mirror of
https://github.com/PaddlePaddle/FastDeploy.git
synced 2025-10-06 00:57:33 +08:00
[Android] Add CxxBuffer to native and Java PaddleSegModel (#677)
[Android] Add CxxBuffer to native PaddleSegModel
This commit is contained in:
@@ -197,6 +197,14 @@ public SegmentationResult predict(Bitmap ARGB8888Bitmap);
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// 预测并且可视化:预测结果以及可视化,并将可视化后的图片保存到指定的途径,以及将可视化结果渲染在Bitmap上
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public SegmentationResult predict(Bitmap ARGB8888Bitmap, String savedImagePath, float weight);
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public SegmentationResult predict(Bitmap ARGB8888Bitmap, boolean rendering, float weight); // 只渲染 不保存图片
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// 修改result,而非返回result,关注性能的用户可以将以下接口与SegmentationResult的CxxBuffer一起使用
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public boolean predict(Bitmap ARGB8888Bitmap, SegmentationResult result);
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public boolean predict(Bitmap ARGB8888Bitmap, SegmentationResult result, String savedImagePath, float weight);
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public boolean predict(Bitmap ARGB8888Bitmap, SegmentationResult result, boolean rendering, float weight);
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```
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- 设置竖屏或横屏模式: 对于 PP-HumanSeg系列模型,必须要调用该方法设置竖屏模式为true.
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```java
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public void setVerticalScreenFlag(boolean flag);
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```
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- 模型资源释放 API:调用 release() API 可以释放模型资源,返回true表示释放成功,false表示失败;调用 initialized() 可以判断模型是否初始化成功,true表示初始化成功,false表示失败。
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```java
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@@ -311,6 +319,10 @@ public class SegmentationResult {
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public float[] mScoreMap; // 预测到的得分 map 每个像素位置对应一个score HxW
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public long[] mShape; // label map实际的shape (H,W)
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public boolean mContainScoreMap = false; // 是否包含 score map
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// 用户可以选择直接使用CxxBuffer,而非通过JNI拷贝到Java层,
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// 该方式可以一定程度上提升性能
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public void setCxxBufferFlag(boolean flag); // 设置是否为CxxBuffer模式
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public boolean releaseCxxBuffer(); // 手动释放CxxBuffer!!!
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public boolean initialized(); // 检测结果是否有效
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}
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```
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@@ -1,5 +1,3 @@
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import java.security.MessageDigest
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apply plugin: 'com.android.application'
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android {
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@@ -90,8 +88,6 @@ task downloadAndExtractModels(type: DefaultTask) {
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mkdir "${cachePath}"
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}
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FD_MODEL.eachWithIndex { model, index ->
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MessageDigest messageDigest = MessageDigest.getInstance('MD5')
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messageDigest.update(model.src.bytes)
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String[] modelPaths = model.src.split("/")
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String modelName = modelPaths[modelPaths.length - 1]
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// Download the target model if not exists
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@@ -19,6 +19,7 @@ import android.preference.PreferenceManager;
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import android.support.annotation.NonNull;
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import android.support.v4.app.ActivityCompat;
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import android.support.v4.content.ContextCompat;
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import android.util.Log;
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import android.view.View;
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import android.view.ViewGroup;
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import android.view.Window;
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@@ -251,12 +252,18 @@ public class SegmentationMainActivity extends Activity implements View.OnClickLi
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boolean modified = false;
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long tc = System.currentTimeMillis();
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SegmentationResult result = predictor.predict(ARGB8888ImageBitmap);
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SegmentationResult result = new SegmentationResult();
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result.setCxxBufferFlag(true);
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predictor.predict(ARGB8888ImageBitmap, result);
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timeElapsed += (System.currentTimeMillis() - tc);
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Visualize.visSegmentation(ARGB8888ImageBitmap, result);
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modified = result.initialized();
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result.releaseCxxBuffer();
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frameCounter++;
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if (frameCounter >= 30) {
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final int fps = (int) (1000 / (timeElapsed / 30));
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@@ -304,7 +311,8 @@ public class SegmentationMainActivity extends Activity implements View.OnClickLi
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// should mean 'width' if the camera display orientation is 90 | 270 degree
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// (Hold the phone upright to record video)
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// (2) Smaller resolution is more suitable for Lite Portrait HumanSeg.
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// So, we set this preview size (480,480) here.
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// So, we set this preview size (480,480) here. Reference:
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// https://github.com/PaddlePaddle/PaddleSeg/blob/release/2.6/contrib/PP-HumanSeg/README_cn.md
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CameraSurfaceView.EXPECTED_PREVIEW_WIDTH = 480;
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CameraSurfaceView.EXPECTED_PREVIEW_HEIGHT = 480;
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svPreview = (CameraSurfaceView) findViewById(R.id.sv_preview);
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@@ -360,6 +368,7 @@ public class SegmentationMainActivity extends Activity implements View.OnClickLi
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if (Boolean.parseBoolean(SegmentationSettingsActivity.enableLiteFp16)) {
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option.enableLiteFp16();
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}
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predictor.setVerticalScreenFlag(true);
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predictor.init(modelFile, paramsFile, configFile, option);
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}
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}
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@@ -1,5 +1,3 @@
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import java.security.MessageDigest
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apply plugin: 'com.android.library'
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@@ -56,26 +54,23 @@ task downloadAndExtractLibs(type: DefaultTask) {
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println "Downloading and extracting fastdeploy android c++ lib ..."
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}
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doLast {
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// Prepare cache folder for archives
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String cachePath = "cache"
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if (!file("${cachePath}").exists()) {
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mkdir "${cachePath}"
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}
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FD_CXX_LIB.eachWithIndex { lib, index ->
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MessageDigest messageDigest = MessageDigest.getInstance('MD5')
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messageDigest.update(lib.src.bytes)
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String cacheName = new BigInteger(1, messageDigest.digest()).toString(32)
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// Download the target archive if not exists
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boolean copyFiles = !file("${lib.dest}").exists()
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if (!file("${cachePath}/${cacheName}.tgz").exists()) {
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ant.get(src: lib.src, dest: file("${cachePath}/${cacheName}.tgz"))
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String[] libPaths = lib.src.split("/")
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String libName = libPaths[libPaths.length - 1]
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libName = libName.split("\\.")[0]
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boolean copyFiles = !file("${lib.dest}/${libName}").exists()
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if (!file("${cachePath}/${libName}.tgz").exists()) {
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println "Downloading ${lib.src} -> ${cachePath}/${libName}.tgz"
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ant.get(src: lib.src, dest: file("${cachePath}/${libName}.tgz"))
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copyFiles = true
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// force to copy files from the latest archive files
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}
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// Extract the target archive if its dest path does not exists
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if (copyFiles) {
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copy {
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from tarTree("${cachePath}/${cacheName}.tgz")
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from tarTree("${cachePath}/${libName}.tgz")
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into "${lib.dest}"
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}
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}
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@@ -283,6 +283,10 @@ bool AllocateJavaSegmentationResultFromCxx(
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j_seg_result_clazz, "mContainScoreMap", "Z");
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const jfieldID j_seg_score_map_id = env->GetFieldID(
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j_seg_result_clazz, "mScoreMap", "[F");
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const jfieldID j_enable_cxx_buffer_id = env->GetFieldID(
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j_seg_result_clazz, "mEnableCxxBuffer", "Z");
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const jfieldID j_cxx_buffer_id = env->GetFieldID(
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j_seg_result_clazz, "mCxxBuffer", "J");
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const jfieldID j_seg_initialized_id = env->GetFieldID(
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j_seg_result_clazz, "mInitialized", "Z");
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@@ -290,6 +294,18 @@ bool AllocateJavaSegmentationResultFromCxx(
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return false;
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}
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// If 'mEnableCxxBuffer' set as true, then, we only setup the cxx result
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// pointer to the value of 'mCxxBuffer' field. Some users may want
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// to use this method to boost the performance of segmentation.
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jboolean j_enable_cxx_buffer =
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env->GetBooleanField(j_seg_result_obj, j_enable_cxx_buffer_id);
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if (j_enable_cxx_buffer == JNI_TRUE) {
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jlong j_cxx_buffer = reinterpret_cast<jlong>(c_result_ptr);
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env->SetLongField(j_seg_result_obj, j_cxx_buffer_id, j_cxx_buffer);
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env->SetBooleanField(j_seg_result_obj, j_seg_initialized_id, JNI_TRUE);
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return true;
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}
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// mLabelMap int[] shape (n): [I
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const auto &label_map_uint8 = c_result_ptr->label_map;
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jbyteArray j_seg_label_map_byte_arr = env->NewByteArray(len);
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@@ -832,6 +848,10 @@ bool AllocateSegmentationResultFromJava(
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j_seg_result_clazz_cc, "mContainScoreMap", "Z");
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const jfieldID j_seg_score_map_id_cc = env->GetFieldID(
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j_seg_result_clazz_cc, "mScoreMap", "[F");
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const jfieldID j_enable_cxx_buffer_id_cc = env->GetFieldID(
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j_seg_result_clazz_cc, "mEnableCxxBuffer", "Z");
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const jfieldID j_cxx_buffer_id_cc = env->GetFieldID(
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j_seg_result_clazz_cc, "mCxxBuffer", "J");
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const jfieldID j_seg_initialized_id_cc = env->GetFieldID(
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j_seg_result_clazz_cc, "mInitialized", "Z");
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@@ -839,6 +859,38 @@ bool AllocateSegmentationResultFromJava(
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return false;
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}
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// If 'mEnableCxxBuffer' set as true, then, we only Allocate from
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// cxx context to cxx result. Some users may want to use this
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// method to boost the performance of segmentation.
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jboolean j_enable_cxx_buffer =
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env->GetBooleanField(j_seg_result_obj, j_enable_cxx_buffer_id_cc);
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if (j_enable_cxx_buffer == JNI_TRUE) {
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jlong j_cxx_buffer = env->GetLongField(j_seg_result_obj, j_cxx_buffer_id_cc);
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if (j_cxx_buffer == 0) {
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return false;
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}
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// Allocate from cxx context to cxx result
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auto c_cxx_buffer = reinterpret_cast<vision::SegmentationResult *>(j_cxx_buffer);
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// TODO: May use 'swap' to exchange the administrative privileges ?
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// c_result_ptr->shape.swap(c_cxx_buffer->shape);
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// c_result_ptr->label_map.swap(c_cxx_buffer->label_map);
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// c_result_ptr->contain_score_map = c_cxx_buffer->contain_score_map;
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// if (c_cxx_buffer->contain_score_map) {
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// c_result_ptr->score_map.swap(c_cxx_buffer->score_map);
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// }
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c_result_ptr->shape.assign(
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c_cxx_buffer->shape.begin(), c_cxx_buffer->shape.end());
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c_result_ptr->label_map.assign(
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c_cxx_buffer->label_map.begin(), c_cxx_buffer->label_map.end());
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c_result_ptr->contain_score_map = c_cxx_buffer->contain_score_map;
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if (c_cxx_buffer->contain_score_map) {
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c_result_ptr->score_map.assign(
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c_cxx_buffer->score_map.begin(), c_cxx_buffer->score_map.end());
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}
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return true;
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}
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// mInitialized boolean: Z
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jboolean j_seg_initialized =
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env->GetBooleanField(j_seg_result_obj, j_seg_initialized_id_cc);
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@@ -1030,3 +1082,43 @@ bool AllocateCxxResultFromJava(
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} // namespace jni
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} // namespace fastdeploy
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#ifdef __cplusplus
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extern "C" {
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#endif
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JNIEXPORT jboolean JNICALL
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Java_com_baidu_paddle_fastdeploy_vision_SegmentationResult_releaseCxxBufferNative(
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JNIEnv *env, jobject thiz) {
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const jclass j_seg_result_clazz = env->GetObjectClass(thiz);
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const jfieldID j_enable_cxx_buffer_id = env->GetFieldID(
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j_seg_result_clazz, "mEnableCxxBuffer", "Z");
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const jfieldID j_cxx_buffer_id = env->GetFieldID(
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j_seg_result_clazz, "mCxxBuffer", "J");
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const jfieldID j_seg_initialized_id = env->GetFieldID(
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j_seg_result_clazz, "mInitialized", "Z");
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jboolean j_enable_cxx_buffer =
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env->GetBooleanField(thiz, j_enable_cxx_buffer_id);
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if (j_enable_cxx_buffer == JNI_FALSE) {
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return JNI_FALSE;
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}
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jlong j_cxx_buffer = env->GetLongField(thiz, j_cxx_buffer_id);
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if (j_cxx_buffer == 0) {
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return JNI_FALSE;
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}
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auto c_result_ptr = reinterpret_cast<
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fastdeploy::vision::SegmentationResult *>(j_cxx_buffer);
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delete c_result_ptr;
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LOGD("[End] Release SegmentationResult in native !");
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env->SetBooleanField(thiz, j_seg_initialized_id, JNI_FALSE);
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env->DeleteLocalRef(j_seg_result_clazz);
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return JNI_TRUE;
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}
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#ifdef __cplusplus
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}
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#endif
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@@ -41,6 +41,17 @@ Java_com_baidu_paddle_fastdeploy_vision_segmentation_PaddleSegModel_bindNative(
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#ifdef ENABLE_RUNTIME_PERF
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c_model_ptr->EnableRecordTimeOfRuntime();
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#endif
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// Setup is_vertical_screen param
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const jclass j_ppseg_clazz = env->GetObjectClass(thiz);
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const jfieldID j_is_vertical_screen_id = env->GetFieldID(
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j_ppseg_clazz, "mIsVerticalScreen", "Z");
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jboolean j_is_vertical_screen = env->GetBooleanField(
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thiz, j_is_vertical_screen_id);
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bool c_is_vertical_screen = static_cast<jboolean>(j_is_vertical_screen);
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c_model_ptr->is_vertical_screen = c_is_vertical_screen;
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env->DeleteLocalRef(j_ppseg_clazz);
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vision::EnableFlyCV();
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return reinterpret_cast<jlong>(c_model_ptr);
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}
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@@ -70,6 +81,48 @@ Java_com_baidu_paddle_fastdeploy_vision_segmentation_PaddleSegModel_predictNativ
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vision::ResultType::SEGMENTATION);
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}
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JNIEXPORT jboolean JNICALL
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Java_com_baidu_paddle_fastdeploy_vision_segmentation_PaddleSegModel_predictNativeV2(
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JNIEnv *env, jobject thiz, jlong cxx_context, jobject argb8888_bitmap,
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jobject result, jboolean save_image, jstring save_path, jboolean rendering,
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jfloat weight) {
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if (cxx_context == 0) {
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return JNI_FALSE;
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}
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cv::Mat c_bgr;
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if (!fni::ARGB888Bitmap2BGR(env, argb8888_bitmap, &c_bgr)) {
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return JNI_FALSE;
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}
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auto c_model_ptr = reinterpret_cast<segmentation::PaddleSegModel *>(cxx_context);
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const jclass j_seg_result_clazz = env->GetObjectClass(result);
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const jfieldID j_enable_cxx_buffer_id = env->GetFieldID(
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j_seg_result_clazz, "mEnableCxxBuffer", "Z");
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jboolean j_enable_cxx_buffer =
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env->GetBooleanField(result, j_enable_cxx_buffer_id);
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auto c_result_ptr = new vision::SegmentationResult();
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auto t = fni::GetCurrentTime();
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c_model_ptr->Predict(&c_bgr, c_result_ptr);
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PERF_TIME_OF_RUNTIME(c_model_ptr, t)
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if (rendering) {
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fni::RenderingSegmentation(env, c_bgr, *c_result_ptr, argb8888_bitmap,
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save_image, weight, save_path);
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}
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if (!fni::AllocateJavaResultFromCxx(
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env, result, reinterpret_cast<void *>(c_result_ptr),
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vision::ResultType::SEGMENTATION)) {
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delete c_result_ptr;
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return JNI_FALSE;
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}
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// Users need to release cxx result buffer manually
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// if mEnableCxxBuffer is set as true.
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if (j_enable_cxx_buffer == JNI_FALSE) {
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delete c_result_ptr;
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}
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return JNI_TRUE;
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}
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JNIEXPORT jboolean JNICALL
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Java_com_baidu_paddle_fastdeploy_vision_segmentation_PaddleSegModel_releaseNative(
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JNIEnv *env, jobject thiz, jlong cxx_context) {
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@@ -87,3 +140,4 @@ Java_com_baidu_paddle_fastdeploy_vision_segmentation_PaddleSegModel_releaseNativ
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#ifdef __cplusplus
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}
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#endif
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@@ -2,6 +2,8 @@ package com.baidu.paddle.fastdeploy.vision;
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import android.support.annotation.NonNull;
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import com.baidu.paddle.fastdeploy.FastDeployInitializer;
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public class SegmentationResult {
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// Init from native
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public byte[] mLabelMap;
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@@ -9,6 +11,11 @@ public class SegmentationResult {
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public long[] mShape;
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public boolean mContainScoreMap = false;
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public boolean mInitialized = false;
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// Cxx result context, some users may want to use
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// result pointer from native directly to boost
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// the performance of segmentation.
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public long mCxxBuffer = 0;
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public boolean mEnableCxxBuffer = false;
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public SegmentationResult() {
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mInitialized = false;
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@@ -18,6 +25,17 @@ public class SegmentationResult {
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return mInitialized;
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}
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public void setCxxBufferFlag(boolean flag) {
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mEnableCxxBuffer = flag;
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}
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public boolean releaseCxxBuffer() {
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if (mCxxBuffer == 0 || !mEnableCxxBuffer) {
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return false;
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}
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return releaseCxxBufferNative();
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}
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public void setLabelMap(@NonNull byte[] labelMapBuffer) {
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if (labelMapBuffer.length > 0) {
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mLabelMap = labelMapBuffer.clone();
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@@ -39,4 +57,11 @@ public class SegmentationResult {
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public void setContainScoreMap(boolean containScoreMap) {
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mContainScoreMap = containScoreMap;
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}
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private native boolean releaseCxxBufferNative();
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// Initializes at the beginning.
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static {
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FastDeployInitializer.init();
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}
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}
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@@ -7,6 +7,7 @@ import com.baidu.paddle.fastdeploy.RuntimeOption;
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import com.baidu.paddle.fastdeploy.vision.SegmentationResult;
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public class PaddleSegModel {
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public boolean mIsVerticalScreen = false;
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protected long mCxxContext = 0; // Context from native.
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protected boolean mInitialized = false;
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@@ -21,6 +22,12 @@ public class PaddleSegModel {
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init_(modelFile, paramsFile, configFile, new RuntimeOption());
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}
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// Is vertical screen or not, for PP-HumanSeg on vertical screen,
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// this flag must be 'true'.
|
||||
public void setVerticalScreenFlag(boolean flag) {
|
||||
mIsVerticalScreen = flag;
|
||||
}
|
||||
|
||||
// Constructor with custom runtime option
|
||||
public PaddleSegModel(String modelFile,
|
||||
String paramsFile,
|
||||
@@ -94,6 +101,41 @@ public class PaddleSegModel {
|
||||
return result;
|
||||
}
|
||||
|
||||
// Reset the values of input SegmentationResult directly instead of
|
||||
// return a SegmentationResult from native.
|
||||
public boolean predict(Bitmap ARGB8888Bitmap,
|
||||
SegmentationResult result) {
|
||||
if (mCxxContext == 0) {
|
||||
return false;
|
||||
}
|
||||
return predictNativeV2(mCxxContext, ARGB8888Bitmap, result,
|
||||
false, "", false, 0.5f);
|
||||
}
|
||||
|
||||
public boolean predict(Bitmap ARGB8888Bitmap,
|
||||
SegmentationResult result,
|
||||
boolean rendering,
|
||||
float weight) {
|
||||
if (mCxxContext == 0) {
|
||||
return false;
|
||||
}
|
||||
return predictNativeV2(mCxxContext, ARGB8888Bitmap, result,
|
||||
false, "", rendering, weight);
|
||||
}
|
||||
|
||||
public boolean predict(Bitmap ARGB8888Bitmap,
|
||||
SegmentationResult result,
|
||||
String savedImagePath,
|
||||
float weight) {
|
||||
if (mCxxContext == 0) {
|
||||
return false;
|
||||
}
|
||||
return predictNativeV2(
|
||||
mCxxContext, ARGB8888Bitmap, result, true,
|
||||
savedImagePath, true, weight);
|
||||
}
|
||||
|
||||
|
||||
private boolean init_(String modelFile,
|
||||
String paramsFile,
|
||||
String configFile,
|
||||
@@ -139,6 +181,15 @@ public class PaddleSegModel {
|
||||
boolean rendering,
|
||||
float weight);
|
||||
|
||||
// Get cxx result pointer from native
|
||||
private native boolean predictNativeV2(long CxxContext,
|
||||
Bitmap ARGB8888Bitmap,
|
||||
SegmentationResult result,
|
||||
boolean saveImage,
|
||||
String savePath,
|
||||
boolean rendering,
|
||||
float weight);
|
||||
|
||||
// Release buffers allocated in native context.
|
||||
private native boolean releaseNative(long CxxContext);
|
||||
|
||||
|
Reference in New Issue
Block a user