Android MoveNet single human pose estimation by ncnn

Last update: Dec 31, 2022

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Overview

ncnn_Android_MoveNet

Android MoveNet single human pose estimation by ncnn

this project is a ncnn Android demo for MoveNet, it depends on ncnn library and opencv.
https://github.com/Tencent/ncnn
https://github.com/nihui/opencv-mobile

model support:

1.movenet-singlepose-lightningv4(from tfhub)
2.movenet-singlepose-thunderv4(from tfhub)

how to build and run

step1

https://github.com/Tencent/ncnn/releases

Download ncnn-YYYYMMDD-android-vulkan.zip or build ncnn for android yourself
Extract ncnn-YYYYMMDD-android-vulkan.zip into app/src/main/jni and change the ncnn_DIR path to yours in app/src/main/jni/CMakeLists.txt

step2

https://github.com/nihui/opencv-mobile

Download opencv-mobile-XYZ-android.zip
Extract opencv-mobile-XYZ-android.zip into app/src/main/jni and change the OpenCV_DIR path to yours in app/src/main/jni/CMakeLists.txt

step3

Open this project with Android Studio, build it and enjoy!

result

reference:

https://github.com/nihui/ncnn-android-nanodet
https://tfhub.dev/google/movenet/singlepose/lightning/4
https://tfhub.dev/google/movenet/singlepose/thunder/4

Comments

The speed might not fast as the tflite version?
Hi there, I used the lightning model and the after-treatment from this project and find the fps is about 20 and up to 25 which is not fast as the original tflite version. I'm not sure the reason, there's my doubt:

the after-treatment cause more computing resources?

there are some opt. in ncnn can be opened, such as vulkan?

the model in ncnn is natively slower than tflite cuz the tflite model is also optimized? Could you give some enlightenment about these? Thx
opened by FreedoomG 2
gpu cpu两种模式没差别

cpu占用基本一眼，帧率基本一样设备 amlogic 311D PID USER PR NI VIRT RES SHR S[%CPU] %MEM TIME+ ARGS 20344 u0_a55 10 -10 1.2G 207M 104M S 284 10.3 32:20.16 com.tencent.ncnnbodypose

20344 u0_a55 10 -10 1.2G 209M 104M S 272 10.4 33:09.35 com.tencent.ncnnbodypose

opened by lovehuanhuan 0
issue about the output of the model

hi I found that there are 4 outputs of lighting.param and thunder.param which are regress, offset, heatmap and center. could you give some advice of how to use these outputs to generate the keypoints? cuz I cannot find the code here. Thx!

opened by FreedoomG 0
@feigechuanshu can you make a face recognition app using NCNN? maybe MobileFaceNet?

could you bring something like this to android ? https://github.com/honghuCode/mobileFacenet-ncnn

for real-time face recognition on live video. With re-training capabilities, in which user can retrain any given face name with additional data.

opened by GeorvityLabs 0
横屏时陀螺仪不起作用导致识别不准

机型：红米K30 NDK版本：android-ndk-r21e camke版本：3.10.2-win64-x64

ALooper_pollAll的返回值一直都是-3，进不去下面的陀螺仪事件里去，导致横屏时识别效果很差，因为图像没旋转的缘故，不知道为什么。

但是这里无视这个错误继续进入那个if分支的话好像也没啥问题，横屏时陀螺仪也能正常工作。

opened by Yamilemon 0
How to hide the current camera screen？

Hello,

I want to implement the title function, and pass the value to the U3D painting after obtaining the detection result. How can I hide my current display screen?

opened by jia0511 1
model convert

thank you for this nice work.Now I want to convert the tensorflow hub's official movenet model to ncnn. My convert steps as follows: 1、convert pb to onnx; 2、optimize and simplifier onnx model; 3、convert onnx to ncnn; However there some ops ncnn dont support. Error msg as follows: Cast not supported yet!

to=1

Unsupported split axis ! ArgMax not supported yet!

axis=1

keepdims=0

Cast not supported yet!

to=6

Cast not supported yet!

to=1

Cast not supported yet!

to=7

GatherND not supported yet! Cast not supported yet!

to=1

ArgMax not supported yet!

axis=1

keepdims=0

Cast not supported yet!

to=6

Cast not supported yet!

to=1

Cast not supported yet!

to=7

GatherND not supported yet! Unsupported unsqueeze axes ! Unsupported unsqueeze axes ! Cast not supported yet!

to=7

GatherND not supported yet! GatherND not supported yet! Unsupported unsqueeze axes ! Unsupported unsqueeze axes ! Cast not supported yet!

to=1

Unsupported unsqueeze axes ! It will be very nice if you can tell me how do you solve this problem, thank you!

opened by ccslience 1
Convert .pt to .bin and .param format

I trained my model yolov5 for object detection and now i want to deploy it on android app. Before I tried covert to .tflite format but slowly. I saw in assets folder the format you used is .bin and .param format. What code did you use to convert my model to format .bin and .param ?

opened by Houangnt 0

Owner

FeiGeChuanShu

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Android MoveNet single human pose estimation by ncnn

Related tags

Overview

ncnn_Android_MoveNet

model support:

how to build and run

step1

step2

step3

result

reference:

Comments

to=1

axis=1

keepdims=0

to=6

to=1

to=7

to=1

axis=1

keepdims=0

to=6

to=1

to=7

to=7

to=1

Owner

FeiGeChuanShu

[] Easily integrate Camera features into your Android app

A solution for streaming H.264, H.263, AMR, AAC using RTP on Android

[] FFmpeg build for android random architectures with example jni

a system for building custom ffmpeg binaries for Android

Android Java wrapper around ffmpeg command line binary

MJPEG video streaming on Android

script(s) to build ffmpeg for android, including support for RTMP (and OpenSSL)

Script and Instructions for building FFmpeg for Android

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A mod of the Twitch Android Mobile App adding BetterTTV and FrankerFaceZ emotes

Android/iOS video player based on FFmpeg n3.4, with MediaCodec, VideoToolbox support.

android video player base on ijkplayer

Android human matting demo infer by ncnn

Age + Gender Estimation on Android - with TensorFlow Lite

Android BlazePose demo by ncnn

CalEF (Calendar Entry Formatter) : Select an entry in Android-Kalender and send/share the entry's content as human readable text.

An Android app that scans images or human faces in real time and detects whether the mask is worn or not, with the ability to set an audible alert

Measures human heart rate using camera and flash light.

A clean-aesthetically pleasing Measuring Application, which uses relevant sensors-converts raw sensor data into human readable formatted outputs-and displays accurate measurements.

The backend of HumLib - The Human Library in Computer Science