Giter Site home page Giter Site logo

linyilyi / pose-monitor Goto Github PK

View Code? Open in Web Editor NEW
2.5K 2.5K 387.0 70.36 MB

“让爷康康”是一款手机 AI 应用程序,可以监测不良坐姿并进行语音提示

License: Apache License 2.0

Kotlin 3.30% Jupyter Notebook 96.69% Python 0.01%

pose-monitor's People

Contributors

linyilyi avatar zhengbangbo avatar

Stargazers

 avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar

Watchers

 avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar

pose-monitor's Issues

关于相机取景距离的问题

Hello,用华为mate 30可以正常运行APP,但是相机取景框焦距恒定,需要把手机放在离人很远的地方(不确定其他手机是否也是这样)。对于空间比较小的房间几乎无法使用,想问一下是否可以增加调节相机焦距的功能?

好好玩哈哈

希望能增加切换到前置摄像头的支持Screenshot_20221105-175211_让爷康康.png

设备小米6 类原生Android11

非常好的APP

作者可以分一个监测小学生写字低头提醒的版本吗?叫爸爸康康。

崩溃报错信息

机型:三星Galaxy S9,打开会崩溃闪退,AS报错信息:Process: lyi.linyi.posemon, PID: 31265
java.lang.IllegalArgumentException: Internal error: Failed to apply delegate: NN API returned error ANEURALNETWORKS_OP_FAILED at line 4274 while completing NNAPI compilation.

Node number 157 (TfLiteNnapiDelegate) failed to prepare.

关于该项目在线下课堂的应用设想

如果运用在线下课堂,就可以检测学生上课的时候是不是在看黑板,或者在大学里面通过学生的专注姿态反向评价老师的上课质量。然后每节课下课就生成报告上传到师生的APP上,就是不知道这app做出来会不会喷死,并且刚刚试了一下 一次只能跟踪一个目标。不知道,能否实现同时跟踪多个目标。想做这个项目,大佬能带带吗?

Have a error when I loading the movenat_thunder.tflite model

Hi,
I tried loading the movenat_thunder.tflite model with tf.lite.interpreter, using the following code:

import tensorflow as tf
interpreter = tf.lite.Interpreter(model_path='movenat_thunder.tflite')

But was hit with the following error:

ValueError Traceback (most recent call last)
/home/generate_cc_array.ipynb Cell 5 in <cell line: 1>()
----> 1 interpreter = tf.lite.Interpreter(model_path='movenat_thunder.tflite')
2 interpreter.allocate_tensors()
4 input_details = interpreter.get_input_details()[0]

File ~/virtual_environments/utkface/lib/python3.10/site-packages/tensorflow/lite/python/interpreter.py:455, in Interpreter.init(self, model_path, model_content, experimental_delegates, num_threads, experimental_op_resolver_type, experimental_preserve_all_tensors)
448 custom_op_registerers_by_name = [
449 x for x in self._custom_op_registerers if isinstance(x, str)
450 ]
451 custom_op_registerers_by_func = [
452 x for x in self._custom_op_registerers if not isinstance(x, str)
453 ]
454 self._interpreter = (
--> 455 _interpreter_wrapper.CreateWrapperFromFile(
456 model_path, op_resolver_id, custom_op_registerers_by_name,
457 custom_op_registerers_by_func, experimental_preserve_all_tensors))
458 if not self._interpreter:
459 raise ValueError('Failed to open {}'.format(model_path))

ValueError: quantized_dimension must be in range [0, 1). Was 3.Tensor 33 has invalid quantization parameters.quantized_dimension must be in range [0, 1). Was 3.Tensor 36 has invalid quantization parameters.quantized_dimension must be in range [0, 1). Was 3.Tensor 40 has invalid quantization parameters.quantized_dimension must be in range [0, 1). Was 3.Tensor 44 has invalid quantization parameters.quantized_dimension must be in range [0, 1). Was 3.Tensor 48 has invalid quantization parameters.quantized_dimension must be in range [0, 1). Was 3.Tensor 52 has invalid quantization parameters.quantized_dimension must be in range [0, 1). Was 3.Tensor 56 has invalid quantization parameters.quantized_dimension must be in range [0, 1). Was 3.Tensor 60 has invalid quantization parameters.quantized_dimension must be in range [0, 1). Was 3.Tensor 64 has invalid quantization parameters.quantized_dimension must be in range [0, 1). Was 3.Tensor 68 has invalid quantization parameters.quantized_dimension must be in range [0, 1). Was 3.Tensor 72 has invalid quantization parameters.quantized_dimension must be in range [0, 1). Was 3.Tensor 76 has invalid quantization parameters.quantized_dimension must be in range [0, 1). Was 3.Tensor 80 has invalid quantization parameters.quantized_dimension must be in range [0, 1). Was 3.Tensor 84 has invalid quantization parameters.

Tensorflow version : 2.9.1
Python version: 3.10.4

How to solve this issue? Please guide

Thanks

使用后遇到的两个想讨论的点。

  1. 画面有缺失的躯干,预测骨架是脑补的,一直抖动。
  2. 当出现多人的,预测只有一个人能显示,但是预测骨架会在几个人身上来回变。

医疗场景中康复治疗的应用讨论

林哥你的这个开源项目突然让我想到一个医疗中使用的场景:
医院中有个科室叫做康复科,主要以促进残疾人及患者康复为主要目的。其中不乏很多需要判定患者在治疗中康复运动是否达标或到位,比如一个简单的抬脚、举手、弯腰等动作。
如果有了这个应用,患者或者自己就可以独立完成一些简单的动作训练,从而解放治疗师的时间,服务更多的患者。

看到林哥的样例使用的是摄像头,对于这个输入源,视频按道理也是可以的,毕竟同样使用的都是 SurfaceView ,如果能行,我是想通过选择本地视频,视频中播放患者做康复训练,在绘制出人体部位的同时,同时绘制出某个部位(比如膝盖)在训练中的移动轨迹。

林哥的这个项目确实很棒,从中其实可以挖掘出很多潜在的应用场景,欢迎大家前来讨论。

报错求解决

AttributeError Traceback (most recent call last)
in
12 image_bad = tf.io.decode_jpeg(image_bad)
13 person = detect(image_bad)
---> 14 _ = draw_prediction_on_image(image_bad.numpy(), person, crop_region=None,
15 close_figure=False, keep_input_size=True)

in draw_prediction_on_image(image, person, crop_region, close_figure, keep_input_size)
18 """
19 # Draw the detection result on top of the image.
---> 20 image_np = utils.visualize(image, [person])
21
22 # Plot the image with detection results.

AttributeError: module 'utils' has no attribute 'visualize'
类似这样的好多地方都找不到我要如何进行操作呢?

在生成姿态分类模型时报错

Define a Keras model for pose classification
print(landmarks.shape)结果(None, 17, 2)

ValueError: Exception encountered when calling layer 'flatten' (type Flatten).

Attempt to convert a value (None) with an unsupported type (<class 'NoneType'>) to a Tensor.

Call arguments received by layer 'flatten' (type Flatten):
• inputs=<KerasTensor: shape=(None, 17, 2) dtype=float32 (created by layer 'tf.math.truediv')>
为什么呀?

Sony多款機型閃退。

如題~
測試機型:1 III、10 II、XA2、XZ2。以上四機型皆在取得相機權限後閃退。

请教 想要自己训练动作,但最后生成tflite时报错

想要自己训练一些动作,编译大佬的文件报错

报错位置:
converter = tf.lite.TFLiteConverter.from_keras_model(model)
converter.optimizations = [tf.lite.Optimize.DEFAULT]
tflite_model = converter.convert()

报错信息:Some of the operators in the model are not supported by the standard TensorFlow Lite runtime. If those are native TensorFlow operators, you might be able to use the extended runtime by passing --enable_select_tf_ops, or by setting target_ops=TFLITE_BUILTINS,SELECT_TF_OPS when calling tf.lite.TFLiteConverter(). Otherwise, if you have a custom implementation for them you can disable this error with --allow_custom_ops, or by setting allow_custom_ops=True when calling tf.lite.TFLiteConverter(). Here is a list of builtin operators you are using: ADD, DIV, EXPAND_DIMS, FLOOR_DIV, FULLY_CONNECTED, GATHER, MAXIMUM, MUL, PACK, REDUCE_MAX, RESHAPE, SOFTMAX, SQRT, SQUEEZE, STRIDED_SLICE, SUB, SUM. Here is a list of operators for which you will need custom implementations: BroadcastTo, Size.

需要增加 这句: converter.allow_custom_ops=True

得到最终:16:23converter = tf.lite.TFLiteConverter.from_keras_model(model)
converter.optimizations = [tf.lite.Optimize.DEFAULT]
converter.allow_custom_ops=True
tflite_model = converter.convert()

这样编译通过了 但是得到的tflite的文件运行到AS上面跑不通,想知道up主为什么不需要加就能编译通过

请教

import org.tensorflow.posemon.data.BodyPart这个依赖中的posemon报红该怎么解决 安卓开发不太懂

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.