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[Sync] Sync Java API to master (#1856) 

* sync rotated detector java api to master

* sync mmseg score output to master

* sync java docs for demo

* sync java docs for master
pull/1887/head
hanrui1sensetime 2023-03-13 11:31:39 +08:00 committed by GitHub
parent 48291f01c8
commit 34c68663b6
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28 changed files with 750 additions and 45 deletions
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7
.github/scripts/test_java_demo.py vendored
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@ -47,6 +47,13 @@ PARAMS = [
'configs': [
'https://media.githubusercontent.com/media/hanrui1sensetime/mmdeploy-javaapi-testdata/master/litehrnet.tar' # noqa: E501
]
},
{
'task':
'RotatedDetection',
'configs': [
'https://media.githubusercontent.com/media/hanrui1sensetime/mmdeploy-javaapi-testdata/master/gliding-vertex.tar' # noqa: E501
]
}
]

1
csrc/mmdeploy/apis/java/CMakeLists.txt
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@ -23,5 +23,6 @@ add_jar(${PROJECT_NAME} SOURCES
mmdeploy/TextRecognizer.java
mmdeploy/Restorer.java
mmdeploy/PoseDetector.java
mmdeploy/RotatedDetector.java
OUTPUT_NAME mmdeploy
OUTPUT_DIR ${CMAKE_LIBRARY_OUTPUT_DIRECTORY})

46
csrc/mmdeploy/apis/java/mmdeploy/Classifier.java
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@ -1,5 +1,6 @@
package mmdeploy;
/** @description: the Java API class of Classifier. */
public class Classifier {
static {
System.loadLibrary("mmdeploy_java");
@ -7,22 +8,49 @@ public class Classifier {
private final long handle;
/** @description: Single classification result of a picture. */
public static class Result {
/** Class id. */
public int label_id;
/** Class score. */
public float score;
/** Initializes a new instance of the Result class.
* @param label_id: class id.
* @param score: class score.
*/
public Result(int label_id, float score) {
this.label_id = label_id;
this.score = score;
}
}
public Classifier(String modelPath, String deviceName, int deviceId) {
/** Initializes a new instance of the Classifier class.
* @param modelPath: model path.
* @param deviceName: device name.
* @param deviceId: device ID.
* @exception Exception: create Classifier failed exception.
*/
public Classifier(String modelPath, String deviceName, int deviceId) throws Exception{
handle = create(modelPath, deviceName, deviceId);
if (handle == -1) {
throw new Exception("Create Classifier failed!");
}
}
public Result[][] apply(Mat[] images) {
/** Get label information of each image in a batch.
* @param images: input mats.
* @return: results of each input mat.
* @exception Exception: apply Classifier failed exception.
*/
public Result[][] apply(Mat[] images) throws Exception{
int[] counts = new int[images.length];
Result[] results = apply(handle, images, counts);
if (results == null) {
throw new Exception("Apply Classifier failed!");
}
Result[][] rets = new Result[images.length][];
int offset = 0;
for (int i = 0; i < images.length; ++i) {
@ -36,12 +64,22 @@ public class Classifier {
return rets;
}
public Result[] apply(Mat image) {
/** Get label information of one image.
* @param image: input mat.
* @return: result of input mat.
* @exception Exception: apply Classifier failed exception.
*/
public Result[] apply(Mat image) throws Exception{
int[] counts = new int[1];
Mat[] images = new Mat[]{image};
return apply(handle, images, counts);
Result[] results = apply(handle, images, counts);
if (results == null) {
throw new Exception("Apply Classifier failed!");
}
return results;
}
/** Release the instance of Classifier. */
public void release() {
destroy(handle);
}

4
csrc/mmdeploy/apis/java/mmdeploy/DataType.java
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@ -1,5 +1,6 @@
package mmdeploy;
/** @description: DataType. */
public enum DataType {
FLOAT(0),
HALF(1),
@ -7,6 +8,9 @@ public enum DataType {
INT32(3);
final int value;
/** Initializes a new instance of the DataType class.
* @param value: the value.
*/
DataType(int value) {
this.value = value;
}

52
csrc/mmdeploy/apis/java/mmdeploy/Detector.java
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@ -1,5 +1,6 @@
package mmdeploy;
/** @description: the Java API class of Detector. */
public class Detector {
static {
System.loadLibrary("mmdeploy_java");
@ -7,11 +8,27 @@ public class Detector {
private final long handle;
/** @description: Single detection result of a picture. */
public static class Result {
/** Bbox class id. */
public int label_id;
/** Bbox score. */
public float score;
/** Bbox coordinates. */
public Rect bbox;
/** Bbox mask. */
public InstanceMask mask;
/** Initializes a new instance of the Result class.
* @param label_id: bbox class id.
* @param score: bbox score.
* @param bbox: bbox coordinates.
* @param mask: bbox mask.
*/
public Result(int label_id, float score, Rect bbox, InstanceMask mask) {
this.label_id = label_id;
this.score = score;
@ -20,13 +37,30 @@ public class Detector {
}
}
public Detector(String modelPath, String deviceName, int deviceId) {
/** Initializes a new instance of the Detector class.
* @param modelPath: model path.
* @param deviceName: device name.
* @param deviceId: device ID.
* @exception Exception: create Detector failed exception.
*/
public Detector(String modelPath, String deviceName, int deviceId) throws Exception {
handle = create(modelPath, deviceName, deviceId);
if (handle == -1) {
throw new Exception("Create Detector failed!");
}
}
public Result[][] apply(Mat[] images) {
/** Get information of each image in a batch.
* @param images: input mats.
* @return: results of each input mat.
* @exception Exception: apply Detector failed exception.
*/
public Result[][] apply(Mat[] images) throws Exception {
int[] counts = new int[images.length];
Result[] results = apply(handle, images, counts);
if (results == null) {
throw new Exception("Apply Detector failed!");
}
Result[][] rets = new Result[images.length][];
int offset = 0;
for (int i = 0; i < images.length; ++i) {
@ -40,12 +74,22 @@ public class Detector {
return rets;
}
public Result[] apply(Mat image) {
/** Get information of one image.
* @param image: input mat.
* @return: result of input mat.
* @exception Exception: apply Detector failed exception.
*/
public Result[] apply(Mat image) throws Exception{
int[] counts = new int[1];
Mat[] images = new Mat[]{image};
return apply(handle, images, counts);
Result[] results = apply(handle, images, counts);
if (results == null) {
throw new Exception("Apply Detector failed!");
}
return results;
}
/** Release the instance of Detector. */
public void release() {
destroy(handle);
}

11
csrc/mmdeploy/apis/java/mmdeploy/InstanceMask.java
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@ -1,10 +1,19 @@
package mmdeploy;
/** @description: InstanceMask. */
public class InstanceMask {
/** Mask shape. */
public int[] shape;
/** Mask data. */
public char[] data;
/** Initialize a new instance of the InstanceMask class.
* @param height: height.
* @param width: width.
* @param data: mask data.
*/
public InstanceMask(int height, int width, char[] data) {
shape = new int[]{height, width};
this.data = data;

18
csrc/mmdeploy/apis/java/mmdeploy/Mat.java
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@ -1,12 +1,28 @@
package mmdeploy;
/** @description: Mat. */
public class Mat {
/** Shape. */
public int[] shape;
/** Pixel format. */
public int format;
/** Data type. */
public int type;
/** Mat data. */
public byte[] data;
/** Initialize a new instance of the Mat class.
* @param height: height.
* @param width: width.
* @param channel: channel.
* @param format: pixel format.
* @param type: data type.
* @param data: mat data.
*/
public Mat(int height, int width, int channel,
PixelFormat format, DataType type, byte[] data) {
shape = new int[]{height, width, channel};

4
csrc/mmdeploy/apis/java/mmdeploy/PixelFormat.java
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@ -1,5 +1,6 @@
package mmdeploy;
/** @description: PixelFormat. */
public enum PixelFormat {
BGR(0),
RGB(1),
@ -9,6 +10,9 @@ public enum PixelFormat {
BGRA(5);
final int value;
/** Initialize a new instance of the PixelFormat class.
* @param value: the value.
*/
PixelFormat(int value) {
this.value = value;
}

10
csrc/mmdeploy/apis/java/mmdeploy/PointF.java
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@ -1,10 +1,18 @@
package mmdeploy;
/** @description: the PointF class. */
public class PointF {
/** x coordinate. */
public float x;
/** y coordinate. */
public float y;
/** Initialize a new instance of the PointF class.
* @param x: x coordinate.
* @param y: y coordinate.
*/
public PointF(float x, float y) {
this.x = x;
this.y = y;

46
csrc/mmdeploy/apis/java/mmdeploy/PoseDetector.java
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@ -1,5 +1,6 @@
package mmdeploy;
/** @description: the Java API class of PoseDetector. */
public class PoseDetector {
static {
System.loadLibrary("mmdeploy_java");
@ -7,21 +8,48 @@ public class PoseDetector {
private final long handle;
/** @description: Single pose estimation result of a picture. */
public static class Result {
/** Points. */
public PointF[] point;
/** Scores of points */
public float[] score;
/** Initializes a new instance of the Result class.
* @param point: points.
* @param score: scores of points.
*/
public Result(PointF[] point, float [] score) {
this.point = point;
this.score = score;
}
}
public PoseDetector(String modelPath, String deviceName, int deviceId) {
/** Initializes a new instance of the PoseDetector class.
* @param modelPath: model path.
* @param deviceName: device name.
* @param deviceId: device ID.
* @exception Exception: create PoseDetector failed exception.
*/
public PoseDetector(String modelPath, String deviceName, int deviceId) throws Exception{
handle = create(modelPath, deviceName, deviceId);
if (handle == -1) {
throw new Exception("Create PoseDetector failed!");
}
}
public Result[][] apply(Mat[] images) {
/** Get information of each image in a batch.
* @param images: input mats.
* @return: results of each input mat.
* @exception Exception: apply PoseDetector failed exception.
*/
public Result[][] apply(Mat[] images) throws Exception{
Result[] results = apply(handle, images);
if (results == null) {
throw new Exception("Apply PoseDetector failed!");
}
Result[][] rets = new Result[images.length][];
int offset = 0;
for (int i = 0; i < images.length; ++i) {
@ -33,11 +61,21 @@ public class PoseDetector {
return rets;
}
public Result[] apply(Mat image) {
/** Get information of one image.
* @param image: input mat.
* @return: result of input mat.
* @exception Exception: apply PoseDetector failed exception.
*/
public Result[] apply(Mat image) throws Exception{
Mat[] images = new Mat[]{image};
return apply(handle, images);
Result[] results = apply(handle, images);
if (results == null) {
throw new Exception("Apply PoseDetector failed!");
}
return results;
}
/** Release the instance of PoseDetector. */
public void release() {
destroy(handle);
}

16
csrc/mmdeploy/apis/java/mmdeploy/Rect.java
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@ -1,12 +1,26 @@
package mmdeploy;
/** @description: the Rect class. */
public class Rect {
/** left coordinate. */
public float left;
/** top coordinate. */
public float top;
/** right coordinate. */
public float right;
/** bottom coordinate. */
public float bottom;
/** Initialize a new instance of the Rect class.
* @param left: left coordinate.
* @param top: top coordinate.
* @param right: right coordinate.
* @param bottom: bottom coordinate.
*/
public Rect(float left, float top, float right, float bottom) {
this.left = left;
this.top = top;

43
csrc/mmdeploy/apis/java/mmdeploy/Restorer.java
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@ -1,5 +1,6 @@
package mmdeploy;
/** @description: the Java API class of Restorer. */
public class Restorer {
static {
System.loadLibrary("mmdeploy_java");
@ -7,19 +8,43 @@ public class Restorer {
private final long handle;
/** @description: Single image restore result of a picture. */
public static class Result {
/** Result mat. */
public Mat res;
/** Initializes a new instance of the Result class.
* @param res: result mat.
*/
public Result(Mat res) {
this.res = res;
}
}
public Restorer(String modelPath, String deviceName, int deviceId) {
/** Initializes a new instance of the Restorer class.
* @param modelPath: model path.
* @param deviceName: device name.
* @param deviceId: device ID.
* @exception Exception: create Restorer failed exception.
*/
public Restorer(String modelPath, String deviceName, int deviceId) throws Exception {
handle = create(modelPath, deviceName, deviceId);
if (handle == -1) {
throw new Exception("Create Restorer failed!");
}
}
public Result[][] apply(Mat[] images) {
/** Get information of each image in a batch.
* @param images: input mats.
* @exception Exception: apply Restorer failed exception.
* @return: results of each input mat.
*/
public Result[][] apply(Mat[] images) throws Exception {
Result[] results = apply(handle, images);
if (results == null) {
throw new Exception("Apply Restorer failed!");
}
Result[][] rets = new Result[images.length][];
int offset = 0;
for (int i = 0; i < images.length; ++i) {
@ -31,11 +56,21 @@ public class Restorer {
return rets;
}
public Result[] apply(Mat image) {
/** Get information of one image.
* @param image: input mat.
* @exception Exception: apply Restorer failed exception.
* @return: result of input mat.
*/
public Result[] apply(Mat image) throws Exception{
Mat[] images = new Mat[]{image};
return apply(handle, images);
Result[] results = apply(handle, images);
if (results == null) {
throw new Exception("Apply Restorer failed!");
}
return results;
}
/** Release the instance of Restorer. */
public void release() {
destroy(handle);
}

97
csrc/mmdeploy/apis/java/mmdeploy/RotatedDetector.java 100644
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@ -0,0 +1,97 @@
package mmdeploy;
/** @description: the Java API class of RotatedDetector. */
public class RotatedDetector {
static {
System.loadLibrary("mmdeploy_java");
}
private final long handle;
/** @description: Single rotated detection result of a picture. */
public static class Result {
/** Label ID. */
public int label_id;
/** Score. */
public float score;
/** Rotated bbox. */
public float[] rbbox;
/** Initializes a new instance of the Result class.
* @param label_id: label ID.
* @param score: score.
* @param rbbox: rotated bbox.
*/
public Result(int label_id, float score, float[] rbbox) {
this.label_id = label_id;
this.score = score;
this.rbbox = rbbox;
}
}
/** Initializes a new instance of the RotatedDetector class.
* @param modelPath: model path.
* @param deviceName: device name.
* @param deviceId: device ID.
* @exception Exception: create RotatedDetector failed exception.
*/
public RotatedDetector(String modelPath, String deviceName, int deviceId) throws Exception{
handle = create(modelPath, deviceName, deviceId);
if (handle == -1) {
throw new Exception("Create RotatedDetector failed!");
}
}
/** Get information of each image in a batch.
* @param images: input mats.
* @exception Exception: apply RotatedDetector failed exception.
* @return: results of each input mat.
*/
public Result[][] apply(Mat[] images) throws Exception{
int[] counts = new int[images.length];
Result[] results = apply(handle, images, counts);
if (results == null) {
throw new Exception("Apply RotatedDetector failed!");
}
Result[][] rets = new Result[images.length][];
int offset = 0;
for (int i = 0; i < images.length; ++i) {
Result[] row = new Result[counts[i]];
if (counts[i] >= 0) {
System.arraycopy(results, offset, row, 0, counts[i]);
}
offset += counts[i];
rets[i] = row;
}
return rets;
}
/** Get information of one image.
* @param image: input mat.
* @exception Exception: apply RotatedDetector failed exception.
* @return: result of input mat.
*/
public Result[] apply(Mat image) throws Exception{
int[] counts = new int[1];
Mat[] images = new Mat[]{image};
Result[] results = apply(handle, images, counts);
if (results == null) {
throw new Exception("Apply RotatedDetector failed!");
}
return results;
}
/** Release the instance of Rotated Detector. */
public void release() {
destroy(handle);
}
private native long create(String modelPath, String deviceName, int deviceId);
private native void destroy(long handle);
private native Result[] apply(long handle, Mat[] images, int[] count);
}

58
csrc/mmdeploy/apis/java/mmdeploy/Segmentor.java
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@ -7,25 +7,63 @@ public class Segmentor {
private final long handle;
/** @description: Single image segmentation result of a picture. */
public static class Result {
/** Height. */
public int height;
/** Width. */
public int width;
/** Number of classes. */
public int classes;
/** Segmentation mask. */
public int[] mask;
public Result(int height, int width, int classes, int [] mask) {
/** Segmentation score. */
public float[] score;
/** Initializes a new instance of the Result class.
* @param height: height.
* @param width: width.
* @param classes: number of classes.
* @param mask: segmentation mask.
* @param score: segmentation score.
*/
public Result(int height, int width, int classes, int [] mask, float [] score) {
this.height = height;
this.width = width;
this.classes = classes;
this.mask = mask;
this.score = score;
}
}
public Segmentor(String modelPath, String deviceName, int deviceId) {
/** Initializes a new instance of the Segmentor class.
* @param modelPath: model path.
* @param deviceName: device name.
* @param deviceId: device ID.
* @exception Exception: create Segmentator failed exception.
*/
public Segmentor(String modelPath, String deviceName, int deviceId) throws Exception{
handle = create(modelPath, deviceName, deviceId);
if (handle == -1) {
throw new Exception("Create Segmentor failed!");
}
}
public Result[][] apply(Mat[] images) {
/** Get information of each image in a batch.
* @param images: input mats.
* @exception Exception: apply Segmentor failed exception.
* @return: results of each input mat.
*/
public Result[][] apply(Mat[] images) throws Exception{
Result[] results = apply(handle, images);
if (results == null) {
throw new Exception("Apply Segmentor failed!");
}
Result[][] rets = new Result[images.length][];
int offset = 0;
for (int i = 0; i < images.length; ++i) {
@ -37,11 +75,21 @@ public class Segmentor {
return rets;
}
public Result[] apply(Mat image) {
/** Get information of one image.
* @param image: input mat.
* @exception Exception: apply Segmentor failed exception.
* @return: result of input mat.
*/
public Result[] apply(Mat image) throws Exception{
Mat[] images = new Mat[]{image};
return apply(handle, images);
Result[] results = apply(handle, images);
if (results == null) {
throw new Exception("Apply Segmentor failed!");
}
return results;
}
/** Release the instance of Segmentor. */
public void release() {
destroy(handle);
}

46
csrc/mmdeploy/apis/java/mmdeploy/TextDetector.java
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@ -1,5 +1,6 @@
package mmdeploy;
/** @description: the Java API class of TextDetector. */
public class TextDetector {
static {
System.loadLibrary("mmdeploy_java");
@ -7,22 +8,49 @@ public class TextDetector {
private final long handle;
/** @description: Single text detection result of a picture. */
public static class Result {
/** Bbox. */
public PointF[] bbox;
/** Score. */
public float score;
/** Initializes a new instance of the Result class.
* @param bbox: bbox.
* @param score: score.
*/
public Result(PointF[] bbox, float score) {
this.bbox = bbox;
this.score = score;
}
}
public TextDetector(String modelPath, String deviceName, int deviceId) {
/** Initializes a new instance of the TextDetector class.
* @param modelPath: model path.
* @param deviceName: device name.
* @param deviceId: device ID.
* @exception Exception: create TextDetector failed exception.
*/
public TextDetector(String modelPath, String deviceName, int deviceId) throws Exception{
handle = create(modelPath, deviceName, deviceId);
if (handle == -1) {
throw new Exception("Create TextDetector failed!");
}
}
public Result[][] apply(Mat[] images) {
/** Get information of each image in a batch.
* @param images: input mats.
* @exception Exception: apply TextDetector failed exception.
* @return: results of each input mat.
*/
public Result[][] apply(Mat[] images) throws Exception{
int[] counts = new int[images.length];
Result[] results = apply(handle, images, counts);
if (results == null) {
throw new Exception("Apply TextDetector failed!");
}
Result[][] rets = new Result[images.length][];
int offset = 0;
for (int i = 0; i < images.length; ++i) {
@ -36,12 +64,22 @@ public class TextDetector {
return rets;
}
public Result[] apply(Mat image) {
/** Get information of one image.
* @param image: input mat.
* @exception Exception: apply TextDetector failed exception.
* @return: result of input mat.
*/
public Result[] apply(Mat image) throws Exception{
int[] counts = new int[1];
Mat[] images = new Mat[]{image};
return apply(handle, images, counts);
Result[] results = apply(handle, images, counts);
if (results == null) {
throw new Exception("Apply TextDetector failed!");
}
return results;
}
/** Release the instance of TextDetector. */
public void release() {
destroy(handle);
}

52
csrc/mmdeploy/apis/java/mmdeploy/TextRecognizer.java
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@ -1,5 +1,6 @@
package mmdeploy;
/** @description: the Java API class of TextRecognizer. */
public class TextRecognizer {
static {
System.loadLibrary("mmdeploy_java");
@ -7,21 +8,48 @@ public class TextRecognizer {
private final long handle;
/** @description: Single text recognition result of a picture. */
public static class Result {
/** Text. */
public byte [] text;
/** Score. */
public float [] score;
/** Initializes a new instance of the Result class.
* @param text: text.
* @param score: score.
*/
public Result(byte [] text, float [] score) {
this.text = text;
this.score = score;
}
}
public TextRecognizer(String modelPath, String deviceName, int deviceId) {
/** Initializes a new instance of the TextRecognizer class.
* @param modelPath: model path.
* @param deviceName: device name.
* @param deviceId: device ID.
* @exception Exception: create TextRecognizer failed exception.
*/
public TextRecognizer(String modelPath, String deviceName, int deviceId) throws Exception{
handle = create(modelPath, deviceName, deviceId);
if (handle == -1) {
throw new Exception("Create TextRecognizer failed!");
}
}
public Result[][] apply(Mat[] images) {
/** Get information of each image in a batch.
* @param images: input mats.
* @exception Exception: apply TextRecognizer failed exception.
* @return: results of each input mat.
*/
public Result[][] apply(Mat[] images) throws Exception{
Result[] results = apply(handle, images);
if (results == null) {
throw new Exception("Apply TextRecognizer failed!");
}
Result[][] rets = new Result[images.length][];
int offset = 0;
for (int i = 0; i < images.length; ++i) {
@ -33,16 +61,32 @@ public class TextRecognizer {
return rets;
}
public Result[] apply(Mat image) {
/** Get information of one image.
* @param image: input mat.
* @exception Exception: apply TextDetector failed exception.
* @return: result of input mat.
*/
public Result[] apply(Mat image) throws Exception{
Mat[] images = new Mat[]{image};
return apply(handle, images);
Result[] results = apply(handle, images);
if (results == null) {
throw new Exception("Apply TextRecognizer failed!");
}
return results;
}
/** Get information of one image from bboxes.
* @param image: input mat.
* @param bbox: bboxes information.
* @param bbox_count: numter of bboxes
* @return: result of input mat.
*/
public Result[] applyBbox(Mat image, TextDetector.Result[] bbox, int[] bbox_count) {
Mat[] images = new Mat[]{image};
return applyBbox(handle, images, bbox, bbox_count);
}
/** Release the instance of TextRecognizer. */
public void release() {
destroy(handle);
}

1
csrc/mmdeploy/apis/java/native/CMakeLists.txt
View File

@ -13,6 +13,7 @@ mmdeploy_add_library(${PROJECT_NAME} SHARED EXCLUDE
mmdeploy_Segmentor.cpp
mmdeploy_Restorer.cpp
mmdeploy_PoseDetector.cpp
mmdeploy_RotatedDetector.cpp
mmdeploy_TextDetector.cpp
mmdeploy_TextRecognizer.cpp)

61
csrc/mmdeploy/apis/java/native/mmdeploy_RotatedDetector.cpp 100644
View File

@ -0,0 +1,61 @@
#include "mmdeploy_RotatedDetector.h"
#include <numeric>
#include "mmdeploy/apis/c/mmdeploy/rotated_detector.h"
#include "mmdeploy/apis/java/native/common.h"
#include "mmdeploy/core/logger.h"
jlong Java_mmdeploy_RotatedDetector_create(JNIEnv *env, jobject, jstring modelPath,
jstring deviceName, jint device_id) {
auto model_path = env->GetStringUTFChars(modelPath, nullptr);
auto device_name = env->GetStringUTFChars(deviceName, nullptr);
mmdeploy_rotated_detector_t rotated_detector{};
auto ec = mmdeploy_rotated_detector_create_by_path(model_path, device_name, (int)device_id,
&rotated_detector);
env->ReleaseStringUTFChars(modelPath, model_path);
env->ReleaseStringUTFChars(deviceName, device_name);
if (ec) {
MMDEPLOY_ERROR("failed to create rotated detector, code = {}", ec);
return -1;
}
return (jlong)rotated_detector;
}
void Java_mmdeploy_RotatedDetector_destroy(JNIEnv *, jobject, jlong handle) {
MMDEPLOY_DEBUG("Java_mmdeploy_RotatedDetector_destroy");
mmdeploy_rotated_detector_destroy((mmdeploy_rotated_detector_t)handle);
}
jobjectArray Java_mmdeploy_RotatedDetector_apply(JNIEnv *env, jobject thiz, jlong handle,
jobjectArray images, jintArray counts) {
return With(env, images, [&](const mmdeploy_mat_t imgs[], int size) -> jobjectArray {
mmdeploy_rotated_detection_t *results{};
int *result_count{};
auto ec = mmdeploy_rotated_detector_apply((mmdeploy_rotated_detector_t)handle, imgs, size,
&results, &result_count);
if (ec) {
MMDEPLOY_ERROR("failed to apply rotated detector, code = {}", ec);
return NULL;
}
auto result_cls = env->FindClass("mmdeploy/RotatedDetector$Result");
auto result_ctor = env->GetMethodID(result_cls, "<init>", "(IF[F)V");
auto total = std::accumulate(result_count, result_count + size, 0);
auto array = env->NewObjectArray(total, result_cls, nullptr);
for (int i = 0; i < total; ++i) {
jfloatArray rbbox = env->NewFloatArray(5);
env->SetFloatArrayRegion(rbbox, 0, 5, (jfloat *)results[i].rbbox);
auto res = env->NewObject(result_cls, result_ctor, (jint)results[i].label_id,
(jfloat)results[i].score, rbbox);
env->SetObjectArrayElement(array, i, res);
}
auto counts_array = env->GetIntArrayElements(counts, nullptr);
for (int i = 0; i < size; ++i) {
counts_array[i] = result_count[i];
}
env->ReleaseIntArrayElements(counts, counts_array, 0);
mmdeploy_rotated_detector_release_result(results, result_count);
return array;
});
}

36
csrc/mmdeploy/apis/java/native/mmdeploy_RotatedDetector.h 100644
View File

@ -0,0 +1,36 @@
/* DO NOT EDIT THIS FILE - it is machine generated */
#include <jni.h>
/* Header for class mmdeploy_RotatedDetector */
#ifndef _Included_mmdeploy_RotatedDetector
#define _Included_mmdeploy_RotatedDetector
#ifdef __cplusplus
extern "C" {
#endif
/*
* Class: mmdeploy_RotatedDetector
* Method: create
* Signature: (Ljava/lang/String;Ljava/lang/String;I)J
*/
JNIEXPORT jlong JNICALL Java_mmdeploy_RotatedDetector_create(JNIEnv *, jobject, jstring, jstring,
jint);
/*
* Class: mmdeploy_RotatedDetector
* Method: destroy
* Signature: (J)V
*/
JNIEXPORT void JNICALL Java_mmdeploy_RotatedDetector_destroy(JNIEnv *, jobject, jlong);
/*
* Class: mmdeploy_RotatedDetector
* Method: apply
* Signature: (J[Lmmdeploy/Mat;[I)[Lmmdeploy/RotatedDetector/Result;
*/
JNIEXPORT jobjectArray JNICALL Java_mmdeploy_RotatedDetector_apply(JNIEnv *, jobject, jlong,
jobjectArray, jintArray);
#ifdef __cplusplus
}
#endif
#endif

30
csrc/mmdeploy/apis/java/native/mmdeploy_Segmentor.cpp
View File

@ -16,6 +16,7 @@ jlong Java_mmdeploy_Segmentor_create(JNIEnv *env, jobject, jstring modelPath, js
env->ReleaseStringUTFChars(deviceName, device_name);
if (ec) {
MMDEPLOY_ERROR("failed to create segmentor, code = {}", ec);
return -1;
}
return (jlong)segmentor;
}
@ -27,23 +28,40 @@ void Java_mmdeploy_Segmentor_destroy(JNIEnv *, jobject, jlong handle) {
jobjectArray Java_mmdeploy_Segmentor_apply(JNIEnv *env, jobject thiz, jlong handle,
jobjectArray images) {
return With(env, images, [&](const mmdeploy_mat_t imgs[], int size) {
return With(env, images, [&](const mmdeploy_mat_t imgs[], int size) -> jobjectArray {
mmdeploy_segmentation_t *results{};
auto ec = mmdeploy_segmentor_apply((mmdeploy_segmentor_t)handle, imgs, size, &results);
if (ec) {
MMDEPLOY_ERROR("failed to apply segmentor, code = {}", ec);
return NULL;
}
auto result_cls = env->FindClass("mmdeploy/Segmentor$Result");
auto result_ctor = env->GetMethodID(result_cls, "<init>", "(III[I)V");
auto result_ctor = env->GetMethodID(result_cls, "<init>", "(III[I[F)V");
auto array = env->NewObjectArray(size, result_cls, nullptr);
jintArray jmask;
jfloatArray jscore;
for (int i = 0; i < size; ++i) {
int *mask = results[i].mask;
jintArray jmask = env->NewIntArray(results[i].height * results[i].width);
env->SetIntArrayRegion(jmask, 0, results[i].width * results[i].height, (const jint *)mask);
float *score = results[i].score;
if (results[i].mask) {
jmask = env->NewIntArray(results[i].height * results[i].width);
env->SetIntArrayRegion(jmask, 0, results[i].width * results[i].height, (const jint *)mask);
} else {
jmask = env->NewIntArray(0);
env->SetIntArrayRegion(jmask, 0, 0, nullptr);
}
if (results[i].score) {
jscore = env->NewFloatArray(results[i].classes * results[i].height * results[i].width);
env->SetFloatArrayRegion(jscore, 0,
results[i].classes * results[i].height * results[i].width,
(const jfloat *)score);
} else {
jscore = env->NewFloatArray(0);
env->SetFloatArrayRegion(jscore, 0, 0, nullptr);
}
auto res = env->NewObject(result_cls, result_ctor, (jint)results[i].height,
(jint)results[i].width, (jint)results[i].classes, jmask);
(jint)results[i].width, (jint)results[i].classes, jmask, jscore);
env->SetObjectArrayElement(array, i, res);
}
mmdeploy_segmentor_release_result(results, size);

6
demo/java/ImageClassification.java
View File

@ -9,8 +9,14 @@ import java.awt.image.DataBufferByte;
import java.io.File;
import java.io.IOException;
/** @description: this is a class for ImageClassification java demo. */
public class ImageClassification {
/** The main function for ImageClassification Java demo.
* @param deviceName: the device name of the demo.
* @param modelPath: the image classification model path.
* @param imagePath: the image path.
*/
public static void main(String[] args) {
// Parse arguments
if (args.length != 3) {

7
demo/java/ImageRestorer.java
View File

@ -9,8 +9,14 @@ import java.awt.image.DataBufferByte;
import java.io.File;
import java.io.IOException;
/** @description: this is a class for ImageRestorer java demo. */
public class ImageRestorer {
/** The main function for ImageRestorer Java demo.
* @param deviceName: the device name of the demo.
* @param modelPath: the image restorer model path.
* @param imagePath: the image path.
*/
public static void main(String[] args) {
// Parse arguments
if (args.length != 3) {
@ -26,6 +32,7 @@ public class ImageRestorer {
try {
restorer = new Restorer(modelPath, deviceName, 0);
// load image
Mat img = Utils.loadImage(imagePath);

7
demo/java/ImageSegmentation.java
View File

@ -9,8 +9,14 @@ import java.awt.image.DataBufferByte;
import java.io.File;
import java.io.IOException;
/** @description: this is a class for ImageSegmentation java demo. */
public class ImageSegmentation {
/** The main function for ImageSegmentation Java demo.
* @param deviceName: the device name of the demo.
* @param modelPath: the image segmentation model path.
* @param imagePath: the image path.
*/
public static void main(String[] args) {
// Parse arguments
if (args.length != 3) {
@ -26,6 +32,7 @@ public class ImageSegmentation {
try {
segmentor = new Segmentor(modelPath, deviceName, 0);
// load image
Mat img = Utils.loadImage(imagePath);

8
demo/java/ObjectDetection.java
View File

@ -12,8 +12,14 @@ import java.awt.Graphics;
import java.io.File;
import java.io.IOException;
/** @description: this is a class for ObjectDetection java demo. */
public class ObjectDetection {
/** The main function for ObjectDetection Java demo.
* @param deviceName: the device name of the demo.
* @param modelPath: the object detection model path.
* @param imagePath: the image path.
*/
public static void main(String[] args) {
// Parse arguments
if (args.length != 3) {
@ -28,12 +34,14 @@ public class ObjectDetection {
Detector detector = null;
try {
detector = new Detector(modelPath, deviceName, 0);
// load image
BufferedImage srcImg = ImageIO.read(new File(imagePath));
Mat img = Utils.bufferedImage2Mat(srcImg);
// apply detector
Detector.Result[] result = detector.apply(img);
// print results
Graphics ghandle = srcImg.createGraphics();
for (int i = 0; i < result.length; i++) {

15
demo/java/Ocr.java
View File

@ -10,12 +10,19 @@ import java.awt.image.DataBufferByte;
import java.io.File;
import java.io.IOException;
/** @description: this is a class for Ocr java demo. */
public class Ocr {
/** The main function for Ocr Java demo.
* @param deviceName: the device name of the demo.
* @param detModelPath: the text detection model path.
* @param recModelPath: the text recognition model path.
* @param imagePath: the image path.
*/
public static void main(String[] args) {
// Parse arguments
if (args.length != 4) {
System.out.println("usage:\njava TextDetection deviceName detModelPath recModelPath imagePath");
System.out.println("usage:\njava Ocr deviceName detModelPath recModelPath imagePath");
return;
}
String deviceName = args[0];
@ -30,13 +37,19 @@ public class Ocr {
try {
text_detector = new TextDetector(detModelPath, deviceName, 0);
text_recognizer = new TextRecognizer(recModelPath, deviceName, 0);
// load image
Mat img = Utils.loadImage(imagePath);
// apply text detector
TextDetector.Result[] detResult = text_detector.apply(img);
int [] detResultCount = {detResult.length};
TextRecognizer.Result[] recResult = text_recognizer.applyBbox(img, detResult, detResultCount);
if (recResult == null) {
System.out.println("Apply TextRecognizer failed.");
System.exit(1);
}
// print results
for (int i = 0; i < detResultCount[0]; ++i) {
System.out.printf("box[%d]: %s\n", i, new String(recResult[i].text));

17
demo/java/PoseDetection.java
View File

@ -9,8 +9,14 @@ import java.awt.image.DataBufferByte;
import java.io.File;
import java.io.IOException;
/** @description: this is a class for PoseDetection java demo. */
public class PoseDetection {
/** The main function for PoseDetection Java demo.
* @param deviceName: the device name of the demo.
* @param modelPath: the pose detection model path.
* @param imagePath: the image path.
*/
public static void main(String[] args) {
// Parse arguments
if (args.length != 3) {
@ -22,15 +28,16 @@ public class PoseDetection {
String imagePath = args[2];
// create pose estimator
PoseDetector pose_estimator = null;
PoseDetector poseEstimator = null;
try {
pose_estimator = new PoseDetector(modelPath, deviceName, 0);
poseEstimator = new PoseDetector(modelPath, deviceName, 0);
// load image
Mat img = Utils.loadImage(imagePath);
// apply pose estimator
PoseDetector.Result[] result = pose_estimator.apply(img);
PoseDetector.Result[] result = poseEstimator.apply(img);
// print results
for (PoseDetector.Result value : result) {
@ -42,8 +49,8 @@ public class PoseDetection {
System.out.println("exception: " + e.getMessage());
} finally {
// release pose estimator
if (pose_estimator != null) {
pose_estimator.release();
if (poseEstimator != null) {
poseEstimator.release();
}
}
}

83
demo/java/RotatedDetection.java 100644
View File

@ -0,0 +1,83 @@
import mmdeploy.RotatedDetector;
import mmdeploy.PixelFormat;
import mmdeploy.DataType;
import mmdeploy.Mat;
import javax.imageio.ImageIO;
import java.awt.Color;
import java.awt.image.BufferedImage;
import java.awt.image.DataBufferByte;
import java.awt.Graphics;
import java.io.File;
import java.io.IOException;
import java.lang.Math;
/** @description: this is a class for RotatedDetection java demo. */
public class RotatedDetection {
/** The main function for RotatedDetection Java demo.
* @param deviceName: the device name of the demo.
* @param modelPath: the rotated detection model path.
* @param imagePath: the image path.
*/
public static void main(String[] args) {
// Parse arguments
if (args.length != 3) {
System.out.println("usage:\njava RotatedDetection deviceName modelPath imagePath");
return;
}
String deviceName = args[0];
String modelPath = args[1];
String imagePath = args[2];
// create rotated detector
RotatedDetector rotatedDetector = null;
try {
rotatedDetector = new RotatedDetector(modelPath, deviceName, 0);
// load image
BufferedImage srcImg = ImageIO.read(new File(imagePath));
Mat img = Utils.bufferedImage2Mat(srcImg);
// apply rotated detector
RotatedDetector.Result[] result = rotatedDetector.apply(img);
// print results
Graphics ghandle = srcImg.createGraphics();
for (int i = 0; i < result.length; i++) {
RotatedDetector.Result value = result[i];
float cx, cy, w, h, angle;
cx = value.rbbox[0];
cy = value.rbbox[1];
w = value.rbbox[2];
h = value.rbbox[3];
angle = value.rbbox[4];
float wx = w / 2 * (float)Math.cos(angle);
float wy = w / 2 * (float)Math.sin(angle);
float hx = -h / 2 * (float)Math.sin(angle);
float hy = h / 2 * (float)Math.cos(angle);
System.out.printf("box %d, score %.2f, point1: (%.2f, %.2f), point2: (%.2f, %.2f), point3: (%.2f, %.2f), point4: (%.2f, %.2f)\n",
i, value.score, cx - wx - hx, cy - wy - hy, cx + wx - hx, cy + wy - hy, cx + wx + hx, cy + wy + hy, cx - wx + hx, cy - wy + hy);
// skip rotated detections less than specified score threshold
if (value.score < 0.1) {
continue;
}
ghandle.setColor(new Color(0, 255, 0));
int[] polygonX = new int[] {(int)(cx - wx - hx), (int)(cx + wx - hx), (int)(cx + wx + hx), (int)(cx - wx + hx)};
int[] polygonY = new int[] {(int)(cy - wy - hy), (int)(cy + wy - hy), (int)(cy + wy + hy), (int)(cy - wy + hy)};
ghandle.drawPolygon(polygonX, polygonY, 4);
}
ghandle.dispose();
ImageIO.write(srcImg, "png", new File("output_rotated_detection.png"));
} catch (Exception e) {
System.out.println("exception: " + e.getMessage());
} finally {
// release rotated detector
if (rotatedDetector != null) {
rotatedDetector.release();
}
}
}
}

13
demo/java/Utils.java
View File

@ -7,12 +7,25 @@ import java.awt.image.BufferedImage;
import java.awt.image.DataBufferByte;
import java.io.File;
import java.io.IOException;
import java.lang.*;
/** @description: this is a util class for java demo. */
public class Utils {
/** This function loads the image by path.
* @param path: the image path.
* @return: the image with Mat format.
* @exception IOException: throws an IO exception when load failed.
*/
public static Mat loadImage(String path) throws IOException {
BufferedImage img = ImageIO.read(new File(path));
return bufferedImage2Mat(img);
}
/** This function changes bufferedImage to Mat.
* @param img: the bufferedImage.
* @return: the image with Mat format.
*/
public static Mat bufferedImage2Mat(BufferedImage img) {
byte[] data = ((DataBufferByte) img.getData().getDataBuffer()).getData();
return new Mat(img.getHeight(), img.getWidth(), img.getColorModel().getNumComponents(),