Separated required vision ops for android into vision_lite.h

cmake/package_lite.cmake

@@ -21,7 +21,7 @@ set(PROTOBF_DIR_RUN_X86 ${MAIN_DIR}-${RUN_X86_COMPONENT_NAME}/third_party/protob
 set(FLATBF_DIR_RUN_X86 ${MAIN_DIR}-${RUN_X86_COMPONENT_NAME}/third_party/flatbuffers)
 
 if (BUILD_MINDDATA STREQUAL "full" OR BUILD_MINDDATA STREQUAL "wrapper")
-    install(DIRECTORY ${TOP_DIR}/mindspore/ccsrc/minddata/dataset/include/ DESTINATION ${MIND_DATA_INC_DIR} COMPONENT ${COMPONENT_NAME} FILES_MATCHING PATTERN "*.h")
+    install(DIRECTORY ${TOP_DIR}/mindspore/ccsrc/minddata/dataset/include/ DESTINATION ${MIND_DATA_INC_DIR} COMPONENT ${COMPONENT_NAME} FILES_MATCHING PATTERN "*.h" PATTERN "vision.h" EXCLUDE)
     if (PLATFORM_ARM64)
         install(FILES ${TOP_DIR}/mindspore/lite/build/minddata/libminddata-lite.so DESTINATION ${MIND_DATA_LIB_DIR} COMPONENT ${COMPONENT_NAME})
         install(FILES ${TOP_DIR}/third_party/libjpeg-turbo/lib/libjpeg.so DESTINATION ${TURBO_DIR}/lib COMPONENT ${COMPONENT_NAME})

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

@@ -0,0 +1,174 @@
+/**
+ * Copyright 2020 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_INCLUDE_VISION_LITE_H_
+#define MINDSPORE_CCSRC_MINDDATA_DATASET_INCLUDE_VISION_LITE_H_
+
+#include <map>
+#include <memory>
+#include <string>
+#include <utility>
+#include <vector>
+#include "minddata/dataset/core/constants.h"
+#include "minddata/dataset/include/transforms.h"
+#include "minddata/dataset/util/status.h"
+
+namespace mindspore {
+namespace dataset {
+
+// Transform operations for performing computer vision.
+namespace vision {
+
+// Char arrays storing name of corresponding classes (in alphabetical order)
+constexpr char kCenterCropOperation[] = "CenterCrop";
+constexpr char kCropOperation[] = "Crop";
+constexpr char kDecodeOperation[] = "Decode";
+constexpr char kNormalizeOperation[] = "Normalize";
+constexpr char kResizeOperation[] = "Resize";
+
+// Transform Op classes (in alphabetical order)
+class CenterCropOperation;
+class CropOperation;
+class DecodeOperation;
+class NormalizeOperation;
+class ResizeOperation;
+
+/// \brief Function to create a CenterCrop TensorOperation.
+/// \notes Crops the input image at the center to the given size.
+/// \param[in] size A vector representing the output size of the cropped image.
+///     If size is a single value, a square crop of size (size, size) is returned.
+///     If size has 2 values, it should be (height, width).
+/// \return Shared pointer to the current TensorOperation.
+std::shared_ptr<CenterCropOperation> CenterCrop(std::vector<int32_t> size);
+
+/// \brief Function to create a Crop TensorOp
+/// \notes Crop an image based on location and crop size
+/// \param[in] coordinates Starting location of crop. Must be a vector of two values, in the form of {x_coor, y_coor}
+/// \param[in] size Size of the cropped area. Must be a vector of two values, in the form of {height, width}
+/// \return Shared pointer to the current TensorOp
+std::shared_ptr<CropOperation> Crop(std::vector<int32_t> coordinates, std::vector<int32_t> size);
+
+/// \brief Function to create a Decode TensorOperation.
+/// \notes Decode the input image in RGB mode.
+/// \param[in] rgb A boolean of whether to decode in RGB mode or not.
+/// \return Shared pointer to the current TensorOperation.
+std::shared_ptr<DecodeOperation> Decode(bool rgb = true);
+
+/// \brief Function to create a Normalize TensorOperation.
+/// \notes Normalize the input image with respect to mean and standard deviation.
+/// \param[in] mean A vector of mean values for each channel, w.r.t channel order.
+///     The mean values must be in range (0.0, 255.0].
+/// \param[in] std A vector of standard deviations for each channel, w.r.t. channel order.
+///     The standard deviation values must be in range (0.0, 255.0]
+/// \return Shared pointer to the current TensorOperation.
+std::shared_ptr<NormalizeOperation> Normalize(std::vector<float> mean, std::vector<float> std);
+
+/// \brief Function to create a Resize TensorOperation.
+/// \notes Resize the input image to the given size.
+/// \param[in] size A vector representing the output size of the resized image.
+///     If size is a single value, the image will be resized to this value with
+///     the same image aspect ratio. If size has 2 values, it should be (height, width).
+/// \param[in] interpolation An enum for the mode of interpolation
+/// \return Shared pointer to the current TensorOperation.
+std::shared_ptr<ResizeOperation> Resize(std::vector<int32_t> size,
+                                        InterpolationMode interpolation = InterpolationMode::kLinear);
+
+class CenterCropOperation : public TensorOperation {
+ public:
+  explicit CenterCropOperation(std::vector<int32_t> size);
+
+  ~CenterCropOperation() = default;
+
+  std::shared_ptr<TensorOp> Build() override;
+
+  Status ValidateParams() override;
+
+  std::string Name() const override { return kCenterCropOperation; }
+
+ private:
+  std::vector<int32_t> size_;
+};
+
+class CropOperation : public TensorOperation {
+ public:
+  CropOperation(std::vector<int32_t> coordinates, std::vector<int32_t> size);
+
+  ~CropOperation() = default;
+
+  std::shared_ptr<TensorOp> Build() override;
+
+  Status ValidateParams() override;
+
+  std::string Name() const override { return kCropOperation; }
+
+ private:
+  std::vector<int32_t> coordinates_;
+  std::vector<int32_t> size_;
+};
+class DecodeOperation : public TensorOperation {
+ public:
+  explicit DecodeOperation(bool rgb = true);
+
+  ~DecodeOperation() = default;
+
+  std::shared_ptr<TensorOp> Build() override;
+
+  Status ValidateParams() override;
+
+  std::string Name() const override { return kDecodeOperation; }
+
+ private:
+  bool rgb_;
+};
+
+class NormalizeOperation : public TensorOperation {
+ public:
+  NormalizeOperation(std::vector<float> mean, std::vector<float> std);
+
+  ~NormalizeOperation() = default;
+
+  std::shared_ptr<TensorOp> Build() override;
+
+  Status ValidateParams() override;
+
+  std::string Name() const override { return kNormalizeOperation; }
+
+ private:
+  std::vector<float> mean_;
+  std::vector<float> std_;
+};
+
+class ResizeOperation : public TensorOperation {
+ public:
+  explicit ResizeOperation(std::vector<int32_t> size,
+                           InterpolationMode interpolation_mode = InterpolationMode::kLinear);
+
+  ~ResizeOperation() = default;
+
+  std::shared_ptr<TensorOp> Build() override;
+
+  Status ValidateParams() override;
+
+  std::string Name() const override { return kResizeOperation; }
+
+ private:
+  std::vector<int32_t> size_;
+  InterpolationMode interpolation_;
+};
+}  // namespace vision
+}  // namespace dataset
+}  // namespace mindspore
+#endif  // MINDSPORE_CCSRC_MINDDATA_DATASET_INCLUDE_VISION_LITE_H_