tensorflow_lite_support/java/src/native/task/vision/segmenter/image_segmenter_jni.cc - platform/external/tflite-support - Git at Google

 /* Copyright 2020 The TensorFlow Authors. All Rights Reserved.

 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 <jni.h>

 #include <memory>
 #include <string>

 #include "absl/strings/str_cat.h"
 #include "tensorflow_lite_support/cc/port/statusor.h"
 #include "tensorflow_lite_support/cc/task/vision/core/frame_buffer.h"
 #include "tensorflow_lite_support/cc/task/vision/image_segmenter.h"
 #include "tensorflow_lite_support/cc/task/vision/proto/image_segmenter_options_proto_inc.h"
 #include "tensorflow_lite_support/cc/task/vision/proto/segmentations_proto_inc.h"
 #include "tensorflow_lite_support/cc/task/vision/utils/frame_buffer_common_utils.h"
 #include "tensorflow_lite_support/cc/utils/jni_utils.h"
 #include "tensorflow_lite_support/java/src/native/task/vision/jni_utils.h"

 namespace {

 using ::tflite::support::StatusOr;
 using ::tflite::support::utils::CreateByteArray;
 using ::tflite::support::utils::GetMappedFileBuffer;
 using ::tflite::support::utils::kAssertionError;
 using ::tflite::support::utils::kIllegalArgumentException;
 using ::tflite::support::utils::kInvalidPointer;
 using ::tflite::support::utils::ThrowException;
 using ::tflite::task::vision::ConvertToFrameBufferOrientation;
 using ::tflite::task::vision::FrameBuffer;
 using ::tflite::task::vision::ImageSegmenter;
 using ::tflite::task::vision::ImageSegmenterOptions;
 using ::tflite::task::vision::Segmentation;
 using ::tflite::task::vision::SegmentationResult;

 constexpr char kArrayListClassNameNoSig[] = "java/util/ArrayList";
 constexpr char kObjectClassName[] = "Ljava/lang/Object;";
 constexpr char kColorClassName[] = "Landroid/graphics/Color;";
 constexpr char kColorClassNameNoSig[] = "android/graphics/Color";
 constexpr char kColoredLabelClassName[] =
     "Lorg/tensorflow/lite/task/vision/segmenter/ColoredLabel;";
 constexpr char kColoredLabelClassNameNoSig[] =
     "org/tensorflow/lite/task/vision/segmenter/ColoredLabel";
 constexpr char kStringClassName[] = "Ljava/lang/String;";
 constexpr int kOutputTypeCategoryMask = 0;
 constexpr int kOutputTypeConfidenceMask = 1;

 // Creates an ImageSegmenterOptions proto based on the Java class.
 ImageSegmenterOptions ConvertToProtoOptions(JNIEnv* env,
                                             jstring display_names_locale,
                                             jint output_type,
                                             jint num_threads) {
   ImageSegmenterOptions proto_options;

   const char* pchars = env->GetStringUTFChars(display_names_locale, nullptr);
   proto_options.set_display_names_locale(pchars);
   env->ReleaseStringUTFChars(display_names_locale, pchars);

   switch (output_type) {
     case kOutputTypeCategoryMask:
       proto_options.set_output_type(ImageSegmenterOptions::CATEGORY_MASK);
       break;
     case kOutputTypeConfidenceMask:
       proto_options.set_output_type(ImageSegmenterOptions::CONFIDENCE_MASK);
       break;
     default:
       // Should never happen.
       ThrowException(env, kIllegalArgumentException,
                      "Unsupported output type: %d", output_type);
   }

   proto_options.set_num_threads(num_threads);

   return proto_options;
 }

 void ConvertToSegmentationResults(JNIEnv* env,
                                   const SegmentationResult& results,
                                   jobject jmask_buffers, jintArray jmask_shape,
                                   jobject jcolored_labels) {
   if (results.segmentation_size() != 1) {
     // Should never happen.
     ThrowException(
         env, kAssertionError,
         "ImageSegmenter only supports one segmentation result, getting %d",
         results.segmentation_size());
   }

   const Segmentation& segmentation = results.segmentation(0);

   // Get the shape from the C++ Segmentation results.
   int shape_array[2] = {segmentation.height(), segmentation.width()};
   env->SetIntArrayRegion(jmask_shape, 0, 2, shape_array);

   // jclass, init, and add of ArrayList.
   jclass array_list_class = env->FindClass(kArrayListClassNameNoSig);
   jmethodID array_list_add_method =
       env->GetMethodID(array_list_class, "add",
                        absl::StrCat("(", kObjectClassName, ")Z").c_str());

   // Convert the masks into ByteBuffer list.
   int num_pixels = segmentation.height() * segmentation.width();
   if (segmentation.has_category_mask()) {
     jbyteArray byte_array = CreateByteArray(
         env,
         reinterpret_cast<const jbyte*>(segmentation.category_mask().data()),
         num_pixels * sizeof(uint8));
     env->CallBooleanMethod(jmask_buffers, array_list_add_method, byte_array);
     env->DeleteLocalRef(byte_array);
   } else {
     for (const auto& confidence_mask :
          segmentation.confidence_masks().confidence_mask()) {
       jbyteArray byte_array = CreateByteArray(
           env, reinterpret_cast<const jbyte*>(confidence_mask.value().data()),
           num_pixels * sizeof(float));
       env->CallBooleanMethod(jmask_buffers, array_list_add_method, byte_array);
       env->DeleteLocalRef(byte_array);
     }
   }

   // Convert colored labels from the C++ object to the Java object.
   jclass color_class = env->FindClass(kColorClassNameNoSig);
   jmethodID color_rgb_method =
       env->GetStaticMethodID(color_class, "rgb", "(III)I");
   jclass colored_label_class = env->FindClass(kColoredLabelClassNameNoSig);
   jmethodID colored_label_create_method = env->GetStaticMethodID(
       colored_label_class, "create",
       absl::StrCat("(", kStringClassName, kStringClassName, "I)",
                    kColoredLabelClassName)
           .c_str());

   for (const auto& colored_label : segmentation.colored_labels()) {
     jstring label = env->NewStringUTF(colored_label.class_name().c_str());
     jstring display_name =
         env->NewStringUTF(colored_label.display_name().c_str());
     jint rgb = env->CallStaticIntMethod(color_class, color_rgb_method,
                                         colored_label.r(), colored_label.g(),
                                         colored_label.b());
     jobject jcolored_label = env->CallStaticObjectMethod(
         colored_label_class, colored_label_create_method, label, display_name,
         rgb);
     env->CallBooleanMethod(jcolored_labels, array_list_add_method,
                            jcolored_label);

     env->DeleteLocalRef(label);
     env->DeleteLocalRef(display_name);
     env->DeleteLocalRef(jcolored_label);
   }
 }

 jlong CreateImageClassifierFromOptions(JNIEnv* env,
                                        const ImageSegmenterOptions& options) {
   StatusOr<std::unique_ptr<ImageSegmenter>> image_segmenter_or =
       ImageSegmenter::CreateFromOptions(options);
   if (image_segmenter_or.ok()) {
     return reinterpret_cast<jlong>(image_segmenter_or->release());
   } else {
     ThrowException(env, kAssertionError,
                    "Error occurred when initializing ImageSegmenter: %s",
                    image_segmenter_or.status().message().data());
     return kInvalidPointer;
   }
 }

 extern "C" JNIEXPORT void JNICALL
 Java_org_tensorflow_lite_task_vision_segmenter_ImageSegmenter_deinitJni(
     JNIEnv* env, jobject thiz, jlong native_handle) {
   delete reinterpret_cast<ImageSegmenter*>(native_handle);
 }

 // Creates an ImageSegmenter instance from the model file descriptor.
 // file_descriptor_length and file_descriptor_offset are optional. Non-possitive
 // values will be ignored.
 extern "C" JNIEXPORT jlong JNICALL
 Java_org_tensorflow_lite_task_vision_segmenter_ImageSegmenter_initJniWithModelFdAndOptions(
     JNIEnv* env, jclass thiz, jint file_descriptor,
     jlong file_descriptor_length, jlong file_descriptor_offset,
     jstring display_names_locale, jint output_type, jint num_threads) {
   ImageSegmenterOptions proto_options = ConvertToProtoOptions(
       env, display_names_locale, output_type, num_threads);
   auto file_descriptor_meta = proto_options.mutable_model_file_with_metadata()
                                   ->mutable_file_descriptor_meta();
   file_descriptor_meta->set_fd(file_descriptor);
   if (file_descriptor_length > 0) {
     file_descriptor_meta->set_length(file_descriptor_length);
   }
   if (file_descriptor_offset > 0) {
     file_descriptor_meta->set_offset(file_descriptor_offset);
   }
   return CreateImageClassifierFromOptions(env, proto_options);
 }

 extern "C" JNIEXPORT jlong JNICALL
 Java_org_tensorflow_lite_task_vision_segmenter_ImageSegmenter_initJniWithByteBuffer(
     JNIEnv* env, jclass thiz, jobject model_buffer,
     jstring display_names_locale, jint output_type, jint num_threads) {
   ImageSegmenterOptions proto_options = ConvertToProtoOptions(
       env, display_names_locale, output_type, num_threads);
   proto_options.mutable_model_file_with_metadata()->set_file_content(
       static_cast<char*>(env->GetDirectBufferAddress(model_buffer)),
       static_cast<size_t>(env->GetDirectBufferCapacity(model_buffer)));
   return CreateImageClassifierFromOptions(env, proto_options);
 }

 extern "C" JNIEXPORT void JNICALL
 Java_org_tensorflow_lite_task_vision_segmenter_ImageSegmenter_segmentNative(
     JNIEnv* env, jclass thiz, jlong native_handle, jobject jimage_byte_buffer,
     jint width, jint height, jobject jmask_buffers, jintArray jmask_shape,
     jobject jcolored_labels, jint jorientation) {
   auto* segmenter = reinterpret_cast<ImageSegmenter*>(native_handle);
   absl::string_view image = GetMappedFileBuffer(env, jimage_byte_buffer);
   std::unique_ptr<FrameBuffer> frame_buffer = CreateFromRgbRawBuffer(
       reinterpret_cast<const uint8*>(image.data()),
       FrameBuffer::Dimension{width, height},
       ConvertToFrameBufferOrientation(env, jorientation));
   auto results_or = segmenter->Segment(*frame_buffer);
   if (results_or.ok()) {
     ConvertToSegmentationResults(env, results_or.value(), jmask_buffers,
                                  jmask_shape, jcolored_labels);
   } else {
     ThrowException(env, kAssertionError,
                    "Error occurred when segmenting the image: %s",
                    results_or.status().message().data());
   }
 }

 }  // namespace
	/* Copyright 2020 The TensorFlow Authors. All Rights Reserved.

	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 <jni.h>

	#include <memory>
	#include <string>

	#include "absl/strings/str_cat.h"
	#include "tensorflow_lite_support/cc/port/statusor.h"
	#include "tensorflow_lite_support/cc/task/vision/core/frame_buffer.h"
	#include "tensorflow_lite_support/cc/task/vision/image_segmenter.h"
	#include "tensorflow_lite_support/cc/task/vision/proto/image_segmenter_options_proto_inc.h"
	#include "tensorflow_lite_support/cc/task/vision/proto/segmentations_proto_inc.h"
	#include "tensorflow_lite_support/cc/task/vision/utils/frame_buffer_common_utils.h"
	#include "tensorflow_lite_support/cc/utils/jni_utils.h"
	#include "tensorflow_lite_support/java/src/native/task/vision/jni_utils.h"

	namespace {

	using ::tflite::support::StatusOr;
	using ::tflite::support::utils::CreateByteArray;
	using ::tflite::support::utils::GetMappedFileBuffer;
	using ::tflite::support::utils::kAssertionError;
	using ::tflite::support::utils::kIllegalArgumentException;
	using ::tflite::support::utils::kInvalidPointer;
	using ::tflite::support::utils::ThrowException;
	using ::tflite::task::vision::ConvertToFrameBufferOrientation;
	using ::tflite::task::vision::FrameBuffer;
	using ::tflite::task::vision::ImageSegmenter;
	using ::tflite::task::vision::ImageSegmenterOptions;
	using ::tflite::task::vision::Segmentation;
	using ::tflite::task::vision::SegmentationResult;

	constexpr char kArrayListClassNameNoSig[] = "java/util/ArrayList";
	constexpr char kObjectClassName[] = "Ljava/lang/Object;";
	constexpr char kColorClassName[] = "Landroid/graphics/Color;";
	constexpr char kColorClassNameNoSig[] = "android/graphics/Color";
	constexpr char kColoredLabelClassName[] =
	"Lorg/tensorflow/lite/task/vision/segmenter/ColoredLabel;";
	constexpr char kColoredLabelClassNameNoSig[] =
	"org/tensorflow/lite/task/vision/segmenter/ColoredLabel";
	constexpr char kStringClassName[] = "Ljava/lang/String;";
	constexpr int kOutputTypeCategoryMask = 0;
	constexpr int kOutputTypeConfidenceMask = 1;

	// Creates an ImageSegmenterOptions proto based on the Java class.
	ImageSegmenterOptions ConvertToProtoOptions(JNIEnv* env,
	jstring display_names_locale,
	jint output_type,
	jint num_threads) {
	ImageSegmenterOptions proto_options;

	const char* pchars = env->GetStringUTFChars(display_names_locale, nullptr);
	proto_options.set_display_names_locale(pchars);
	env->ReleaseStringUTFChars(display_names_locale, pchars);

	switch (output_type) {
	case kOutputTypeCategoryMask:
	proto_options.set_output_type(ImageSegmenterOptions::CATEGORY_MASK);
	break;
	case kOutputTypeConfidenceMask:
	proto_options.set_output_type(ImageSegmenterOptions::CONFIDENCE_MASK);
	break;
	default:
	// Should never happen.
	ThrowException(env, kIllegalArgumentException,
	"Unsupported output type: %d", output_type);
	}

	proto_options.set_num_threads(num_threads);

	return proto_options;
	}

	void ConvertToSegmentationResults(JNIEnv* env,
	const SegmentationResult& results,
	jobject jmask_buffers, jintArray jmask_shape,
	jobject jcolored_labels) {
	if (results.segmentation_size() != 1) {
	// Should never happen.
	ThrowException(
	env, kAssertionError,
	"ImageSegmenter only supports one segmentation result, getting %d",
	results.segmentation_size());
	}

	const Segmentation& segmentation = results.segmentation(0);

	// Get the shape from the C++ Segmentation results.
	int shape_array[2] = {segmentation.height(), segmentation.width()};
	env->SetIntArrayRegion(jmask_shape, 0, 2, shape_array);

	// jclass, init, and add of ArrayList.
	jclass array_list_class = env->FindClass(kArrayListClassNameNoSig);
	jmethodID array_list_add_method =
	env->GetMethodID(array_list_class, "add",
	absl::StrCat("(", kObjectClassName, ")Z").c_str());

	// Convert the masks into ByteBuffer list.
	int num_pixels = segmentation.height() * segmentation.width();
	if (segmentation.has_category_mask()) {
	jbyteArray byte_array = CreateByteArray(
	env,
	reinterpret_cast<const jbyte*>(segmentation.category_mask().data()),
	num_pixels * sizeof(uint8));
	env->CallBooleanMethod(jmask_buffers, array_list_add_method, byte_array);
	env->DeleteLocalRef(byte_array);
	} else {
	for (const auto& confidence_mask :
	segmentation.confidence_masks().confidence_mask()) {
	jbyteArray byte_array = CreateByteArray(
	env, reinterpret_cast<const jbyte*>(confidence_mask.value().data()),
	num_pixels * sizeof(float));
	env->CallBooleanMethod(jmask_buffers, array_list_add_method, byte_array);
	env->DeleteLocalRef(byte_array);
	}
	}

	// Convert colored labels from the C++ object to the Java object.
	jclass color_class = env->FindClass(kColorClassNameNoSig);
	jmethodID color_rgb_method =
	env->GetStaticMethodID(color_class, "rgb", "(III)I");
	jclass colored_label_class = env->FindClass(kColoredLabelClassNameNoSig);
	jmethodID colored_label_create_method = env->GetStaticMethodID(
	colored_label_class, "create",
	absl::StrCat("(", kStringClassName, kStringClassName, "I)",
	kColoredLabelClassName)
	.c_str());

	for (const auto& colored_label : segmentation.colored_labels()) {
	jstring label = env->NewStringUTF(colored_label.class_name().c_str());
	jstring display_name =
	env->NewStringUTF(colored_label.display_name().c_str());
	jint rgb = env->CallStaticIntMethod(color_class, color_rgb_method,
	colored_label.r(), colored_label.g(),
	colored_label.b());
	jobject jcolored_label = env->CallStaticObjectMethod(
	colored_label_class, colored_label_create_method, label, display_name,
	rgb);
	env->CallBooleanMethod(jcolored_labels, array_list_add_method,
	jcolored_label);

	env->DeleteLocalRef(label);
	env->DeleteLocalRef(display_name);
	env->DeleteLocalRef(jcolored_label);
	}
	}

	jlong CreateImageClassifierFromOptions(JNIEnv* env,
	const ImageSegmenterOptions& options) {
	StatusOr<std::unique_ptr<ImageSegmenter>> image_segmenter_or =
	ImageSegmenter::CreateFromOptions(options);
	if (image_segmenter_or.ok()) {
	return reinterpret_cast<jlong>(image_segmenter_or->release());
	} else {
	ThrowException(env, kAssertionError,
	"Error occurred when initializing ImageSegmenter: %s",
	image_segmenter_or.status().message().data());
	return kInvalidPointer;
	}
	}

	extern "C" JNIEXPORT void JNICALL
	Java_org_tensorflow_lite_task_vision_segmenter_ImageSegmenter_deinitJni(
	JNIEnv* env, jobject thiz, jlong native_handle) {
	delete reinterpret_cast<ImageSegmenter*>(native_handle);
	}

	// Creates an ImageSegmenter instance from the model file descriptor.
	// file_descriptor_length and file_descriptor_offset are optional. Non-possitive
	// values will be ignored.
	extern "C" JNIEXPORT jlong JNICALL
	Java_org_tensorflow_lite_task_vision_segmenter_ImageSegmenter_initJniWithModelFdAndOptions(
	JNIEnv* env, jclass thiz, jint file_descriptor,
	jlong file_descriptor_length, jlong file_descriptor_offset,
	jstring display_names_locale, jint output_type, jint num_threads) {
	ImageSegmenterOptions proto_options = ConvertToProtoOptions(
	env, display_names_locale, output_type, num_threads);
	auto file_descriptor_meta = proto_options.mutable_model_file_with_metadata()
	->mutable_file_descriptor_meta();
	file_descriptor_meta->set_fd(file_descriptor);
	if (file_descriptor_length > 0) {
	file_descriptor_meta->set_length(file_descriptor_length);
	}
	if (file_descriptor_offset > 0) {
	file_descriptor_meta->set_offset(file_descriptor_offset);
	}
	return CreateImageClassifierFromOptions(env, proto_options);
	}

	extern "C" JNIEXPORT jlong JNICALL
	Java_org_tensorflow_lite_task_vision_segmenter_ImageSegmenter_initJniWithByteBuffer(
	JNIEnv* env, jclass thiz, jobject model_buffer,
	jstring display_names_locale, jint output_type, jint num_threads) {
	ImageSegmenterOptions proto_options = ConvertToProtoOptions(
	env, display_names_locale, output_type, num_threads);
	proto_options.mutable_model_file_with_metadata()->set_file_content(
	static_cast<char*>(env->GetDirectBufferAddress(model_buffer)),
	static_cast<size_t>(env->GetDirectBufferCapacity(model_buffer)));
	return CreateImageClassifierFromOptions(env, proto_options);
	}

	extern "C" JNIEXPORT void JNICALL
	Java_org_tensorflow_lite_task_vision_segmenter_ImageSegmenter_segmentNative(
	JNIEnv* env, jclass thiz, jlong native_handle, jobject jimage_byte_buffer,
	jint width, jint height, jobject jmask_buffers, jintArray jmask_shape,
	jobject jcolored_labels, jint jorientation) {
	auto* segmenter = reinterpret_cast<ImageSegmenter*>(native_handle);
	absl::string_view image = GetMappedFileBuffer(env, jimage_byte_buffer);
	std::unique_ptr<FrameBuffer> frame_buffer = CreateFromRgbRawBuffer(
	reinterpret_cast<const uint8*>(image.data()),
	FrameBuffer::Dimension{width, height},
	ConvertToFrameBufferOrientation(env, jorientation));
	auto results_or = segmenter->Segment(*frame_buffer);
	if (results_or.ok()) {
	ConvertToSegmentationResults(env, results_or.value(), jmask_buffers,
	jmask_shape, jcolored_labels);
	} else {
	ThrowException(env, kAssertionError,
	"Error occurred when segmenting the image: %s",
	results_or.status().message().data());
	}
	}

	} // namespace