bot: fetch update components

Seeed-Studio · Dec 25, 2024 · 9f42e0c · 9f42e0c
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commit 9f42e0c
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Showing 14 changed files with 1,136 additions and 60 deletions.
diff --git a/src/components/sscma-micro/sscma/core/engine/ma_engine_hailo.cpp b/src/components/sscma-micro/sscma/core/engine/ma_engine_hailo.cpp
@@ -207,6 +207,16 @@ ma_err_t EngineHailo::load(const string& model_path) {
                     tensor->shape.dims[2] = shape.features;
                     tensor->shape.dims[3] = shape.width;
                     break;
+                case HAILO_FORMAT_ORDER_NC:
+                    if (shape.width != 1 || shape.height != 1) {
+                        tensor->shape.dims[1] = shape.features;
+                        tensor->shape.dims[2] = shape.height;
+                        tensor->shape.dims[3] = shape.width;
+                        break;
+                    }
+                    tensor->shape.dims[1] = shape.features;
+                    tensor->shape.size    = 2;
+                    break;
                 default:
                     break;
             }

diff --git a/src/components/sscma-micro/sscma/core/ma_definations.h b/src/components/sscma-micro/sscma/core/ma_definations.h
@@ -42,6 +42,8 @@
 
 #define MA_STORAGE_KEY_TRIGGER_RULES   "trigger#rules"
 
+#define MA_STORAGE_KEY_WS_PORT           "ws#port"
+
 
 #define MA_AT_CMD_PREFIX               "AT+"
 #define MA_AT_CMD_QUERY                "?"

diff --git a/src/components/sscma-micro/sscma/core/ma_types.h b/src/components/sscma-micro/sscma/core/ma_types.h
@@ -97,7 +97,7 @@ typedef struct {
     } data;
     bool is_physical;  // For physical tensor
     bool is_variable;  // For constant tensor
-    void* external_handler = nullptr;
+    void* external_handler;
 } ma_tensor_t;
 
 typedef enum {
@@ -241,7 +241,8 @@ typedef enum {
     MA_TRANSPORT_MQTT    = 5,
     MA_TRANSPORT_TCP     = 6,
     MA_TRANSPORT_UDP     = 7,
-    MA_TRANSPORT_RTSP    = 8
+    MA_TRANSPORT_RTSP    = 8,
+    MA_TRANSPORT_WS     = 9
 } ma_transport_type_t;
 
 typedef enum {
@@ -283,7 +284,9 @@ typedef enum {
     MA_MODEL_TYPE_YOLO_WORLD  = 8u,
     MA_MODEL_TYPE_YOLO11      = 9u,
     MA_MODEL_TYPE_YOLO11_POSE = 10u,
-    MA_MODEL_TYPE_YOLO11_SEG = 11u,
+    MA_MODEL_TYPE_YOLO11_SEG  = 11u,
+    MA_MODEL_TYPE_YOLOV8_SGE  = 12u,
+    MA_MODEL_TYPE_RTMDET      = 13u
 } ma_model_type_t;
 
 typedef struct {
@@ -444,4 +447,4 @@ typedef struct in6_info_t {
 
 #endif
 
-#endif  // _MA_TYPES_H_
+#endif  // _MA_TYPES_H_
diff --git a/src/components/sscma-micro/sscma/core/math/ma_math_vectors.h b/src/components/sscma-micro/sscma/core/math/ma_math_vectors.h
@@ -1,15 +1,30 @@
 #ifndef _MA_MATH_VECTORS_H_
 #define _MA_MATH_VECTORS_H_
 
-#include <cstdint>
 #include <cstddef>
+#include <cstdint>
+
+#if MA_USE_LIB_XTENSOR
+#include <xtensor/xarray.hpp>
+#include <xtensor/xmath.hpp>
+#include <xtensor/xview.hpp>
+#endif
 
 namespace ma::math {
 
 void softmax(float* data, size_t size);
 
 void fastSoftmax(float* data, size_t size);
 
+#if MA_USE_LIB_XTENSOR
+template <typename QT>
+static void dequantizeValues1D(xt::xarray<float>& dequantized_outputs, int index, const xt::xarray<QT>& quantized_outputs, size_t dim1, float32_t qp_scale, float32_t qp_zp) {
+    for (size_t i = 0; i < dim1; ++i) {
+        dequantized_outputs(i) = (float(quantized_outputs(index, i)) - qp_zp) * qp_scale;
+    }
+}
+#endif
+
 }  // namespace ma::math
 
 #endif
diff --git a/src/components/sscma-micro/sscma/core/model/ma_model_classifier.cpp b/src/components/sscma-micro/sscma/core/model/ma_model_classifier.cpp
@@ -40,9 +40,7 @@ bool Classifier::isValid(Engine* engine) {
         return false;
     }
 
-    const auto& input_shape = engine->getInputShape(0);
-    const auto& output_shape{engine->getOutputShape(0)};
-
+    const auto input_shape = engine->getInputShape(0);
     int n = input_shape.dims[0], h = input_shape.dims[1], w = input_shape.dims[2], c = input_shape.dims[3];
     bool is_nhwc = c == 3 || c == 1;
 
@@ -52,17 +50,17 @@ bool Classifier::isValid(Engine* engine) {
     if (n != 1 || h < 32 || h % 32 != 0 || (c != 3 && c != 1))
         return false;
 
+    const auto output_shape = engine->getOutputShape(0);
+    if (output_shape.size != 2) {
+        return false;
+    }
 
     if (output_shape.dims[0] != 1 ||  // N = 1
         output_shape.dims[1] < 2      // C >= 2
     ) {
         return false;
     }
 
-    if (output_shape.size >= 3) {
-        return false;
-    }
-
     return true;
 }
 
@@ -91,32 +89,65 @@ ma_err_t Classifier::preprocess() {
 ma_err_t Classifier::postprocess() {
     results_.clear();
 
-    if (output_.type == MA_TENSOR_TYPE_S8) {
-        auto scale{output_.quant_param.scale};
-        auto zero_point{output_.quant_param.zero_point};
-        bool rescale{scale < 0.1f ? true : false};
-        auto* data = output_.data.s8;
+    switch (output_.type) {
+        case MA_TENSOR_TYPE_S8: {
+            auto scale{output_.quant_param.scale};
+            auto zero_point{output_.quant_param.zero_point};
+            bool rescale{scale < 0.1f ? true : false};
+            auto* data = output_.data.s8;
+            auto pred_l{output_.shape.dims[1]};
+
+            for (decltype(pred_l) i{0}; i < pred_l; ++i) {
+                auto score{static_cast<decltype(scale)>(data[i] - zero_point) * scale};
+                score = rescale ? score : score / 100.f;
+                if (score > threshold_score_)
+                    results_.emplace_front(ma_class_t{score, i});
+            }
+        } break;
+
+        case MA_TENSOR_TYPE_U8: {
+            auto scale{output_.quant_param.scale};
+            auto zero_point{output_.quant_param.zero_point};
+            bool rescale{scale < 0.1f ? true : false};
+            auto* data = output_.data.u8;
+            auto pred_l{output_.shape.dims[1]};
+
+            for (decltype(pred_l) i{0}; i < pred_l; ++i) {
+                auto score{static_cast<decltype(scale)>(data[i] - zero_point) * scale};
+                score = rescale ? score : score / 100.f;
+                if (score > threshold_score_)
+                    results_.emplace_front(ma_class_t{score, i});
+            }
+        } break;
+
+        case MA_TENSOR_TYPE_U16: {
+            auto scale{output_.quant_param.scale};
+            auto zero_point{output_.quant_param.zero_point};
+            bool rescale{scale < 0.1f ? true : false};
+            auto* data = output_.data.u16;
+            auto pred_l{output_.shape.dims[1]};
+
+            for (decltype(pred_l) i{0}; i < pred_l; ++i) {
+                auto score{static_cast<decltype(scale)>(data[i] - zero_point) * scale};
+                score = rescale ? score : score / 100.f;
+                if (score > threshold_score_)
+                    results_.emplace_front(ma_class_t{score, i});
+            }
+        } break;
+
+
+        case MA_TENSOR_TYPE_F32: {
+            auto* data = output_.data.f32;
+            auto pred_l{output_.shape.dims[1]};
+            for (decltype(pred_l) i{0}; i < pred_l; ++i) {
+                auto score{data[i]};
+                if (score > threshold_score_)
+                    results_.emplace_front(ma_class_t{score, i});
+            }
+        } break;
 
-        auto pred_l{output_.shape.dims[1]};
-
-        for (decltype(pred_l) i{0}; i < pred_l; ++i) {
-            auto score{static_cast<decltype(scale)>(data[i] - zero_point) * scale};
-            score = rescale ? score : score / 100.f;
-            if (score > threshold_score_)
-                results_.emplace_front(ma_class_t{score, i});
-        }
-    }
-    if (output_.type == MA_TENSOR_TYPE_F32) {
-        auto* data = output_.data.f32;
-        auto pred_l{output_.shape.dims[1]};
-        for (decltype(pred_l) i{0}; i < pred_l; ++i) {
-            auto score{data[i]};
-            if (score > threshold_score_)
-                results_.emplace_front(ma_class_t{score, i});
-        }
-
-    } else {
-        return MA_ENOTSUP;
+        default:
+            return MA_ENOTSUP;
     }
 
     results_.sort([](const ma_class_t& a, const ma_class_t& b) { return a.score > b.score; });

diff --git a/src/components/sscma-micro/sscma/core/model/ma_model_factory.cpp b/src/components/sscma-micro/sscma/core/model/ma_model_factory.cpp
@@ -37,6 +37,10 @@ Model* ModelFactory::create(Engine* engine, size_t algorithm_id) {
             if (YoloV8PoseHailo::isValid(engine)) {
                 return new YoloV8PoseHailo(engine);
             }
+
+            if (YoloV8SegHailo::isValid(engine)) {
+                return new YoloV8SegHailo(engine);
+            }
 #endif
             if (YoloV8Pose::isValid(engine)) {
                 return new YoloV8Pose(engine);
@@ -52,6 +56,11 @@ Model* ModelFactory::create(Engine* engine, size_t algorithm_id) {
                 return new NvidiaDet(engine);
             }
 
+        case MA_MODEL_TYPE_RTMDET:
+            if (RTMDet::isValid(engine)) {
+                return new RTMDet(engine);
+            }
+
         case MA_MODEL_TYPE_YOLO_WORLD:
             if (YoloWorld::isValid(engine)) {
                 return new YoloWorld(engine);

diff --git a/src/components/sscma-micro/sscma/core/model/ma_model_factory.h b/src/components/sscma-micro/sscma/core/model/ma_model_factory.h
@@ -21,6 +21,8 @@
 #include "ma_model_yolov8.h"
 #include "ma_model_yolov8_pose.h"
 #include "ma_model_yolov8_pose_hailo.h"
+#include "ma_model_yolov8_seg_hailo.h"
+#include "ma_model_rtmdet.h"
 
 namespace ma {