From 96745d665b9f063a62d5798d76cb6a90da3f23f5 Mon Sep 17 00:00:00 2001
From: Dmitry Kurtaev <dmitry.kurtaev@gmail.com>
Date: Wed, 11 Jun 2025 18:59:24 +0300
Subject: [PATCH 1/6] Adopt TFLite fixes for new engine

---
 modules/dnn/src/tflite/tflite_importer.cpp | 20 +++++++++++++++--
 modules/dnn/test/test_tflite_importer.cpp  | 26 +++++++++++-----------
 2 files changed, 31 insertions(+), 15 deletions(-)

diff --git a/modules/dnn/src/tflite/tflite_importer.cpp b/modules/dnn/src/tflite/tflite_importer.cpp
index e44dd669270b..5a5e7e3aded4 100644
--- a/modules/dnn/src/tflite/tflite_importer.cpp
+++ b/modules/dnn/src/tflite/tflite_importer.cpp
@@ -310,6 +310,10 @@ void TFLiteImporter::populateNet()
             }
             throw;
         }
+        if (op_outputs->Get(0) == 194)
+        {
+            break;
+        }
     }
     if (newEngine)
     {
@@ -488,11 +492,13 @@ void TFLiteImporter::parseConvolution(const Operator& op, const std::string& opc
     layerParams.type = "Convolution";
 
     int inpId = op.inputs()->Get(0);
+    bool additionalPreLayer = false;
     if (layouts[inpId] == DNN_LAYOUT_UNKNOWN && modelTensors->Get(inpId)->shape()->size() == 4)
     {
         int permId = addPermuteLayer({0, 3, 1, 2}, layerParams.name + "/permute_input", layerIds[inpId], isInt8(op) ? CV_8S : CV_32F, op.inputs()->Get(0));  // NHWC -> NCHW
         layerIds[inpId] = std::make_pair(permId, 0);
         layouts[op.outputs()->Get(0)] = DNN_LAYOUT_NHWC;
+        additionalPreLayer = true;
     }
 
     auto options = reinterpret_cast<const Conv2DOptions*>(op.builtin_options());
@@ -554,7 +560,7 @@ void TFLiteImporter::parseConvolution(const Operator& op, const std::string& opc
 
     std::string fusedActivationType = EnumNameActivationFunctionType(options->fused_activation_function());
     bool haveFusedActivation = fusedActivationType != "NONE";
-    addLayer(layerParams, op, false, haveFusedActivation);
+    addLayer(layerParams, op, additionalPreLayer, haveFusedActivation);
     parseFusedActivation(op, options->fused_activation_function());
 }
 
@@ -1083,7 +1089,17 @@ int TFLiteImporter::addConstLayer(const Mat& blob, const std::string& name)
 {
     LayerParams lp;
     lp.blobs.push_back(blob.u ? blob : blob.clone());  // some tensors are owned by OpenCV
-    return dstNet.addLayer(name, "Const", lp);
+    if (newEngine)
+    {
+        lp.type = "Const";
+        lp.name = name;
+        addLayer(lp, {}, {name});
+        return -1;
+    }
+    else
+    {
+        return dstNet.addLayer(name, "Const", lp);
+    }
 }
 
 void TFLiteImporter::parseDeconvolution(const Operator& op, const std::string& opcode, LayerParams& layerParams) {
diff --git a/modules/dnn/test/test_tflite_importer.cpp b/modules/dnn/test/test_tflite_importer.cpp
index 52e5ecef275e..1b5ca8b03334 100644
--- a/modules/dnn/test/test_tflite_importer.cpp
+++ b/modules/dnn/test/test_tflite_importer.cpp
@@ -55,18 +55,18 @@ void Test_TFLite::testModel(Net& net, const std::string& modelName, const Mat& i
     std::vector<Mat> outs;
     net.forward(outs, outNames);
 
-    ASSERT_EQ(outs.size(), outNames.size());
-    for (int i = 0; i < outNames.size(); ++i) {
-        std::replace(outNames[i].begin(), outNames[i].end(), ':', '_');
-        Mat ref = blobFromNPY(findDataFile(format("dnn/tflite/%s_out_%s.npy", modelName.c_str(), outNames[i].c_str())));
-        // A workaround solution for the following cases due to inconsistent shape definitions.
-        // The details please see: https://github.com/opencv/opencv/pull/25297#issuecomment-2039081369
-        if (modelName == "face_landmark" || modelName == "selfie_segmentation") {
-            ref = ref.reshape(1, 1);
-            outs[i] = outs[i].reshape(1, 1);
-        }
-        normAssert(ref, outs[i], outNames[i].c_str(), l1, lInf);
-    }
+    // ASSERT_EQ(outs.size(), outNames.size());
+    // for (int i = 0; i < outNames.size(); ++i) {
+    //     std::replace(outNames[i].begin(), outNames[i].end(), ':', '_');
+    //     Mat ref = blobFromNPY(findDataFile(format("dnn/tflite/%s_out_%s.npy", modelName.c_str(), outNames[i].c_str())));
+    //     // A workaround solution for the following cases due to inconsistent shape definitions.
+    //     // The details please see: https://github.com/opencv/opencv/pull/25297#issuecomment-2039081369
+    //     if (modelName == "face_landmark" || modelName == "selfie_segmentation") {
+    //         ref = ref.reshape(1, 1);
+    //         outs[i] = outs[i].reshape(1, 1);
+    //     }
+    //     normAssert(ref, outs[i], outNames[i].c_str(), l1, lInf);
+    // }
 }
 
 void Test_TFLite::testModel(const std::string& modelName, const Mat& input, double l1, double lInf)
@@ -283,7 +283,7 @@ TEST_P(Test_TFLite, StridedSlice) {
     testLayer("strided_slice");
 }
 
-TEST_P(Test_TFLite, DISABLED_face_blendshapes)
+TEST_P(Test_TFLite, face_blendshapes)
 {
     Mat inp = blobFromNPY(findDataFile("dnn/tflite/face_blendshapes_inp.npy"));
     testModel("face_blendshapes", inp);

From 30a084da62b6cc3d7a8798908ee967154c97615b Mon Sep 17 00:00:00 2001
From: Dmitry Kurtaev <dmitry.kurtaev@gmail.com>
Date: Thu, 12 Jun 2025 15:54:18 +0300
Subject: [PATCH 2/6] model infered

---
 modules/dnn/src/net_impl2.cpp              |  5 ++
 modules/dnn/src/tflite/tflite_importer.cpp | 86 +++++++++-------------
 2 files changed, 41 insertions(+), 50 deletions(-)

diff --git a/modules/dnn/src/net_impl2.cpp b/modules/dnn/src/net_impl2.cpp
index 37f172133964..948851e0f79d 100644
--- a/modules/dnn/src/net_impl2.cpp
+++ b/modules/dnn/src/net_impl2.cpp
@@ -333,7 +333,12 @@ void Net::Impl::allocateLayerOutputs(
     tempShapes.clear();
     tempTypes.clear();
     layer->getMemoryShapes(inpShapes, (int)noutputs, outShapes, tempShapes);
+    std::cout << layer->name << " " << layer->type << std::endl;
+    if (inpTypes.size() > 0)
+        std::cout << " in " << inpTypes[0] << std::endl;
     layer->getTypes(inpTypes, (int)noutputs, (int)tempShapes.size(), outTypes, tempTypes);
+    if (outTypes.size() > 0)
+        std::cout << " out " << outTypes[0] << std::endl;
     CV_Assert(tempShapes.size() == tempTypes.size());
     CV_Assert(outShapes.size() == outTypes.size());
     CV_Assert(outShapes.size() == noutputs);
diff --git a/modules/dnn/src/tflite/tflite_importer.cpp b/modules/dnn/src/tflite/tflite_importer.cpp
index 5a5e7e3aded4..908ab181025f 100644
--- a/modules/dnn/src/tflite/tflite_importer.cpp
+++ b/modules/dnn/src/tflite/tflite_importer.cpp
@@ -86,7 +86,7 @@ class TFLiteImporter {
     int addReshapeLayer(const std::vector<int>& shape, int axis, int num_axes,
                         const std::string& name, const std::pair<int, int>& inpId, int dtype, int inpTensorId);
     int addFlattenLayer(int axis, int end_axis, const std::string& name, const std::pair<int, int>& inpId, int dtype, int outTensorId);
-    int addConstLayer(const Mat& data, const std::string& name);
+    void addConstLayer(const Mat& data, int tensorIdx);
 
     inline bool isInt8(const Operator& op);
     inline void getQuantParams(const Operator& op, float& inpScale, int& inpZero, float& outScale, int& outZero);
@@ -310,10 +310,10 @@ void TFLiteImporter::populateNet()
             }
             throw;
         }
-        if (op_outputs->Get(0) == 194)
-        {
-            break;
-        }
+        // if (op_outputs->Get(0) == 71)
+        // {
+        //     break;
+        // }
     }
     if (newEngine)
     {
@@ -726,8 +726,7 @@ void TFLiteImporter::parseEltwise(const Operator& op, const std::string& opcode,
         if (layouts[op.inputs()->Get(0)] == DNN_LAYOUT_NHWC && blob.dims == 1) {
             blob = blob.reshape(1, {1, (int)blob.total(), 1, 1});
         }
-        int constId = addConstLayer(blob, modelTensors->Get(idx)->name()->str());
-        layerIds[idx] = std::make_pair(constId, 0);
+        addConstLayer(blob, idx);
     }
 
 
@@ -736,18 +735,18 @@ void TFLiteImporter::parseEltwise(const Operator& op, const std::string& opcode,
     addLayer(layerParams, op, false, haveFusedActivation);
     parseFusedActivation(op, activ);
 
-    // Layers that split on multiple operations
-    if (opcode == "SQUARED_DIFFERENCE") {
-        LayerParams lp;
-        lp.set("power", 2);
-        int id = dstNet.addLayerToPrev(layerParams.name + "/square", "Power", isOpInt8 ? CV_8S : CV_32F, lp);
-        layerIds[op.outputs()->Get(0)] = std::make_pair(id, 0);
-    }
-    else if (opcode == "RSQRT") {
-        LayerParams lp;
-        int id = dstNet.addLayerToPrev(layerParams.name + "/inv", "Reciprocal", isOpInt8 ? CV_8S : CV_32F, lp);
-        layerIds[op.outputs()->Get(0)] = std::make_pair(id, 0);
-    }
+    // // Layers that split on multiple operations
+    // if (opcode == "SQUARED_DIFFERENCE") {
+    //     LayerParams lp;
+    //     lp.set("power", 2);
+    //     int id = dstNet.addLayerToPrev(layerParams.name + "/square", "Power", isOpInt8 ? CV_8S : CV_32F, lp);
+    //     layerIds[op.outputs()->Get(0)] = std::make_pair(id, 0);
+    // }
+    // else if (opcode == "RSQRT") {
+    //     LayerParams lp;
+    //     int id = dstNet.addLayerToPrev(layerParams.name + "/inv", "Reciprocal", isOpInt8 ? CV_8S : CV_32F, lp);
+    //     layerIds[op.outputs()->Get(0)] = std::make_pair(id, 0);
+    // }
 }
 
 void TFLiteImporter::parsePooling(const Operator& op, const std::string& opcode, LayerParams& layerParams) {
@@ -872,8 +871,7 @@ void TFLiteImporter::parseConcat(const Operator& op, const std::string& opcode,
             transposeND(blob, {0, 3, 1, 2}, nchwBlob);
             blob = nchwBlob;
         }
-        int constId = addConstLayer(blob, modelTensors->Get(idx)->name()->str());
-        layerIds[idx] = std::make_pair(constId, 0);
+        addConstLayer(blob, idx);
     }
 
     std::string fusedActivationType = EnumNameActivationFunctionType(options->fused_activation_function());
@@ -1085,20 +1083,23 @@ int TFLiteImporter::addFlattenLayer(int axis, int end_axis, const std::string& n
     }
 }
 
-int TFLiteImporter::addConstLayer(const Mat& blob, const std::string& name)
+void TFLiteImporter::addConstLayer(const Mat& blob, int tensorIdx)
 {
+    const std::string& name = modelTensors->Get(tensorIdx)->name()->str();
     LayerParams lp;
     lp.blobs.push_back(blob.u ? blob : blob.clone());  // some tensors are owned by OpenCV
+    std::cout << "add const " << name << std::endl;
     if (newEngine)
     {
         lp.type = "Const";
         lp.name = name;
         addLayer(lp, {}, {name});
-        return -1;
+        layerIds[tensorIdx] = std::make_pair(-1, -1);
     }
     else
     {
-        return dstNet.addLayer(name, "Const", lp);
+        int constId = dstNet.addLayer(name, "Const", lp);
+        layerIds[tensorIdx] = std::make_pair(constId, 0);
     }
 }
 
@@ -1239,17 +1240,17 @@ void TFLiteImporter::parseStridedSlice(const Operator& op, const std::string& op
         layerParams.name += "/slice";
     }
 
-    addLayer(layerParams, op);
+    addLayer(layerParams, op, false, false);
 
-    for (int axis = 0; axis < num; ++axis)
-    {
-        if (!(shrinkMask & (1 << axis)))
-            continue;
-        std::string name = (axis == lastShrinkAxis) ? layerName : format("%s/shrink_axis_%d", layerName.c_str(), axis);
-        int layerId = addFlattenLayer(axis, axis + 1, name,
-            layerIds[op.outputs()->Get(0)], isInt8(op) ? CV_8S : CV_32F, op.inputs()->Get(0));
-        layerIds[op.inputs()->Get(0)] = std::make_pair(layerId, 0);
-    }
+    // for (int axis = 0; axis < num; ++axis)
+    // {
+    //     if (!(shrinkMask & (1 << axis)))
+    //         continue;
+    //     std::string name = (axis == lastShrinkAxis) ? layerName : format("%s/shrink_axis_%d", layerName.c_str(), axis);
+    //     int layerId = addFlattenLayer(axis, axis + 1, name,
+    //         layerIds[op.outputs()->Get(0)], isInt8(op) ? CV_8S : CV_32F, op.inputs()->Get(0));
+    //     layerIds[op.inputs()->Get(0)] = std::make_pair(layerId, 0);
+    // }
 }
 
 void TFLiteImporter::parseFullyConnected(const Operator& op, const std::string& opcode, LayerParams& layerParams) {
@@ -1344,22 +1345,7 @@ void TFLiteImporter::parseDetectionPostProcess(const Operator& op, const std::st
         layerParams.set("variance_encoded_in_target", true);
     }
 
-    LayerParams priorsLP;
-    priorsLP.name = layerParams.name + "/priors";
-    priorsLP.type = "Const";
-    priorsLP.blobs.resize(1, priors);
-
-    if (newEngine)
-    {
-        std::string outTensorName = modelTensors->Get(op.inputs()->Get(2))->name()->str();
-        addLayer(priorsLP, {}, {outTensorName});
-        layerIds[op.inputs()->Get(2)] = std::make_pair(-1, -1);
-    }
-    else
-    {
-        int priorsId = dstNet.addLayer(priorsLP.name, priorsLP.type, priorsLP);
-        layerIds[op.inputs()->Get(2)] = std::make_pair(priorsId, 0);
-    }
+    addConstLayer(priors, op.inputs()->Get(2));
     addLayer(layerParams, op);
 }
 

From e12d7db7634468ad53ca8de64be273a2ddcb0516 Mon Sep 17 00:00:00 2001
From: Dmitry Kurtaev <dmitry.kurtaev@gmail.com>
Date: Thu, 12 Jun 2025 16:27:15 +0300
Subject: [PATCH 3/6] Enable test

---
 modules/dnn/src/net_impl2.cpp              |  5 ---
 modules/dnn/src/tflite/tflite_importer.cpp | 37 ++++++++++++----------
 modules/dnn/test/test_tflite_importer.cpp  | 24 +++++++-------
 3 files changed, 33 insertions(+), 33 deletions(-)

diff --git a/modules/dnn/src/net_impl2.cpp b/modules/dnn/src/net_impl2.cpp
index 948851e0f79d..37f172133964 100644
--- a/modules/dnn/src/net_impl2.cpp
+++ b/modules/dnn/src/net_impl2.cpp
@@ -333,12 +333,7 @@ void Net::Impl::allocateLayerOutputs(
     tempShapes.clear();
     tempTypes.clear();
     layer->getMemoryShapes(inpShapes, (int)noutputs, outShapes, tempShapes);
-    std::cout << layer->name << " " << layer->type << std::endl;
-    if (inpTypes.size() > 0)
-        std::cout << " in " << inpTypes[0] << std::endl;
     layer->getTypes(inpTypes, (int)noutputs, (int)tempShapes.size(), outTypes, tempTypes);
-    if (outTypes.size() > 0)
-        std::cout << " out " << outTypes[0] << std::endl;
     CV_Assert(tempShapes.size() == tempTypes.size());
     CV_Assert(outShapes.size() == outTypes.size());
     CV_Assert(outShapes.size() == noutputs);
diff --git a/modules/dnn/src/tflite/tflite_importer.cpp b/modules/dnn/src/tflite/tflite_importer.cpp
index 908ab181025f..fe8f626f80e4 100644
--- a/modules/dnn/src/tflite/tflite_importer.cpp
+++ b/modules/dnn/src/tflite/tflite_importer.cpp
@@ -310,10 +310,6 @@ void TFLiteImporter::populateNet()
             }
             throw;
         }
-        // if (op_outputs->Get(0) == 71)
-        // {
-        //     break;
-        // }
     }
     if (newEngine)
     {
@@ -1088,7 +1084,6 @@ void TFLiteImporter::addConstLayer(const Mat& blob, int tensorIdx)
     const std::string& name = modelTensors->Get(tensorIdx)->name()->str();
     LayerParams lp;
     lp.blobs.push_back(blob.u ? blob : blob.clone());  // some tensors are owned by OpenCV
-    std::cout << "add const " << name << std::endl;
     if (newEngine)
     {
         lp.type = "Const";
@@ -1235,22 +1230,32 @@ void TFLiteImporter::parseStridedSlice(const Operator& op, const std::string& op
             lastShrinkAxis = axis;
     }
     std::string layerName = layerParams.name;
-    if (lastShrinkAxis != -1)
+    if (!newEngine && lastShrinkAxis != -1)
     {
         layerParams.name += "/slice";
     }
 
-    addLayer(layerParams, op, false, false);
+    addLayer(layerParams, op, false, lastShrinkAxis != -1);
 
-    // for (int axis = 0; axis < num; ++axis)
-    // {
-    //     if (!(shrinkMask & (1 << axis)))
-    //         continue;
-    //     std::string name = (axis == lastShrinkAxis) ? layerName : format("%s/shrink_axis_%d", layerName.c_str(), axis);
-    //     int layerId = addFlattenLayer(axis, axis + 1, name,
-    //         layerIds[op.outputs()->Get(0)], isInt8(op) ? CV_8S : CV_32F, op.inputs()->Get(0));
-    //     layerIds[op.inputs()->Get(0)] = std::make_pair(layerId, 0);
-    // }
+    for (int axis = 0; axis < num; ++axis)
+    {
+        if (!(shrinkMask & (1 << axis)))
+            continue;
+        if (newEngine)
+        {
+            if (axis != lastShrinkAxis)
+                CV_Error(Error::StsNotImplemented, "Multiple axes shrink in new engine");
+            addFlattenLayer(axis, axis + 1, layerName,
+                layerIds[op.outputs()->Get(0)], isInt8(op) ? CV_8S : CV_32F, op.outputs()->Get(0));
+        }
+        else
+        {
+            std::string name = (axis == lastShrinkAxis) ? layerName : format("%s/shrink_axis_%d", layerName.c_str(), axis);
+            int layerId = addFlattenLayer(axis, axis + 1, name,
+                layerIds[op.outputs()->Get(0)], isInt8(op) ? CV_8S : CV_32F, op.inputs()->Get(0));
+            layerIds[op.inputs()->Get(0)] = std::make_pair(layerId, 0);
+        }
+    }
 }
 
 void TFLiteImporter::parseFullyConnected(const Operator& op, const std::string& opcode, LayerParams& layerParams) {
diff --git a/modules/dnn/test/test_tflite_importer.cpp b/modules/dnn/test/test_tflite_importer.cpp
index 1b5ca8b03334..b4e89ee46cdd 100644
--- a/modules/dnn/test/test_tflite_importer.cpp
+++ b/modules/dnn/test/test_tflite_importer.cpp
@@ -55,18 +55,18 @@ void Test_TFLite::testModel(Net& net, const std::string& modelName, const Mat& i
     std::vector<Mat> outs;
     net.forward(outs, outNames);
 
-    // ASSERT_EQ(outs.size(), outNames.size());
-    // for (int i = 0; i < outNames.size(); ++i) {
-    //     std::replace(outNames[i].begin(), outNames[i].end(), ':', '_');
-    //     Mat ref = blobFromNPY(findDataFile(format("dnn/tflite/%s_out_%s.npy", modelName.c_str(), outNames[i].c_str())));
-    //     // A workaround solution for the following cases due to inconsistent shape definitions.
-    //     // The details please see: https://github.com/opencv/opencv/pull/25297#issuecomment-2039081369
-    //     if (modelName == "face_landmark" || modelName == "selfie_segmentation") {
-    //         ref = ref.reshape(1, 1);
-    //         outs[i] = outs[i].reshape(1, 1);
-    //     }
-    //     normAssert(ref, outs[i], outNames[i].c_str(), l1, lInf);
-    // }
+    ASSERT_EQ(outs.size(), outNames.size());
+    for (int i = 0; i < outNames.size(); ++i) {
+        std::replace(outNames[i].begin(), outNames[i].end(), ':', '_');
+        Mat ref = blobFromNPY(findDataFile(format("dnn/tflite/%s_out_%s.npy", modelName.c_str(), outNames[i].c_str())));
+        // A workaround solution for the following cases due to inconsistent shape definitions.
+        // The details please see: https://github.com/opencv/opencv/pull/25297#issuecomment-2039081369
+        if (modelName == "face_landmark" || modelName == "selfie_segmentation") {
+            ref = ref.reshape(1, 1);
+            outs[i] = outs[i].reshape(1, 1);
+        }
+        normAssert(ref, outs[i], outNames[i].c_str(), l1, lInf);
+    }
 }
 
 void Test_TFLite::testModel(const std::string& modelName, const Mat& input, double l1, double lInf)

From aeea1d0a8f3589aef896f96aa2ff3f3cba9059bc Mon Sep 17 00:00:00 2001
From: Dmitry Kurtaev <dmitry.kurtaev@gmail.com>
Date: Thu, 12 Jun 2025 16:44:03 +0300
Subject: [PATCH 4/6] Accuracy test pass

---
 modules/dnn/src/tflite/tflite_importer.cpp | 31 +++++++++++++---------
 1 file changed, 18 insertions(+), 13 deletions(-)

diff --git a/modules/dnn/src/tflite/tflite_importer.cpp b/modules/dnn/src/tflite/tflite_importer.cpp
index fe8f626f80e4..771a2a17d91d 100644
--- a/modules/dnn/src/tflite/tflite_importer.cpp
+++ b/modules/dnn/src/tflite/tflite_importer.cpp
@@ -728,21 +728,26 @@ void TFLiteImporter::parseEltwise(const Operator& op, const std::string& opcode,
 
     std::string fusedActivationType = EnumNameActivationFunctionType(activ);
     bool haveFusedActivation = fusedActivationType != "NONE";
-    addLayer(layerParams, op, false, haveFusedActivation);
+    addLayer(layerParams, op, false, haveFusedActivation || opcode == "SQUARED_DIFFERENCE" || opcode == "RSQRT");
     parseFusedActivation(op, activ);
 
-    // // Layers that split on multiple operations
-    // if (opcode == "SQUARED_DIFFERENCE") {
-    //     LayerParams lp;
-    //     lp.set("power", 2);
-    //     int id = dstNet.addLayerToPrev(layerParams.name + "/square", "Power", isOpInt8 ? CV_8S : CV_32F, lp);
-    //     layerIds[op.outputs()->Get(0)] = std::make_pair(id, 0);
-    // }
-    // else if (opcode == "RSQRT") {
-    //     LayerParams lp;
-    //     int id = dstNet.addLayerToPrev(layerParams.name + "/inv", "Reciprocal", isOpInt8 ? CV_8S : CV_32F, lp);
-    //     layerIds[op.outputs()->Get(0)] = std::make_pair(id, 0);
-    // }
+    if (opcode == "SQUARED_DIFFERENCE" || opcode == "RSQRT") {
+        LayerParams lp;
+        if (opcode == "RSQRT")
+            lp.type = "Reciprocal";
+        else {
+            lp.type = "Power";
+            lp.set("power", 2);
+        }
+        if (newEngine) {
+            std::string tensorName = modelTensors->Get(op.outputs()->Get(0))->name()->str();
+            addLayer(lp, {tensorName + "_additional_post_layer"}, {tensorName});
+            layerIds[op.outputs()->Get(0)] = std::make_pair(-1, -1);
+        } else {
+            int id = dstNet.addLayerToPrev(layerParams.name + "/post", "Power", isOpInt8 ? CV_8S : CV_32F, lp);
+            layerIds[op.outputs()->Get(0)] = std::make_pair(id, 0);
+        }
+    }
 }
 
 void TFLiteImporter::parsePooling(const Operator& op, const std::string& opcode, LayerParams& layerParams) {

From 016b01ed20b567251e371a8033d055fa0110f27f Mon Sep 17 00:00:00 2001
From: Dmitry Kurtaev <dmitry.kurtaev@gmail.com>
Date: Thu, 12 Jun 2025 16:48:26 +0300
Subject: [PATCH 5/6] Replace exceptions to warnings

---
 modules/dnn/src/tflite/tflite_importer.cpp | 4 +++-
 1 file changed, 3 insertions(+), 1 deletion(-)

diff --git a/modules/dnn/src/tflite/tflite_importer.cpp b/modules/dnn/src/tflite/tflite_importer.cpp
index 771a2a17d91d..580f05b57fb3 100644
--- a/modules/dnn/src/tflite/tflite_importer.cpp
+++ b/modules/dnn/src/tflite/tflite_importer.cpp
@@ -732,6 +732,8 @@ void TFLiteImporter::parseEltwise(const Operator& op, const std::string& opcode,
     parseFusedActivation(op, activ);
 
     if (opcode == "SQUARED_DIFFERENCE" || opcode == "RSQRT") {
+        if (haveFusedActivation)
+            CV_LOG_WARNING(NULL, format("%s with fused activation on new engine is not tested", opcode.c_str()));
         LayerParams lp;
         if (opcode == "RSQRT")
             lp.type = "Reciprocal";
@@ -1249,7 +1251,7 @@ void TFLiteImporter::parseStridedSlice(const Operator& op, const std::string& op
         if (newEngine)
         {
             if (axis != lastShrinkAxis)
-                CV_Error(Error::StsNotImplemented, "Multiple axes shrink in new engine");
+                CV_LOG_WARNING(NULL, "StridedSlice with multiple axes shrink in new engine is not tested");
             addFlattenLayer(axis, axis + 1, layerName,
                 layerIds[op.outputs()->Get(0)], isInt8(op) ? CV_8S : CV_32F, op.outputs()->Get(0));
         }

From 38160f6d7d11cdcefac6a6eb241f1b5869a15152 Mon Sep 17 00:00:00 2001
From: Dmitry Kurtaev <dmitry.kurtaev@gmail.com>
Date: Thu, 12 Jun 2025 20:02:58 +0300
Subject: [PATCH 6/6] fix classic engine

---
 modules/dnn/src/tflite/tflite_importer.cpp | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/modules/dnn/src/tflite/tflite_importer.cpp b/modules/dnn/src/tflite/tflite_importer.cpp
index 580f05b57fb3..dd74d6ead0e7 100644
--- a/modules/dnn/src/tflite/tflite_importer.cpp
+++ b/modules/dnn/src/tflite/tflite_importer.cpp
@@ -746,7 +746,7 @@ void TFLiteImporter::parseEltwise(const Operator& op, const std::string& opcode,
             addLayer(lp, {tensorName + "_additional_post_layer"}, {tensorName});
             layerIds[op.outputs()->Get(0)] = std::make_pair(-1, -1);
         } else {
-            int id = dstNet.addLayerToPrev(layerParams.name + "/post", "Power", isOpInt8 ? CV_8S : CV_32F, lp);
+            int id = dstNet.addLayerToPrev(layerParams.name + "/post", lp.type, isOpInt8 ? CV_8S : CV_32F, lp);
             layerIds[op.outputs()->Get(0)] = std::make_pair(id, 0);
         }
     }

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