SDK release v1.48.2

edgeimpulse · Mar 18, 2024 · d6423f5 · d6423f5
1 parent afc5c7a
commit d6423f5
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diff --git a/EdgeImpulse.EI-SDK.pdsc b/EdgeImpulse.EI-SDK.pdsc
@@ -5,13 +5,16 @@
 	<name>EI-SDK</name>
 	<license>LICENSE-apache-2.0.txt</license>
 	<description>Edge Impulse SDK</description>
-	<url>https://github.com/edgeimpulse/edge-impulse-sdk-pack/releases/download/v1.48.1/</url>
+	<url>https://github.com/edgeimpulse/edge-impulse-sdk-pack/releases/download/v1.48.2/</url>
 	<supportContact>[email protected]</supportContact>
 	<repository type="git">https://github.com/edgeimpulse/edge-impulse-sdk-pack.git</repository>
 	<releases>
-		<release version="1.48.1" tag="v1.48.1" date="2024-03-14" url="https://github.com/edgeimpulse/edge-impulse-sdk-pack/releases/download/v1.48.1/EdgeImpulse.EI-SDK.1.48.1.pack">
+		<release version="1.48.2" tag="v1.48.2" date="2024-03-18" url="https://github.com/edgeimpulse/edge-impulse-sdk-pack/releases/download/v1.48.2/EdgeImpulse.EI-SDK.1.48.2.pack">
       		EI-SDK
     	</release>	
+		<release version="1.48.1" tag="v1.48.1" date="2024-03-14" url="https://github.com/edgeimpulse/edge-impulse-sdk-pack/releases/download/v1.48.1/EdgeImpulse.EI-SDK.1.48.1.pack">
+      		EI-SDK
+    	</release>
 		<release version="1.47.2" tag="v1.47.2" date="2024-03-12" url="https://github.com/edgeimpulse/edge-impulse-sdk-pack/releases/download/v1.47.2/EdgeImpulse.EI-SDK.1.47.2.pack">
       		EI-SDK
     	</release>
@@ -86,7 +89,7 @@
     </packages>
     </requirements>
 	<components>
-		<component Cclass="EdgeImpulse" Cgroup="SDK" Cversion="1.48.1">
+		<component Cclass="EdgeImpulse" Cgroup="SDK" Cversion="1.48.2">
 			<description>Edge Impulse SDK</description>	
 				<!-- short component description -->
 				<files>

diff --git a/EdgeImpulse.pidx b/EdgeImpulse.pidx
@@ -2,8 +2,8 @@
 <index schemaVersion="1.0.0" xs:noNamespaceSchemaLocation="PackIndex.xsd" xmlns:xs="http://www.w3.org/2001/XMLSchema-instance">
   <vendor>EdgeImpulse</vendor>
   <url>https://raw.githubusercontent.com/edgeimpulse/edge-impulse-sdk-pack/main/</url>
-  <timestamp>2024-03-14 14:16:31</timestamp>
+  <timestamp>2024-03-18 16:38:05</timestamp>
   <pindex>
-    <pdsc url="https://github.com/edgeimpulse/edge-impulse-sdk-pack/releases/download/v1.48.1/" vendor="EdgeImpulse" name="EI-SDK" version="1.48.1"/>
+    <pdsc url="https://github.com/edgeimpulse/edge-impulse-sdk-pack/releases/download/v1.48.2/" vendor="EdgeImpulse" name="EI-SDK" version="1.48.2"/>
   </pindex>
 </index>
diff --git a/edgeimpulse/edge-impulse-sdk/classifier/ei_fill_result_struct.h b/edgeimpulse/edge-impulse-sdk/classifier/ei_fill_result_struct.h
diff --git a/edgeimpulse/edge-impulse-sdk/classifier/ei_model_types.h b/edgeimpulse/edge-impulse-sdk/classifier/ei_model_types.h
@@ -164,6 +164,8 @@ typedef struct {
     uint8_t output_data_tensor;
     uint8_t output_labels_tensor;
     uint8_t output_score_tensor;
+    /* object detection and visual AD */
+    float threshold;
     /* tflite graph params */
     bool quantized;
     bool compiled;
@@ -218,10 +220,7 @@ typedef struct ei_impulse {
     ei_model_dsp_t *dsp_blocks;
 
     /* object detection */
-    bool object_detection;
     uint16_t object_detection_count;
-    float object_detection_threshold;
-    int8_t object_detection_last_layer;
     uint32_t fomo_output_size;
     uint32_t tflite_output_features_count;
 

diff --git a/edgeimpulse/edge-impulse-sdk/classifier/inferencing_engines/akida.h b/edgeimpulse/edge-impulse-sdk/classifier/inferencing_engines/akida.h
@@ -353,7 +353,7 @@ EI_IMPULSE_ERROR run_nn_inference(
     std::vector<float> potentials_v;// = potentials.cast<std::vector<float>>();
 
     // TODO: output conversion depending on output shape?
-    if (impulse->object_detection == false) {
+    if (block_config->object_detection == false) {
         potentials_v = potentials.squeeze().cast<std::vector<float>>();
     }
     else {
@@ -396,11 +396,12 @@ EI_IMPULSE_ERROR run_nn_inference(
     engine_info << "Power consumption: " << std::fixed << std::setprecision(2) << active_power << " mW\n";
     engine_info << "Inferences per second: " << (1000000 / result->timing.classification_us);
 
-    if (impulse->object_detection) {
-        switch (impulse->object_detection_last_layer) {
+    if (block_config->object_detection) {
+        switch (block_config->object_detection_last_layer) {
             case EI_CLASSIFIER_LAST_LAYER_FOMO: {
                 fill_res = fill_result_struct_f32_fomo(
                     impulse,
+                    block_config,
                     result,
                     potentials_v.data(),
                     impulse->fomo_output_size,
@@ -409,17 +410,17 @@ EI_IMPULSE_ERROR run_nn_inference(
             }
             case EI_CLASSIFIER_LAST_LAYER_SSD: {
                 ei_printf("ERR: MobileNet SSD models are not implemented for Akida (%d)\n",
-                    impulse->object_detection_last_layer);
+                    block_config->object_detection_last_layer);
                 return EI_IMPULSE_UNSUPPORTED_INFERENCING_ENGINE;
             }
             case EI_CLASSIFIER_LAST_LAYER_YOLOV5: {
                 ei_printf("ERR: YOLO v5 models are not implemented for Akida (%d)\n",
-                    impulse->object_detection_last_layer);
+                    block_config->object_detection_last_layer);
                 return EI_IMPULSE_UNSUPPORTED_INFERENCING_ENGINE;
             }
             default: {
                 ei_printf("ERR: Unsupported object detection last layer (%d)\n",
-                    impulse->object_detection_last_layer);
+                    block_config->object_detection_last_layer);
                 return EI_IMPULSE_UNSUPPORTED_INFERENCING_ENGINE;
             }
         }
@@ -547,6 +548,9 @@ __attribute__((unused)) int extract_tflite_features(signal_t *signal, matrix_t *
         .output_data_tensor = 0,
         .output_labels_tensor = 255,
         .output_score_tensor = 255,
+        .threshold = 0,
+        .quantized = 0,
+        .compiled = 1,
         .graph_config = &ei_config_tflite_graph_0
     };
 

diff --git a/edgeimpulse/edge-impulse-sdk/classifier/inferencing_engines/anomaly.h b/edgeimpulse/edge-impulse-sdk/classifier/inferencing_engines/anomaly.h
@@ -214,6 +214,7 @@ EI_IMPULSE_ERROR run_gmm_anomaly(
         .output_data_tensor = 0,
         .output_labels_tensor = 0,
         .output_score_tensor = 0,
+        .threshold = block_config->anomaly_threshold,
         .quantized = 0,
         .compiled = 0,
         .graph_config = block_config->graph_config

diff --git a/edgeimpulse/edge-impulse-sdk/classifier/inferencing_engines/drpai.h b/edgeimpulse/edge-impulse-sdk/classifier/inferencing_engines/drpai.h
@@ -455,10 +455,12 @@ EI_IMPULSE_ERROR drpai_close(uint32_t input_frame_size) {
 #if ((EI_CLASSIFIER_OBJECT_DETECTION == 1) && (EI_CLASSIFIER_OBJECT_DETECTION_LAST_LAYER == EI_CLASSIFIER_LAST_LAYER_YOLOV5_V5_DRPAI))
 EI_IMPULSE_ERROR drpai_run_yolov5_postprocessing(
     const ei_impulse_t *impulse,
+    ei_learning_block_config_tflite_graph_t *block_config,
     signal_t *signal,
     ei_impulse_result_t *result,
     bool debug = false)
 {
+
     static std::unique_ptr<tflite::FlatBufferModel> model = nullptr;
     static std::unique_ptr<tflite::Interpreter> interpreter = nullptr;
 
@@ -564,7 +566,7 @@ EI_IMPULSE_ERROR drpai_run_yolov5_postprocessing(
     // }
     // printf("\n");
 
-    return fill_result_struct_f32_yolov5(impulse, result, 5, out_data, out_size);
+    return fill_result_struct_f32_yolov5(impulse, block_config, result, 5, out_data, out_size);
 }
 #endif
 
@@ -602,6 +604,8 @@ EI_IMPULSE_ERROR run_nn_inference_image_quantized(
     void *config_ptr,
     bool debug = false)
 {
+    ei_learning_block_config_tflite_graph_t *block_config = (ei_learning_block_config_tflite_graph_t*)config_ptr;
+
     // this needs to be changed for multi-model, multi-impulse
     static bool first_run = true;
     uint64_t ctx_start_us;
@@ -678,8 +682,8 @@ EI_IMPULSE_ERROR run_nn_inference_image_quantized(
 
     EI_IMPULSE_ERROR fill_res = EI_IMPULSE_OK;
 
-    if (impulse->object_detection) {
-        switch (impulse->object_detection_last_layer) {
+    if (block_config->object_detection) {
+        switch (block_config->object_detection_last_layer) {
             case EI_CLASSIFIER_LAST_LAYER_FOMO: {
                 if (debug) {
                     ei_printf("DEBUG: raw drpai output");
@@ -693,6 +697,7 @@ EI_IMPULSE_ERROR run_nn_inference_image_quantized(
 
                 fill_res = fill_result_struct_f32_fomo(
                     impulse,
+                    block_config,
                     result,
                     drpai_output_buf,
                     impulse->fomo_output_size,
@@ -701,7 +706,7 @@ EI_IMPULSE_ERROR run_nn_inference_image_quantized(
             }
             case EI_CLASSIFIER_LAST_LAYER_SSD: {
                 ei_printf("ERR: MobileNet SSD models are not implemented for DRP-AI (%d)\n",
-                    impulse->object_detection_last_layer);
+                    block_config->object_detection_last_layer);
                 return EI_IMPULSE_UNSUPPORTED_INFERENCING_ENGINE;
             }
             case EI_CLASSIFIER_LAST_LAYER_YOLOV5_V5_DRPAI: {
@@ -723,7 +728,7 @@ EI_IMPULSE_ERROR run_nn_inference_image_quantized(
 
 #if ((EI_CLASSIFIER_OBJECT_DETECTION == 1) && (EI_CLASSIFIER_OBJECT_DETECTION_LAST_LAYER == EI_CLASSIFIER_LAST_LAYER_YOLOV5_V5_DRPAI))
                   // do post processing
-                  fill_res = drpai_run_yolov5_postprocessing(impulse, signal, result, debug);
+                  fill_res = drpai_run_yolov5_postprocessing(impulse, block_config, signal, result, debug);
 #endif
 
                 #endif
@@ -732,7 +737,7 @@ EI_IMPULSE_ERROR run_nn_inference_image_quantized(
             }
             default: {
                 ei_printf("ERR: Unsupported object detection last layer (%d)\n",
-                    impulse->object_detection_last_layer);
+                    block_config->object_detection_last_layer);
                 return EI_IMPULSE_UNSUPPORTED_INFERENCING_ENGINE;
             }
         }

diff --git a/edgeimpulse/edge-impulse-sdk/classifier/inferencing_engines/memryx.h b/edgeimpulse/edge-impulse-sdk/classifier/inferencing_engines/memryx.h
@@ -208,6 +208,8 @@ EI_IMPULSE_ERROR run_nn_inference(
     void *config_ptr,
     bool debug = false)
 {
+    ei_learning_block_config_tflite_graph_t *block_config = (ei_learning_block_config_tflite_graph_t*)config_ptr;
+
     memx_status status = MEMX_STATUS_OK;
     int32_t ifmap_height, ifmap_width, ifmap_channel_number, ifmap_format;
     int32_t ofmap_height, ofmap_width, ofmap_channel_number, ofmap_format;
@@ -311,12 +313,13 @@ EI_IMPULSE_ERROR run_nn_inference(
     tflite::reference_ops::Softmax(dummy_params, softmax_shape, ofmap, softmax_shape, ofmap);
 
     // handle inference outputs
-    if (impulse->object_detection) {
-        switch (impulse->object_detection_last_layer) {
+    if (block_config->object_detection) {
+        switch (block_config->object_detection_last_layer) {
             case EI_CLASSIFIER_LAST_LAYER_FOMO: {
                 ei_printf("FOMO executed on Memryx\n");
                 fill_result_struct_f32_fomo(
                     impulse,
+                    block_config,
                     result,
                     ofmap,
                     impulse->fomo_output_size,
@@ -329,7 +332,7 @@ EI_IMPULSE_ERROR run_nn_inference(
             }
             default: {
                 ei_printf("ERR: Unsupported object detection last layer (%d)\n",
-                    impulse->object_detection_last_layer);
+                    block_config->object_detection_last_layer);
                 return EI_IMPULSE_UNSUPPORTED_INFERENCING_ENGINE;
             }
         }
@@ -353,6 +356,8 @@ EI_IMPULSE_ERROR run_nn_inference(
     void *config_ptr,
     bool debug = false)
 {
+    ei_learning_block_config_tflite_graph_t *block_config = (ei_learning_block_config_tflite_graph_t*)config_ptr;
+
     // init Python embedded interpreter (should be called once!)
     static py::scoped_interpreter guard{};
 
@@ -420,7 +425,7 @@ EI_IMPULSE_ERROR run_nn_inference(
 
     potentials = outputs.squeeze().cast<py::array_t<float>>();
 
-    if (impulse->object_detection == false) {
+    if (block_config->object_detection == false) {
         potentials_v = outputs.squeeze().cast<std::vector<float>>();
     }
     else {
@@ -439,12 +444,13 @@ EI_IMPULSE_ERROR run_nn_inference(
         ei_printf("Memryx raw output:\n%s\n", ret_str.c_str());
     }
 
-    if (impulse->object_detection) {
-        switch (impulse->object_detection_last_layer) {
+    if (block_config->object_detection) {
+        switch (block_config->object_detection_last_layer) {
             case EI_CLASSIFIER_LAST_LAYER_FOMO: {
                 ei_printf("FOMO executed on Memryx\n");
                 fill_result_struct_f32_fomo(
                     impulse,
+                    block_config,
                     result,
                     potentials_v.data(),
                     impulse->fomo_output_size,

diff --git a/edgeimpulse/edge-impulse-sdk/classifier/inferencing_engines/onnx_tidl.h b/edgeimpulse/edge-impulse-sdk/classifier/inferencing_engines/onnx_tidl.h
@@ -347,6 +347,7 @@ static EI_IMPULSE_ERROR inference_onnx_setup(
  * @return  EI_IMPULSE_OK if successful
  */
 static EI_IMPULSE_ERROR inference_onnx_run(const ei_impulse_t *impulse,
+    void *config_ptr,
     uint64_t ctx_start_us,
     std::vector<Ort::Value>* input_tensors,
     std::vector<Ort::Value>* output_tensors,
@@ -356,6 +357,8 @@ static EI_IMPULSE_ERROR inference_onnx_run(const ei_impulse_t *impulse,
     ei_impulse_result_t *result,
     bool debug) {
 
+    ei_learning_block_config_tflite_graph_t *block_config = (ei_learning_block_config_tflite_graph_t*)config_ptr;
+
     session->Run(*run_options, *binding);
 
     uint64_t ctx_end_us = ei_read_timer_us();
@@ -381,8 +384,8 @@ static EI_IMPULSE_ERROR inference_onnx_run(const ei_impulse_t *impulse,
     EI_IMPULSE_ERROR fill_res = EI_IMPULSE_OK;
 
     // NOTE: for now only yolox object detection supported
-    if (impulse->object_detection) {
-        switch (impulse->object_detection_last_layer) {
+    if (block_config->object_detection) {
+        switch (block_config->object_detection_last_layer) {
             case EI_CLASSIFIER_LAST_LAYER_YOLOX: {
                 #if EI_CLASSIFIER_TFLITE_OUTPUT_QUANTIZED == 1
                     ei_printf("ERR: YOLOX does not support quantized inference\n");
@@ -399,6 +402,7 @@ static EI_IMPULSE_ERROR inference_onnx_run(const ei_impulse_t *impulse,
                     }
                     fill_res = fill_result_struct_f32_yolox_detect(
                         impulse,
+                        block_config,
                         result,
                         (float*)out_data,
                         output_tensor_features_count);
@@ -407,7 +411,7 @@ static EI_IMPULSE_ERROR inference_onnx_run(const ei_impulse_t *impulse,
             }
             default: {
                 ei_printf("ERR: Unsupported object detection last layer (%d)\n",
-                    impulse->object_detection_last_layer);
+                    block_config->object_detection_last_layer);
                 break;
             }
         }
@@ -549,6 +553,7 @@ EI_IMPULSE_ERROR run_nn_inference(
 
     ctx_start_us = ei_read_timer_us();
     EI_IMPULSE_ERROR run_res = inference_onnx_run(impulse,
+        config_ptr,
         ctx_start_us,
         &input_tensors,
         &output_tensors,
@@ -678,6 +683,7 @@ EI_IMPULSE_ERROR run_nn_inference_image_quantized(
 
     ctx_start_us = ei_read_timer_us();
     EI_IMPULSE_ERROR run_res = inference_onnx_run(impulse,
+        config_ptr,
         ctx_start_us,
         &input_tensors,
         &output_tensors,