From 1cd70589056bc139693a2a9f29d5af137c2189f9 Mon Sep 17 00:00:00 2001
From: Xing Song <xing_song@foxmail.com>
Date: Fri, 15 May 2026 04:41:43 +0800
Subject: [PATCH] temp

Signed-off-by: Xing Song <xing_song@foxmail.com>
---
 examples/yolov8/cpp/src/postprocess.cpp | 23 ++++++++++++++++++-----
 1 file changed, 18 insertions(+), 5 deletions(-)

diff --git a/examples/yolov8/cpp/src/postprocess.cpp b/examples/yolov8/cpp/src/postprocess.cpp
index 57ac8c8..32f7057 100755
--- a/examples/yolov8/cpp/src/postprocess.cpp
+++ b/examples/yolov8/cpp/src/postprocess.cpp
@@ -156,7 +156,7 @@ cv::Mat quantize_input(const cv::Mat& float_img, float scale, int8_t zero_point)
 }
 
 static std::vector<Detection> get_detections(float* output, std::tuple<int, int, int> output_shape,
-                                            int stride, float conf_thresh) {
+                                            int stride, float conf_thresh, int index) {
     std::vector<Detection> detections;
 
     int grid_h = std::get<0>(output_shape);
@@ -208,6 +208,8 @@ static std::vector<Detection> get_detections(float* output, std::tuple<int, int,
                 }
             }
 
+            float keypoint_index = index + (i * grid_w) + j;
+
             // Convert to absolute coordinates
             float anchor_x = (j + 0.5f) * stride;
             float anchor_y = (i + 0.5f) * stride;
@@ -222,29 +224,33 @@ static std::vector<Detection> get_detections(float* output, std::tuple<int, int,
             float x2 = anchor_x + right * stride;
             float y2 = anchor_y + bottom * stride;
 
-            detections.push_back({x1, y1, x2, y2, max_score, class_id});
+            detections.push_back({x1, y1, x2, y2, max_score, class_id, keypoint_index});
         }
     }
+    index += grid_h * grid_w;
     return detections;
 }
 
 std::vector<Detection> postprocess(std::tuple<float*, std::tuple<int, int, int>, int> out0,
                                    std::tuple<float*, std::tuple<int, int, int>, int> out1,
                                    std::tuple<float*, std::tuple<int, int, int>, int> out2,
+                                   std::tuple<float*, std::tuple<int, int, int>, int> out3,
                                    std::tuple<cv::Mat, float, std::tuple<int, int>> input_tuple,
                                    float conf_thresh, float iou_threshold) {
     float scale = std::get<1>(input_tuple);
     int pad_left = std::get<0>(std::get<2>(input_tuple));
     int pad_top = std::get<1>(std::get<2>(input_tuple));
+    int index = 0;
 
     std::vector<Detection> detections;
 
-    auto process_out = [&](auto& out) {
+    auto process_out = [&](auto& out, auto& index) {
         float* output = std::get<0>(out);
         auto shape = std::get<1>(out);
         int stride = std::get<2>(out);
-        std::vector<Detection> dets = get_detections(output, shape, stride, conf_thresh);
+        std::vector<Detection> dets = get_detections(output, shape, stride, conf_thresh, index);
         detections.insert(detections.end(), dets.begin(), dets.end());
+        index +=
     };
 
     // Process all three scales
@@ -255,6 +261,13 @@ std::vector<Detection> postprocess(std::tuple<float*, std::tuple<int, int, int>,
     // Map coordinates back to original image
     std::vector<Detection> detections_orig;
     for (const auto& det : detections) {
+        for (int j = 0; j < 17; i++) {
+            Keypoint* keypoint = det.keypoint;
+            keypoint[j].x = (out3[j*3*8400+0*8400+det.keypoint_index] - pad_left) / scale;
+            keypoint[j].y = (out3[j*3*8400+1*8400+det.keypoint_index] - pad_left) / scale;
+            keypoint[j].score = out3[j*3*8400+2*8400+det.keypoint_index];
+        }
+
         float x1_orig = (det.x1 - pad_left) / scale;
         float y1_orig = (det.y1 - pad_top) / scale;
         float x2_orig = (det.x2 - pad_left) / scale;
@@ -266,7 +279,7 @@ std::vector<Detection> postprocess(std::tuple<float*, std::tuple<int, int, int>,
         x2_orig = std::max(0.0f, x2_orig);
         y2_orig = std::max(0.0f, y2_orig);
 
-        detections_orig.push_back({x1_orig, y1_orig, x2_orig, y2_orig, det.score, det.class_id});
+        detections_orig.push_back({x1_orig, y1_orig, x2_orig, y2_orig, det.score, det.class_id, det.keypoint_index, det.keypoint});
     }
 
     // Apply NMS