diff --git a/configs/sample_person_shoe_two_stage.json b/configs/sample_person_shoe_two_stage.json
index 9793e91..646e805 100644
--- a/configs/sample_person_shoe_two_stage.json
+++ b/configs/sample_person_shoe_two_stage.json
@@ -74,19 +74,20 @@
           "type": "ai_shoe_det",
           "role": "filter",
           "enable": true,
-          "infer_fps": 2,
+          "infer_fps": 1,
           "model_path": "./models/shoe_detector_openimages_ppe_v1.rknn",
           "model_w": 640,
           "model_h": 640,
           "conf": 0.25,
           "nms": 0.45,
+          "v8_box_format": "cxcywh",
           "append_detections": true,
           "dynamic_roi": {
             "enable": true,
             "person_class_id": 0,
             "shoe_class_id": 1,
             "debug_roi_class_id": 2,
-            "max_rois": 4,
+            "max_rois": 3,
             "min_person_height": 80,
             "x_offset": -0.20,
             "y_offset": 0.68,
diff --git a/plugins/ai_shoe_det/ai_shoe_det_node.cpp b/plugins/ai_shoe_det/ai_shoe_det_node.cpp
index 159eb6b..3c2064f 100644
--- a/plugins/ai_shoe_det/ai_shoe_det_node.cpp
+++ b/plugins/ai_shoe_det/ai_shoe_det_node.cpp
@@ -283,6 +283,28 @@ public:
         conf_thresh_ = config.ValueOr<float>("conf", 0.25f);
         nms_thresh_ = config.ValueOr<float>("nms", 0.45f);
         append_detections_ = config.ValueOr<bool>("append_detections", false);
+        {
+            const std::string bf = config.ValueOr<std::string>("v8_box_format", "auto");
+            if (bf == "xyxy") {
+                v8_box_format_ = V8BoxFormat::XyXy;
+            } else if (bf == "xywh") {
+                v8_box_format_ = V8BoxFormat::XyWh;
+            } else if (bf == "cxcywh") {
+                v8_box_format_ = V8BoxFormat::CxCyWh;
+            } else {
+                v8_box_format_ = V8BoxFormat::Auto;
+            }
+        }
+        {
+            const std::string act = config.ValueOr<std::string>("v8_cls_activation", "auto");
+            if (act == "sigmoid") {
+                v8_cls_activation_ = V8ClsActivation::Sigmoid;
+            } else if (act == "none") {
+                v8_cls_activation_ = V8ClsActivation::None;
+            } else {
+                v8_cls_activation_ = V8ClsActivation::Auto;
+            }
+        }
 
         infer_interval_ms_ = std::max<int64_t>(
             0, static_cast<int64_t>(config.ValueOr<int>("infer_interval_ms", 0)));
@@ -581,7 +603,7 @@ private:
         auto append_box = [&](float a, float b, float c, float d, float conf) {
             if (!std::isfinite(a) || !std::isfinite(b) || !std::isfinite(c) || !std::isfinite(d)) return;
             float x = 0.0f, y = 0.0f, w = 0.0f, h = 0.0f;
-            DecodeV8Box(a, b, c, d, model_w_, model_h_, V8BoxFormat::Auto, x, y, w, h);
+            DecodeV8Box(a, b, c, d, model_w_, model_h_, v8_box_format_, x, y, w, h);
             if (!std::isfinite(x) || !std::isfinite(y) || !std::isfinite(w) || !std::isfinite(h)) return;
             if (w <= 1e-3f || h <= 1e-3f) return;
             if (w > model_w_ * 1.2f || h > model_h_ * 1.2f) return;
@@ -599,7 +621,7 @@ private:
         if (outputs[0].type == RKNN_TENSOR_FLOAT32) {
             const float* data = reinterpret_cast<const float*>(outputs[0].data);
             const bool apply_sigmoid = ResolveV8ApplySigmoid(
-                data, num_boxes, kNumClasses, layout.channels_first, V8ClsActivation::Auto);
+                data, num_boxes, kNumClasses, layout.channels_first, v8_cls_activation_);
             for (int i = 0; i < num_boxes; ++i) {
                 const float score = layout.channels_first ? data[4 * num_boxes + i]
                                                           : data[i * num_channels + 4];
@@ -618,7 +640,7 @@ private:
                 fp32_decode_buf_[i] = Fp16ToFp32(data[i]);
             }
             const bool apply_sigmoid = ResolveV8ApplySigmoid(
-                fp32_decode_buf_.data(), num_boxes, kNumClasses, layout.channels_first, V8ClsActivation::Auto);
+                fp32_decode_buf_.data(), num_boxes, kNumClasses, layout.channels_first, v8_cls_activation_);
             for (int i = 0; i < num_boxes; ++i) {
                 const float score = layout.channels_first ? fp32_decode_buf_[4 * num_boxes + i]
                                                           : fp32_decode_buf_[i * num_channels + 4];
@@ -733,6 +755,8 @@ private:
     float conf_thresh_ = 0.25f;
     float nms_thresh_ = 0.45f;
     bool append_detections_ = false;
+    V8BoxFormat v8_box_format_ = V8BoxFormat::Auto;
+    V8ClsActivation v8_cls_activation_ = V8ClsActivation::Auto;
     int64_t infer_interval_ms_ = 0;
     int64_t last_infer_pts_ms_ = 0;
     DynamicRoiConfig dynamic_roi_;