[TF FE] Implemented RGBToHSV operation

src/frontends/tensorflow/docs/supported_ops.md

@@ -829,7 +829,7 @@ A "supported operation" is one that TensorFlow Frontend can convert to the OpenV
 | RFFT                                                    | YES                           |                               |
 | RFFT2D                                                  | YES                           |                               |
 | RFFT3D                                                  | YES                           |                               |
-| RGBToHSV                                                | NO                            |                               |
+| RGBToHSV                                                | YES                           |                               |
 | RaggedBincount                                          | NO                            |                               |
 | RaggedCountSparseOutput                                 | NO                            |                               |
 | RaggedCross                                             | NO                            |                               |

src/frontends/tensorflow/src/op_table.cpp

@@ -363,6 +363,7 @@ const std::map<std::string, CreatorFunction> get_supported_ops() {
         {"RFFT", CreatorFunction(translate_rfft_op)},
         {"RFFT2D", CreatorFunction(translate_rfft_op)},
         {"RFFT3D", CreatorFunction(translate_rfft_op)},
+        {"RGBToHSV", CreatorFunction(translate_rgb_to_hsv_op)},
         {"Rint", CreatorFunction(translate_rint_op)},
         {"Roll", CreatorFunction(translate_roll_op)},
         {"Round", CreatorFunction(translate_round_op)},

src/frontends/tensorflow_common/include/common_op_table.hpp

@@ -139,6 +139,7 @@ OP_CONVERTER(translate_reverse_op);
 OP_CONVERTER(translate_reverse_v2_op);
 OP_CONVERTER(translate_reverse_sequence_op);
 OP_CONVERTER(translate_rfft_op);
+OP_CONVERTER(translate_rgb_to_hsv_op);
 OP_CONVERTER(translate_rint_op);
 OP_CONVERTER(translate_roll_op);
 OP_CONVERTER(translate_round_op);

src/frontends/tensorflow_common/include/utils.hpp

@@ -156,7 +156,7 @@ ov::Output<ov::Node> get_data_slice(const ov::Output<ov::Node>& data,
 ov::Output<ov::Node> compute_broadcast_args(const ov::Output<ov::Node>& shape1, const ov::Output<ov::Node>& shape2);
 
 std::shared_ptr<std::tuple<std::shared_ptr<ov::Node>, std::shared_ptr<ov::Node>, std::shared_ptr<ov::Node>>> rgb_to_hsv(
-    const std::shared_ptr<ov::Node>& images);
+    const ov::Output<ov::Node>& images);
 
 std::shared_ptr<ov::Node> hsv_to_rgb(const ov::Output<ov::Node>& h,
                                      const ov::Output<ov::Node>& s,

src/frontends/tensorflow_common/src/op/rgb_to_hsv.cpp

@@ -0,0 +1,38 @@
+// Copyright (C) 2018-2024 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+
+#include "common_op_table.hpp"
+#include "openvino/op/concat.hpp"
+#include "utils.hpp"
+
+using namespace std;
+using namespace ov;
+using namespace ov::op;
+
+namespace ov {
+namespace frontend {
+namespace tensorflow {
+namespace op {
+
+OutputVector translate_rgb_to_hsv_op(const NodeContext& node) {
+    default_op_checks(node, 1, {"RGBToHSV"});
+    auto images = node.get_input(0);
+    auto node_name = node.get_name();
+
+    auto hsv_components = rgb_to_hsv(images);
+
+    auto hh = get<0>(*hsv_components);
+    auto ss = get<1>(*hsv_components);
+    auto vv = get<2>(*hsv_components);
+
+    auto rgb = make_shared<v0::Concat>(NodeVector{hh, ss, vv}, -1);
+
+    set_node_name(node_name, rgb);
+    return {rgb};
+}
+
+}  // namespace op
+}  // namespace tensorflow
+}  // namespace frontend
+}  // namespace ov

src/frontends/tensorflow_common/src/utils.cpp

@@ -431,7 +431,7 @@ Output<Node> compute_broadcast_args(const Output<Node>& shape1, const Output<Nod
     return broadcasted_shape->output(0);
 }
 
-shared_ptr<tuple<shared_ptr<Node>, shared_ptr<Node>, shared_ptr<Node>>> rgb_to_hsv(const shared_ptr<Node>& images) {
+shared_ptr<tuple<shared_ptr<Node>, shared_ptr<Node>, shared_ptr<Node>>> rgb_to_hsv(const ov::Output<ov::Node>& images) {
     // image format conversion based on
     // https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/kernels/image/adjust_saturation_op.cc
     auto const_zero_f_ = create_same_type_const_scalar<float>(images, 0.0f);

tests/layer_tests/tensorflow_tests/test_tf_RGBToHSV.py

@@ -0,0 +1,54 @@
+# Copyright (C) 2018-2024 Intel Corporation
+# SPDX-License-Identifier: Apache-2.0
+
+import numpy as np
+import platform
+import pytest
+import tensorflow as tf
+from common.tf_layer_test_class import CommonTFLayerTest
+
+rng = np.random.default_rng(3476123)
+
+
+class TestRGBToHSV(CommonTFLayerTest):
+    def _prepare_input(self, inputs_info):
+        assert 'images:0' in inputs_info
+        if self.special_case == 'Black Image':
+            images_shape = inputs_info['images:0']
+            inputs_data = {}
+            inputs_data['images:0'] = np.zeros(images_shape).astype(self.input_type)
+        elif self.special_case == 'Grayscale Image':
+            images_shape = inputs_info['images:0']
+            inputs_data = {}
+            inputs_data['images:0'] = np.ones(images_shape).astype(self.input_type) * rng.random()
+        else:
+            images_shape = inputs_info['images:0']
+            inputs_data = {}
+            inputs_data['images:0'] = rng.random(images_shape).astype(self.input_type)
+
+        return inputs_data
+
+    def create_rgb_to_hsv_net(self, input_shape, input_type, special_case):
+        self.special_case = special_case
+        self.input_type = input_type
+        tf.compat.v1.reset_default_graph()
+        # Create the graph and model
+        with tf.compat.v1.Session() as sess:
+            images = tf.compat.v1.placeholder(input_type, input_shape, 'images')
+            tf.raw_ops.RGBToHSV(images=images)
+            tf.compat.v1.global_variables_initializer()
+            tf_net = sess.graph_def
+
+        return tf_net, None
+
+    @pytest.mark.parametrize('input_shape', [[2, 3], [5, 6, 3], [2, 5, 10, 3]])
+    @pytest.mark.parametrize('input_type', [np.float32, np.float64])
+    @pytest.mark.parametrize('special_case', [None, 'Black Image', 'Grayscale Image'])
+    @pytest.mark.precommit
+    @pytest.mark.nightly
+    def test_adjust_hue_basic(self, input_shape, input_type, special_case,
+                              ie_device, precision, ir_version, temp_dir,
+                              use_legacy_frontend):
+        self._test(*self.create_rgb_to_hsv_net(input_shape, input_type, special_case),
+                   ie_device, precision, ir_version, temp_dir=temp_dir,
+                   use_legacy_frontend=use_legacy_frontend)