From 12aa0fe89819c02db53677c5749771a1007f623e Mon Sep 17 00:00:00 2001
From: Dhanwanth1803 <147172285+Dhanwanth1803@users.noreply.github.com>
Date: Fri, 16 Feb 2024 20:49:29 +0530
Subject: [PATCH] Merge pull request #24985 from Dhanwanth1803:hardswish

Fixes #24974 support HardSwishInt8 #24985

As given very clearly in the issue #24974 I made the required 2 changes to implement HardSwish Layer in INT8. Requesting comments.

resolves https://github.com/opencv/opencv/issues/24974

- [X] I agree to contribute to the project under Apache 2 License.
- [X] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [X] The PR is proposed to the proper branch
- [X] There is a reference to the original bug report and related work
- [ ] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [ ] The feature is well documented and sample code can be built with the project CMake

Co-authored-by: Dhanwanth1803 <dhanwanthvarala@gmail,com>
---
 modules/dnn/src/init.cpp                          | 1 +
 modules/dnn/src/int8layers/elementwise_layers.cpp | 2 ++
 modules/dnn/src/tflite/tflite_importer.cpp        | 2 ++
 3 files changed, 5 insertions(+)

diff --git a/modules/dnn/src/init.cpp b/modules/dnn/src/init.cpp
index 2170aafc4b..e8450c18f9 100644
--- a/modules/dnn/src/init.cpp
+++ b/modules/dnn/src/init.cpp
@@ -212,6 +212,7 @@ void initializeLayerFactory()
     CV_DNN_REGISTER_LAYER_CLASS(SigmoidInt8,      ActivationLayerInt8);
     CV_DNN_REGISTER_LAYER_CLASS(TanHInt8,         ActivationLayerInt8);
     CV_DNN_REGISTER_LAYER_CLASS(SwishInt8,        ActivationLayerInt8);
+    CV_DNN_REGISTER_LAYER_CLASS(HardSwishInt8,    ActivationLayerInt8);
     CV_DNN_REGISTER_LAYER_CLASS(MishInt8,         ActivationLayerInt8);
     CV_DNN_REGISTER_LAYER_CLASS(ELUInt8,          ActivationLayerInt8);
     CV_DNN_REGISTER_LAYER_CLASS(BNLLInt8,         ActivationLayerInt8);
diff --git a/modules/dnn/src/int8layers/elementwise_layers.cpp b/modules/dnn/src/int8layers/elementwise_layers.cpp
index 2f40a4039f..5c533840f3 100644
--- a/modules/dnn/src/int8layers/elementwise_layers.cpp
+++ b/modules/dnn/src/int8layers/elementwise_layers.cpp
@@ -267,6 +267,8 @@ public:
             res = std::make_shared<ngraph::op::Elu>(input, 1.0f);
         } else if (type == "MishInt8") {
             res = std::make_shared<ngraph::op::v4::Mish>(input);
+        } else if (type == "HardSwishInt8") {
+            res = std::make_shared<ngraph::op::v4::HSwish>(input);
         } else if (type == "AbsValInt8") {
             res = std::make_shared<ngraph::op::Abs>(input);
         } else if (type == "SigmoidInt8") {
diff --git a/modules/dnn/src/tflite/tflite_importer.cpp b/modules/dnn/src/tflite/tflite_importer.cpp
index ed51b4461a..f0e1546306 100644
--- a/modules/dnn/src/tflite/tflite_importer.cpp
+++ b/modules/dnn/src/tflite/tflite_importer.cpp
@@ -939,6 +939,8 @@ void TFLiteImporter::parseActivation(const Operator& op, const std::string& opco
                 y = std::min(std::max(x, 0.f), 6.f);
             else if (opcode == "LOGISTIC")
                 y = 1.0f / (1.0f + std::exp(-x));
+            else if (opcode == "HARD_SWISH")
+                y = x * max(0.f, min(1.f, x / 6.f + 0.5f));
             else
                 CV_Error(Error::StsNotImplemented, "Lookup table for " + opcode);