, const struct estimate_kernel_options& opts) {
k.resize(ks, ks);
// solves the Equation (28)
@@ -313,7 +313,7 @@ public:
fv = fft::r2c(v);
}
- void solve(img_t<T>& k, const img_t<T>& u, const struct options& opts) {
+ void solve(img_t<T>& k, const img_t<T>& u, const struct estimate_kernel_options& opts) {
if (k.w != ks || k.h != ks)
k.resize(ks, ks);
@@ -407,7 +407,7 @@ public:
// estimates the sharp image and the kernel from a blurry image and an initialization of u
template <typename T>
void l0_kernel_estimation(img_t<T>& k, img_t<T>& u, const img_t<T>& v,
- const img_t<T>& initu, struct options& opts) {
+ const img_t<T>& initu, struct estimate_kernel_options& opts) {
// static int it = 0;
ImagePredictor<T>* sharp_predictor = nullptr;
sharp_predictor = new L0ImagePredictor<T>(v);
@@ -463,7 +463,7 @@ void l0_kernel_estimation(img_t<T>& k, img_t<T>& u, const img_t<T>& v,
// it assumes that the image was previously processed by preprocess_image
// the inner loop is implemented in l0_kernel_estimation
template <typename T>
-void multiscale_l0_kernel_estimation(img_t<T>& k, img_t<T>& u, const img_t<T>& v, struct options& opts) {
+void multiscale_l0_kernel_estimation(img_t<T>& k, img_t<T>& u, const img_t<T>& v, struct estimate_kernel_options& opts) {
std::vector<img_t<T>> vs;
std::vector<int> kernelSizes;
printf("Multiscale kernel estimation...\n");
@@ -511,7 +511,7 @@ void multiscale_l0_kernel_estimation(img_t<T>& k, img_t<T>& u, const img_t<T>& v
// preprocess the input blurry image as describe in Section 2.1
template <typename T>
-void preprocess_image(img_t<T>& out, const img_t<T>& _v, struct options& opts) {
+void preprocess_image(img_t<T>& out, const img_t<T>& _v, struct estimate_kernel_options& opts) {
img_t<T> v(_v.w, _v.h);
// convert to grayscale
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