!35406 [assistant] [I501QD] Add new operator Solarize

Merge pull request !35406 from HKO/Solarize

mindspore/ccsrc/minddata/dataset/api/python/bindings/dataset/kernels/ir/image/bindings.cc

@@ -70,6 +70,7 @@
 #include "minddata/dataset/kernels/ir/vision/rgb_to_bgr_ir.h"
 #include "minddata/dataset/kernels/ir/vision/rotate_ir.h"
 #include "minddata/dataset/kernels/ir/vision/slice_patches_ir.h"
+#include "minddata/dataset/kernels/ir/vision/solarize_ir.h"
 #include "minddata/dataset/kernels/ir/vision/to_tensor_ir.h"
 #include "minddata/dataset/kernels/ir/vision/uniform_aug_ir.h"
 #include "minddata/dataset/kernels/ir/vision/vertical_flip_ir.h"
@@ -700,6 +701,17 @@ PYBIND_REGISTER(
       }));
   }));
 
+PYBIND_REGISTER(SolarizeOperation, 1, ([](const py::module *m) {
+                  (void)
+                    py::class_<vision::SolarizeOperation, TensorOperation, std::shared_ptr<vision::SolarizeOperation>>(
+                      *m, "SolarizeOperation")
+                      .def(py::init([](const std::vector<float> &threshold) {
+                        auto solarize = std::make_shared<vision::SolarizeOperation>(threshold);
+                        THROW_IF_ERROR(solarize->ValidateParams());
+                        return solarize;
+                      }));
+                }));
+
 PYBIND_REGISTER(ToTensorOperation, 1, ([](const py::module *m) {
                   (void)
                     py::class_<vision::ToTensorOperation, TensorOperation, std::shared_ptr<vision::ToTensorOperation>>(

mindspore/ccsrc/minddata/dataset/api/vision.cc

@@ -75,6 +75,7 @@
 #include "minddata/dataset/kernels/ir/vision/rgba_to_rgb_ir.h"
 #include "minddata/dataset/kernels/ir/vision/rotate_ir.h"
 #include "minddata/dataset/kernels/ir/vision/slice_patches_ir.h"
+#include "minddata/dataset/kernels/ir/vision/solarize_ir.h"
 #include "minddata/dataset/kernels/ir/vision/swap_red_blue_ir.h"
 #include "minddata/dataset/kernels/ir/vision/to_tensor_ir.h"
 #include "minddata/dataset/kernels/ir/vision/uniform_aug_ir.h"
@@ -1130,6 +1131,16 @@ std::shared_ptr<TensorOperation> SlicePatches::Parse() {
                                                  data_->fill_value_);
 }
 
+// Solarize Transform Operation.
+struct Solarize::Data {
+  explicit Data(const std::vector<float> &threshold) : threshold_(threshold) {}
+  std::vector<float> threshold_;
+};
+
+Solarize::Solarize(const std::vector<float> &threshold) : data_(std::make_shared<Data>(threshold)) {}
+
+std::shared_ptr<TensorOperation> Solarize::Parse() { return std::make_shared<SolarizeOperation>(data_->threshold_); }
+
 // SwapRedBlue Transform Operation.
 SwapRedBlue::SwapRedBlue() = default;
 std::shared_ptr<TensorOperation> SwapRedBlue::Parse() { return std::make_shared<SwapRedBlueOperation>(); }

mindspore/ccsrc/minddata/dataset/include/dataset/vision.h

@@ -1571,6 +1571,38 @@ class MS_API SlicePatches final : public TensorTransform {
   std::shared_ptr<Data> data_;
 };
 
+/// \brief Invert pixels within a specified range.
+class MS_API Solarize final : public TensorTransform {
+ public:
+  /// \brief Constructor.
+  /// \param[in] threshold A vector with two elements specifying the pixel range to invert.
+  ///     Threshold values should always be in (min, max) format.
+  ///     If min=max, it will to invert all pixels above min(max).
+  /// \par Example
+  /// \code
+  ///     /* Define operations */
+  ///     auto decode_op = vision::Decode();
+  ///     auto solarize_op = vision::Solarize({0, 255});
+  ///
+  ///     /* dataset is an instance of Dataset object */
+  ///     dataset = dataset->Map({decode_op, solarize_op},  // operations
+  ///                            {"image"});                // input columns
+  /// \endcode
+  explicit Solarize(const std::vector<float> &threshold);
+
+  /// \brief Destructor.
+  ~Solarize() = default;
+
+ protected:
+  /// \brief The function to convert a TensorTransform object into a TensorOperation object.
+  /// \return Shared pointer to TensorOperation object.
+  std::shared_ptr<TensorOperation> Parse() override;
+
+ private:
+  struct Data;
+  std::shared_ptr<Data> data_;
+};
+
 /// \brief Swap the red and blue channels of the input image.
 class MS_API SwapRedBlue final : public TensorTransform {
  public:

mindspore/ccsrc/minddata/dataset/kernels/image/image_utils.cc

@@ -1895,6 +1895,7 @@ Status SlicePatches(const std::shared_ptr<Tensor> &input, std::vector<std::share
 Status Solarize(const std::shared_ptr<Tensor> &input, std::shared_ptr<Tensor> *output,
                 const std::vector<float> &threshold) {
   try {
+    RETURN_IF_NOT_OK(ValidateImage(input, "Solarize", {1, 2, 3, 4, 5, 6, 11, 12}, {2, 3}, {1, 3}));
     std::shared_ptr<CVTensor> input_cv = CVTensor::AsCVTensor(input);
     cv::Mat input_img = input_cv->mat();
     if (!input_cv->mat().data) {
@@ -1920,8 +1921,10 @@ Status Solarize(const std::shared_ptr<Tensor> &input, std::shared_ptr<Tensor> *o
     // solarize desired portion
     const float max_size = 255.f;
     output_cv_tensor->mat() = cv::Scalar::all(max_size) - mask_mat_tensor->mat();
-    input_cv->mat().copyTo(output_cv_tensor->mat(), mask_mat_tensor->mat() == 0);
     input_cv->mat().copyTo(output_cv_tensor->mat(), input_cv->mat() < threshold_min);
+    if (threshold_min < threshold_max) {
+      input_cv->mat().copyTo(output_cv_tensor->mat(), input_cv->mat() > threshold_max);
+    }
 
     *output = std::static_pointer_cast<Tensor>(output_cv_tensor);
   }

mindspore/ccsrc/minddata/dataset/kernels/ir/vision/CMakeLists.txt

@@ -57,6 +57,7 @@ set(DATASET_KERNELS_IR_VISION_SRC_FILES
         rgba_to_rgb_ir.cc
         rotate_ir.cc
         slice_patches_ir.cc
+        solarize_ir.cc
         swap_red_blue_ir.cc
         to_tensor_ir.cc
         uniform_aug_ir.cc

mindspore/ccsrc/minddata/dataset/kernels/ir/vision/solarize_ir.cc

@@ -0,0 +1,74 @@
+/**
+ * Copyright 2022 Huawei Technologies Co., Ltd
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include "minddata/dataset/kernels/ir/vision/solarize_ir.h"
+
+#include "minddata/dataset/kernels/image/solarize_op.h"
+#include "minddata/dataset/kernels/ir/validators.h"
+#include "minddata/dataset/util/validators.h"
+
+namespace mindspore {
+namespace dataset {
+namespace vision {
+#ifndef ENABLE_ANDROID
+// SolarizeOperation
+SolarizeOperation::SolarizeOperation(const std::vector<float> &threshold) : threshold_(threshold) {}
+
+SolarizeOperation::~SolarizeOperation() = default;
+
+Status SolarizeOperation::ValidateParams() {
+  constexpr size_t kThresholdSize = 2;
+  constexpr float kThresholdMax = 255;
+
+  if (threshold_.size() != kThresholdSize) {
+    std::string err_msg =
+      "Solarize: threshold must be a vector of two values, got: " + std::to_string(threshold_.size());
+    LOG_AND_RETURN_STATUS_SYNTAX_ERROR(err_msg);
+  }
+  for (size_t i = 0; i < threshold_.size(); ++i) {
+    if (threshold_[i] < 0 || threshold_[i] > kThresholdMax) {
+      std::string err_msg = "Solarize: threshold has to be between 0 and 255, got:" + std::to_string(threshold_[i]);
+      LOG_AND_RETURN_STATUS_SYNTAX_ERROR(err_msg);
+    }
+  }
+  if (threshold_[0] > threshold_[1]) {
+    std::string err_msg = "Solarize: threshold must be passed in a (min, max) format";
+    LOG_AND_RETURN_STATUS_SYNTAX_ERROR(err_msg);
+  }
+  return Status::OK();
+}
+
+std::shared_ptr<TensorOp> SolarizeOperation::Build() {
+  std::shared_ptr<SolarizeOp> tensor_op = std::make_shared<SolarizeOp>(threshold_);
+  return tensor_op;
+}
+
+Status SolarizeOperation::to_json(nlohmann::json *out_json) {
+  (*out_json)["threshold"] = threshold_;
+  return Status::OK();
+}
+
+Status SolarizeOperation::from_json(nlohmann::json op_params, std::shared_ptr<TensorOperation> *operation) {
+  RETURN_IF_NOT_OK(ValidateParamInJson(op_params, "threshold", kSolarizeOperation));
+  std::vector<float> threshold = op_params["threshold"];
+  *operation = std::make_shared<vision::SolarizeOperation>(threshold);
+  return Status::OK();
+}
+
+#endif
+}  // namespace vision
+}  // namespace dataset
+}  // namespace mindspore

mindspore/ccsrc/minddata/dataset/kernels/ir/vision/solarize_ir.h

@@ -0,0 +1,58 @@
+/**
+ * Copyright 2022 Huawei Technologies Co., Ltd
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#ifndef MINDSPORE_CCSRC_MINDDATA_DATASET_KERNELS_IR_VISION_SOLARIZE_IR_H_
+#define MINDSPORE_CCSRC_MINDDATA_DATASET_KERNELS_IR_VISION_SOLARIZE_IR_H_
+
+#include <map>
+#include <memory>
+#include <string>
+#include <utility>
+#include <vector>
+
+#include "include/api/status.h"
+#include "minddata/dataset/include/dataset/constants.h"
+#include "minddata/dataset/include/dataset/transforms.h"
+#include "minddata/dataset/kernels/ir/tensor_operation.h"
+
+namespace mindspore {
+namespace dataset {
+namespace vision {
+constexpr char kSolarizeOperation[] = "Solarize";
+
+class SolarizeOperation : public TensorOperation {
+ public:
+  explicit SolarizeOperation(const std::vector<float> &threshold);
+
+  ~SolarizeOperation();
+
+  std::shared_ptr<TensorOp> Build() override;
+
+  Status ValidateParams() override;
+
+  std::string Name() const override { return kSolarizeOperation; };
+
+  Status to_json(nlohmann::json *out_json) override;
+
+  static Status from_json(nlohmann::json op_params, std::shared_ptr<TensorOperation> *operation);
+
+ private:
+  std::vector<float> threshold_;
+};
+}  // namespace vision
+}  // namespace dataset
+}  // namespace mindspore
+#endif  // MINDSPORE_CCSRC_MINDDATA_DATASET_KERNELS_IR_VISION_SOLARIZE_IR_H_

mindspore/python/mindspore/dataset/vision/__init__.py

@@ -52,6 +52,7 @@ from .transforms import AdjustGamma, AutoAugment, AutoContrast, BoundingBoxAugme
     RandomHorizontalFlipWithBBox, RandomInvert, RandomLighting, RandomPerspective, RandomPosterize, RandomResizedCrop, \
     RandomResizedCropWithBBox, RandomResize, RandomResizeWithBBox, RandomRotation, RandomSelectSubpolicy, \
     RandomSharpness, RandomSolarize, RandomVerticalFlip, RandomVerticalFlipWithBBox, Rescale, Resize, ResizeWithBBox, \
-    RgbToHsv, Rotate, SlicePatches, TenCrop, ToNumpy, ToPIL, ToTensor, ToType, UniformAugment, VerticalFlip, not_random
+    RgbToHsv, Rotate, SlicePatches, Solarize, TenCrop, ToNumpy, ToPIL, ToTensor, ToType, UniformAugment, VerticalFlip, \
+    not_random
 from .utils import AutoAugmentPolicy, Border, ConvertMode, ImageBatchFormat, Inter, SliceMode, get_image_num_channels, \
     get_image_size

mindspore/python/mindspore/dataset/vision/transforms.py

@@ -70,7 +70,7 @@ from .validators import check_adjust_gamma, check_alpha, check_auto_augment, che
     check_random_affine, check_random_auto_contrast, check_random_color_adjust, check_random_crop, \
     check_random_erasing, check_random_perspective, check_random_resize_crop, check_random_rotation, \
     check_random_select_subpolicy_op, check_random_solarize, check_range, check_rescale, check_resize, \
-    check_resize_interpolation, check_rgb_to_hsv, check_rotate, check_slice_patches, check_ten_crop, \
+    check_resize_interpolation, check_rgb_to_hsv, check_rotate, check_slice_patches, check_solarize, check_ten_crop, \
     check_uniform_augment, check_to_tensor, FLOAT_MAX_INTEGER
 from ..core.datatypes import mstype_to_detype, nptype_to_detype
 from ..transforms.py_transforms_util import Implementation
@@ -3292,6 +3292,40 @@ class SlicePatches(ImageTensorOperation):
                                          SliceMode.to_c_type(self.slice_mode), self.fill_value)
 
 
+class Solarize(ImageTensorOperation):
+    """
+    Solarize the image by inverting all pixel values within the threshold.
+
+    Args:
+        threshold (Union[float, tuple[float, float]]): Range of solarize threshold, should always
+            be in (min, max) format, where min and max are integers in range of [0, 255], and min <= max.
+            If min=max, then invert all pixel values above min(max).
+
+    Raises:
+        TypeError: If `threshold` is not of type float or tuple[float, float].
+        ValueError: If `threshold` is not in range of [0, 255].
+
+    Supported Platforms:
+        ``CPU``
+
+    Examples:
+        >>> transforms_list = [vision.Decode(), vision.Solarize(threshold=(10, 100))]
+        >>> image_folder_dataset = image_folder_dataset.map(operations=transforms_list,
+        ...                                                 input_columns=["image"])
+    """
+
+    @check_solarize
+    def __init__(self, threshold):
+        super().__init__()
+        if isinstance(threshold, (float, int)):
+            threshold = (threshold, threshold)
+        self.threshold = threshold
+        self.implementation = Implementation.C
+
+    def parse(self):
+        return cde.SolarizeOperation(self.threshold)
+
+
 class TenCrop(PyTensorOperation):
     """
     Crop the given image into one central crop and four corners with the flipped version of these.

mindspore/python/mindspore/dataset/vision/validators.py

@@ -22,7 +22,7 @@ from mindspore._c_dataengine import TensorOp, TensorOperation
 from mindspore._c_expression import typing
 from mindspore.dataset.core.validator_helpers import check_value, check_uint8, FLOAT_MIN_INTEGER, FLOAT_MAX_INTEGER, \
     check_pos_float32, check_float32, check_2tuple, check_range, check_positive, INT32_MAX, INT32_MIN, \
-    parse_user_args, type_check, type_check_list, check_c_tensor_op, UINT8_MAX, check_value_normalize_std, \
+    parse_user_args, type_check, type_check_list, check_c_tensor_op, UINT8_MAX, UINT8_MIN, check_value_normalize_std, \
     check_value_cutoff, check_value_ratio, check_odd, check_non_negative_float32, check_non_negative_int32, \
     check_pos_int32, check_tensor_op, deprecator_factory
 from mindspore.dataset.transforms.validators import check_transform_op_type
@@ -1216,3 +1216,26 @@ def deprecated_py_vision(substitute_name=None, substitute_module=None):
     """
     return deprecator_factory("1.8", "mindspore.dataset.vision.py_transforms", "mindspore.dataset.vision",
                               substitute_name, substitute_module)
+
+
+def check_solarize(method):
+    """Wrapper method to check the parameters of SolarizeOp."""
+
+    @wraps(method)
+    def new_method(self, *args, **kwargs):
+
+        [threshold], _ = parse_user_args(method, *args, **kwargs)
+        type_check(threshold, (float, int, list, tuple), "threshold")
+        if isinstance(threshold, (float, int)):
+            threshold = (threshold, threshold)
+        type_check_list(threshold, (float, int), "threshold")
+        if len(threshold) != 2:
+            raise TypeError("threshold must be a single number or sequence of two numbers.")
+        for i, value in enumerate(threshold):
+            check_value(value, (UINT8_MIN, UINT8_MAX), "threshold[{}]".format(i))
+        if threshold[1] < threshold[0]:
+            raise ValueError("threshold must be in order of (min, max).")
+
+        return method(self, *args, **kwargs)
+
+    return new_method

tests/ut/cpp/dataset/c_api_vision_a_to_q_test.cc

@@ -2139,3 +2139,58 @@ TEST_F(MindDataTestPipeline, TestPadToSizeInvalid) {
   // Expect failure: Invalid offset value
   EXPECT_EQ(iter, nullptr);
 }
+
+/// Feature: Solarize
+/// Description: Test default usage
+/// Expectation: The returned result is as expected
+TEST_F(MindDataTestPipeline, TestSolarize) {
+  MS_LOG(INFO) << "Doing MindDataTestPipeline-TestSolarize.";
+
+  std::string MindDataPath = "data/dataset";
+  std::string folder_path = MindDataPath + "/testImageNetData/train/";
+  std::shared_ptr<Dataset> ds = ImageFolder(folder_path, true, std::make_shared<RandomSampler>(false, 2));
+
+  EXPECT_NE(ds, nullptr);
+
+  std::vector<float> threshold = {1.0, 255.0};
+  auto solarize_op = vision::Solarize(threshold);
+
+  ds = ds->Map({solarize_op});
+  EXPECT_NE(ds, nullptr);
+
+  std::shared_ptr<Iterator> iter = ds->CreateIterator();
+  EXPECT_NE(iter, nullptr);
+  std::unordered_map<std::string, mindspore::MSTensor> row;
+  ASSERT_OK(iter->GetNextRow(&row));
+
+  uint64_t i = 0;
+  while (row.size() != 0) {
+    i++;
+    auto image = row["image"];
+    iter->GetNextRow(&row);
+  }
+  EXPECT_EQ(i, 2);
+
+  iter->Stop();
+}
+
+/// Feature: Solarize
+/// Description: Test parameter check
+/// Expectation: Error logs are as expected
+TEST_F(MindDataTestPipeline, TestSolarizeInvalidFillValue) {
+  MS_LOG(INFO) << "Doing MindDataTestPipeline-TestSolarizeInvalidFillValue.";
+
+  std::string MindDataPath = "data/dataset";
+  std::string folder_path = MindDataPath + "/testImageNetData/train/";
+  std::shared_ptr<Dataset> ds = ImageFolder(folder_path, true, std::make_shared<RandomSampler>(false, 2));
+  EXPECT_NE(ds, nullptr);
+
+  std::vector<float> threshold = {150, 100};
+  auto solarize_op = vision::Solarize(threshold);
+
+  ds = ds->Map({solarize_op});
+  EXPECT_NE(ds, nullptr);
+
+  std::shared_ptr<Iterator> iter = ds->CreateIterator();
+  EXPECT_EQ(iter, nullptr);
+}

tests/ut/python/dataset/test_solarize.py

@@ -0,0 +1,207 @@
+# Copyright 2022 Huawei Technologies Co., Ltd
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ==============================================================================
+"""
+Testing Solarize op in DE
+"""
+import numpy as np
+from PIL import Image, ImageOps
+import pytest
+
+import mindspore.dataset as ds
+import mindspore.dataset.vision as vision
+from mindspore import log as logger
+from util import visualize_list, config_get_set_seed, config_get_set_num_parallel_workers, \
+    visualize_one_channel_dataset, visualize_image, diff_mse
+
+GENERATE_GOLDEN = False
+
+MNIST_DATA_DIR = "../data/dataset/testMnistData"
+DATA_DIR = ["../data/dataset/test_tf_file_3_images/train-0000-of-0001.data"]
+SCHEMA_DIR = "../data/dataset/test_tf_file_3_images/datasetSchema.json"
+
+
+def solarize(threshold, plot=False):
+    # First dataset
+    data1 = ds.TFRecordDataset(DATA_DIR, SCHEMA_DIR, columns_list=["image"], shuffle=False)
+    decode_op = vision.Decode()
+    solarize_op = vision.Solarize(threshold)
+    data1 = data1.map(operations=decode_op, input_columns=["image"])
+    data1 = data1.map(operations=solarize_op, input_columns=["image"])
+    # Second dataset
+    data2 = ds.TFRecordDataset(DATA_DIR, SCHEMA_DIR, columns_list=["image"], shuffle=False)
+    data2 = data2.map(operations=decode_op, input_columns=["image"])
+    num_iter = 0
+    for dat1, dat2 in zip(data1.create_dict_iterator(num_epochs=1, output_numpy=True),
+                          data2.create_dict_iterator(num_epochs=1, output_numpy=True)):
+        if num_iter > 0:
+            break
+        solarize_ms = dat1["image"]
+        original = dat2["image"]
+        original = Image.fromarray(original.astype('uint8')).convert('RGB')
+        solarize_cv = ImageOps.solarize(original, threshold)
+        solarize_ms = np.array(solarize_ms)
+        solarize_cv = np.array(solarize_cv)
+        mse = diff_mse(solarize_ms, solarize_cv)
+        logger.info("rotate_{}, mse: {}".format(num_iter + 1, mse))
+        assert mse == 0
+        num_iter += 1
+        if plot:
+            visualize_image(original, solarize_ms, mse, solarize_cv)
+
+    image_solarized = []
+    image = []
+
+    for item1, item2 in zip(data1.create_dict_iterator(num_epochs=1, output_numpy=True),
+                            data2.create_dict_iterator(num_epochs=1, output_numpy=True)):
+        image_solarized.append(item1["image"].copy())
+        image.append(item2["image"].copy())
+    if plot:
+        visualize_list(image, image_solarized)
+
+
+def test_solarize_basic(plot=False):
+    """
+    Feature: Solarize
+    Description: Test Solarize op basic usage
+    Expectation: The dataset is processed as expected
+    """
+    solarize(150.1, plot)
+    solarize(120, plot)
+    solarize(115, plot)
+
+
+def test_solarize_mnist(plot=False):
+    """
+    Feature: Solarize op
+    Description: Test Solarize op with MNIST dataset (Grayscale images)
+    Expectation: The dataset is processed as expected
+    """
+    original_seed = config_get_set_seed(0)
+    original_num_parallel_workers = config_get_set_num_parallel_workers(1)
+
+    mnist_1 = ds.MnistDataset(dataset_dir=MNIST_DATA_DIR, num_samples=2, shuffle=False)
+    mnist_2 = ds.MnistDataset(dataset_dir=MNIST_DATA_DIR, num_samples=2, shuffle=False)
+    mnist_2 = mnist_2.map(operations=vision.Solarize((1.0, 255.0)), input_columns="image")
+
+    images = []
+    images_trans = []
+    labels = []
+
+    for _, (data_orig, data_trans) in enumerate(zip(mnist_1, mnist_2)):
+        image_orig, label_orig = data_orig
+        image_trans, _ = data_trans
+        images.append(image_orig.asnumpy())
+        labels.append(label_orig.asnumpy())
+        images_trans.append(image_trans.asnumpy())
+
+    if plot:
+        visualize_one_channel_dataset(images, images_trans, labels)
+
+    ds.config.set_seed(original_seed)
+    ds.config.set_num_parallel_workers(original_num_parallel_workers)
+
+
+def test_solarize_errors():
+    """
+    Feature: Solarize op
+    Description: Test that Solarize errors with bad input
+    Expectation: Passes the error check test
+    """
+    with pytest.raises(ValueError) as error_info:
+        vision.Solarize((12, 1))
+    assert "threshold must be in order of (min, max)." in str(error_info.value)
+
+    with pytest.raises(ValueError) as error_info:
+        vision.Solarize((-1, 200))
+    assert "Input threshold[0] is not within the required interval of [0, 255]." in str(error_info.value)
+
+    try:
+        vision.Solarize(("122.1", "140"))
+    except TypeError as e:
+        assert "Argument threshold[0] with value 122.1 is not of type [<class 'float'>, <class 'int'>]" in str(e)
+
+    try:
+        vision.Solarize((122, 100, 30))
+    except TypeError as e:
+        assert "threshold must be a single number or sequence of two numbers." in str(e)
+
+    try:
+        vision.Solarize((120,))
+    except TypeError as e:
+        assert "threshold must be a single number or sequence of two numbers." in str(e)
+
+
+def test_input_shape_errors():
+    """
+    Feature: Solarize op
+    Description: Test that Solarize errors with bad input shape
+    Expectation: Passes the error check test
+    """
+    try:
+        image = np.random.randint(0, 256, (300, 300, 3, 3)).astype(np.uint8)
+        vision.Solarize(5)(image)
+    except RuntimeError as e:
+        assert "Solarize: the dimension of image tensor does not match the requirement of operator" in str(e)
+
+    try:
+        image = np.random.randint(0, 256, (4, 300, 300)).astype(np.uint8)
+        vision.Solarize(5)(image)
+    except RuntimeError as e:
+        assert "Solarize: the channel of image tensor does not match the requirement of operator" in str(e)
+
+    try:
+        image = np.random.randint(0, 256, (3, 300, 300)).astype(np.uint8)
+        vision.Solarize(5)(image)
+    except RuntimeError as e:
+        assert "Solarize: the channel of image tensor does not match the requirement of operator" in str(e)
+
+
+def test_input_type_errors():
+    """
+    Feature: Solarize op
+    Description: Test that Solarize errors with bad input type
+    Expectation: Passes the error check test
+    """
+    try:
+        image = np.random.randint(0, 256, (300, 300, 3)).astype(np.uint32)
+        vision.Solarize(5)(image)
+    except RuntimeError as e:
+        assert "Solarize: the data type of image tensor does not match the requirement of operator." in str(e)
+
+    try:
+        image = np.random.randint(0, 256, (300, 300, 3)).astype(np.uint64)
+        vision.Solarize(5)(image)
+    except RuntimeError as e:
+        assert "Solarize: the data type of image tensor does not match the requirement of operator." in str(e)
+
+    try:
+        image = np.random.randint(0, 256, (300, 300, 3)).astype(np.float16)
+        vision.Solarize(5)(image)
+    except RuntimeError as e:
+        assert "Solarize: the data type of image tensor does not match the requirement of operator." in str(e)
+
+    try:
+        image = np.random.randint(0, 256, (300, 300, 3)).astype(np.float64)
+        vision.Solarize(5)(image)
+    except RuntimeError as e:
+        assert "Solarize: the data type of image tensor does not match the requirement of operator." in str(e)
+
+
+if __name__ == "__main__":
+    test_solarize_basic()
+    test_solarize_mnist(plot=False)
+    test_solarize_errors()
+    test_input_shape_errors()
+    test_input_type_errors()