From 762204e9b28d76b67b51ef8867bf301590fa52ac Mon Sep 17 00:00:00 2001
From: Yang Zhang <yangzhang@live.com>
Date: Thu, 26 Dec 2019 19:25:02 +0800
Subject: [PATCH] Switch to "google" C++ style from customized "linux" style

---
 src/binding.cc | 45 +++++++++++++++------------------------------
 src/nms.cc     | 36 +++++++++++-------------------------
 2 files changed, 26 insertions(+), 55 deletions(-)

diff --git a/src/binding.cc b/src/binding.cc
index 445f853f3..13186dd71 100644
--- a/src/binding.cc
+++ b/src/binding.cc
@@ -4,36 +4,21 @@
 #include <pybind11/numpy.h>
 #include <pybind11/stl.h>
 
+namespace nms {
+enum class Method : uint32_t { LINEAR = 0, GAUSSIAN, HARD };
 
-namespace nms
-{
-enum class Method : uint32_t
-{
-  LINEAR = 0,
-  GAUSSIAN,
-  HARD
-};
-
-size_t soft_nms(float* boxes,
-                int32_t* index,
-                size_t count,
-                Method method,
-                float Nt,
-                float sigma,
-                float threshold);
+size_t soft_nms(float* boxes, int32_t* index, size_t count, Method method,
+                float Nt, float sigma, float threshold);
 }  // namespace nms
 
-namespace binding
-{
+namespace binding {
 namespace py = pybind11;
 using namespace pybind11::literals;
 
 py::tuple py_soft_nms(py::array_t<float, py::array::c_style> boxes,
                       nms::Method method = nms::Method::GAUSSIAN,
-                      float Nt           = 0.3,
-                      float sigma        = 0.5,
-                      float threshold    = 0.001)
-{
+                      float Nt = 0.3, float sigma = 0.5,
+                      float threshold = 0.001) {
   assert(boxes.ndim() == 2 && "Input should be 2-D NumPy array");
   assert(boxes.shape()[1] == 5 && "Input should have size [N,5]");
 
@@ -44,8 +29,8 @@ py::tuple py_soft_nms(py::array_t<float, py::array::c_style> boxes,
 
   auto N = nms::soft_nms(b, i, count, method, Nt, sigma, threshold);
 
-  std::vector<size_t> shape5    = {N, 5};
-  std::vector<size_t> shape1    = {N};
+  std::vector<size_t> shape5 = {N, 5};
+  std::vector<size_t> shape1 = {N};
   std::vector<ssize_t> strides5 = {sizeof(float) * 5, sizeof(float)};
   std::vector<ssize_t> strides1 = {sizeof(float)};
 
@@ -63,12 +48,12 @@ PYBIND11_MODULE(nms, m) {
   m.doc() = "SoftNMS for object detection.";
 
   py::enum_<nms::Method>(m, "NMSMethod")
-    .value("LINEAR", nms::Method::LINEAR)
-    .value("GAUSSIAN", nms::Method::GAUSSIAN)
-    .value("HARD", nms::Method::HARD)
-    .export_values();
+      .value("LINEAR", nms::Method::LINEAR)
+      .value("GAUSSIAN", nms::Method::GAUSSIAN)
+      .value("HARD", nms::Method::HARD)
+      .export_values();
   m.def("soft_nms", &py_soft_nms, "boxes"_a.noconvert(),
-        "method"_a = nms::Method::GAUSSIAN,
-        "Nt"_a = 0.3, "sigma"_a = 0.5, "threshold"_a = 0.001);
+        "method"_a = nms::Method::GAUSSIAN, "Nt"_a = 0.3, "sigma"_a = 0.5,
+        "threshold"_a = 0.001);
 }
 } /* namespace binding */
diff --git a/src/nms.cc b/src/nms.cc
index 84122685c..cbf7ae620 100644
--- a/src/nms.cc
+++ b/src/nms.cc
@@ -1,24 +1,21 @@
 #include <cmath>
 #include <algorithm>
 
-namespace nms
-{
-struct proposal
-{
+namespace nms {
+struct proposal {
   float score, x1, y1, x2, y2;
 };
 
-inline static bool cmp(const proposal& a, const proposal& b)
-{
+inline static bool cmp(const proposal& a, const proposal& b) {
   return a.score < b.score;
 }
 
-inline static float iou(const proposal&, const proposal&) __attribute__((always_inline));
+inline static float iou(const proposal&, const proposal&)
+    __attribute__((always_inline));
 
-static float iou(const proposal& a, const proposal& b)
-{
+static float iou(const proposal& a, const proposal& b) {
   auto overlap = 0.f;
-  float iw  = std::min(b.x2, a.x2) - std::max(b.x1, a.x1) + 1;
+  float iw = std::min(b.x2, a.x2) - std::max(b.x1, a.x1) + 1;
   if (iw > 0) {
     float ih = std::min(b.y2, a.y2) - std::max(b.y1, a.y1) + 1;
     if (ih > 0) {
@@ -31,21 +28,10 @@ static float iou(const proposal& a, const proposal& b)
   return overlap;
 }
 
-enum class Method : uint32_t
-{
-  LINEAR = 0,
-  GAUSSIAN,
-  HARD
-};
+enum class Method : uint32_t { LINEAR = 0, GAUSSIAN, HARD };
 
-size_t soft_nms(float* boxes,
-                int32_t* index,
-                size_t count,
-                Method method,
-                float Nt,
-                float sigma,
-                float threshold)
-{
+size_t soft_nms(float* boxes, int32_t* index, size_t count, Method method,
+                float Nt, float sigma, float threshold) {
   std::iota(index, index + count, 0);  // np.arange()
   auto p = reinterpret_cast<proposal*>(boxes);
 
@@ -55,7 +41,7 @@ size_t soft_nms(float* boxes,
     std::swap(p[i], *max);
     std::swap(index[i], index[max - p]);
 
-    auto j      = i + 1;
+    auto j = i + 1;
     auto weight = 0.f;
     while (j < N) {
       auto ov = iou(p[i], p[j]);
-- 
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