pose-estimation | Human pose estimation using caffe framework | Machine Learning library
kandi X-RAY | pose-estimation Summary
kandi X-RAY | pose-estimation Summary
This project aims at estimating a rough pose out of images. For the same, body joints are classified such that each class represents a quadrant of 36 sized grid over the image. Connecting these joints gives a rough estimation of pose.
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pose-estimation Key Features
pose-estimation Examples and Code Snippets
Community Discussions
Trending Discussions on pose-estimation
QUESTION
I am trying to estimate the head pose of single images mostly following this guide: https://towardsdatascience.com/real-time-head-pose-estimation-in-python-e52db1bc606a
The detection of the face works fine - if i plot the image and the detected landmarks they line up nicely.
I am estimating the camera matrix from the image, and assume no lens distortion:
...ANSWER
Answered 2020-Nov-05 at 16:35Ok so it seems i have found a solution - the model points (which i have found in several blogs on the topic) seem to be wrong. The code seems to work with this combination of model and image points (no idea why it was trial and error):
QUESTION
My executable compiles, but then fails to run saying he cannot load a shared library. But the named library is right there (and LD_LIBRARY_PATH is set to right here too); and both objects are 64b.
...ANSWER
Answered 2020-May-04 at 05:19Who is complaining with "error while loading shared libraries: libmyelin.so.1: cannot open shared object file: No such file or directory" ?
The dynamic linker is.
What's the next debug step to resolve this issue?
Run file pose-estimator libmyelin.so.1. Chances are that one of them is 64-bit (x86_64) while the other is 32-bit (i386).
Update:
My guess was somewhat wrong: both files are for x86_64. But this file
QUESTION
I want to detect the orientation of phone to rotate the frame from camera, then my pose-estimation can inference this rotated image correctly.
Ex: Someone stands in front of my phone and I put my phone horizontally, then I want to rotate this image to be vertical before inference. Because the model just can catch the person in vertical.
I has tried this: var orientation = resources.configuration.orientation
But this only works when Screen's Auto-rotate is on and I don't want this. I don't my app is rotated.
...ANSWER
Answered 2019-Dec-13 at 14:59 val orientationEventListener = object : OrientationEventListener(activity) {
override fun onOrientationChanged(orientation: Int) {
val defaultPortrait = 0
val upsideDownPortrait = 180
val rightLandscape = 90
val leftLandscape = 270
when {
isWithinOrientationRange(orientation, defaultPortrait) -> {}
isWithinOrientationRange(orientation, leftLandscape) -> {}
isWithinOrientationRange(orientation, upsideDownPortrait) -> {}
isWithinOrientationRange(orientation, rightLandscape) -> {}
}
}
private fun isWithinOrientationRange(
currentOrientation: Int, targetOrientation: Int, epsilon: Int = 10
): Boolean {
return currentOrientation > targetOrientation - epsilon
&& currentOrientation < targetOrientation + epsilon
}
}
orientationEventListener.enable()
QUESTION
For this Humanpose Tensorflow network, network_cmu and base, it accepts only NHWC input format. If I construct the network in NCHW format, there is error as
...ANSWER
Answered 2019-Aug-30 at 05:45You can make use of tf.transpose to shift your axis from NHWC to NCHW
QUESTION
I'm working with ARKit and trying to get camera position from QR code with known size (0.16m). To detect QR code I'am using Vision framework so i can get each corner point on image.
Data preparation:
...ANSWER
Answered 2019-Aug-09 at 11:15The estimated translation between the camera and the tag is not correct. The tz is negative which is physically not possible. See here for the details about the camera coordinates system.
You have to be sure that each 3D object point matches with the corresponding 2D image point.
If I plot the 2D coordinates, I have the following image:
With RGBM the order of the points.
If you swap the last two image points, you should get:
QUESTION
I'm using the openvino toolkit in python for head position estimation. I load the network as follows:
...ANSWER
Answered 2019-Aug-01 at 10:05My question was solved by using model_headpose.forward(['angle_p_fc', 'angle_r_fc', 'angle_y_fc'])
QUESTION
I am new to Keras. I need some help in writing a custom loss function in keras with TensorFlow backend for the following loss equation.
The parameters passed to the loss function are :
-
y_truewould be of shape(batch_size, N, 2). Here, we are passing N(x, y)coordinates in each sample in the batch. y_predwould be of shape(batch_size, 256, 256, N). Here, we are passing N predicted heatmaps of256 x 256pixels in each sample in the batch.
i ∈ [0, 255]
j ∈ [0, 255]
Mn(i, j) represents value at pixel location (i, j) for the nth predicted heatmap.
Mn∼(i, j) = Guassian2D((i, j), y_truen, std) where
std = standard deviation, same standard deviation for both the dimensions (5 px).
y_truen is the nth (x, y) coordinate. This is the mean.
For details of this, please check the l2 loss described in this paper Human Pose Estimation.
Note : I mentioned batch_size in shape of y_true and y_pred. I assumed that Keras calls loss function on the entire batch and not on individual samples in the batch. Correct me if I am wrong.
...ANSWER
Answered 2017-Dec-11 at 03:56You can pretty much just translate the numpy functions into Keras backend functions. The only thing to notice is to set up the right broadcast shape.
QUESTION
I want to make this repo https://github.com/ildoonet/tf-pose-estimation run with Intel Movidius, so I tried convert the pb model using mvNCCompile.
The problem is mvNCCompile require a fixed input shape but the model I have is a dynamic one.
I tried this
...ANSWER
Answered 2019-Jun-02 at 09:20I manage to solve this problem using this.
QUESTION
I have a folder structure like so
...ANSWER
Answered 2019-May-21 at 03:07If your start script is located in .../pose/utils then every absolute import looks for modules there, too. This directory contains a module named logging (like the one in the standard library).
During the initialization of the numpy package (executing its __init__.py) and before numpy.testing is available the usual chain of imports happens (as can be seen in the traceback) which leads to the wrong logging module which in turn leads to import of _numpy_compat which tries to access numpy.testing too early.
To avoid this circular import problem you can either rename your logging module or move the start script to another directory.
QUESTION
I’m using a modified version of a gauss-newton method to refine a pose estimate using OpenCV. The unmodified code can be found here: http://people.rennes.inria.fr/Eric.Marchand/pose-estimation/tutorial-pose-gauss-newton-opencv.html
The details of this approach are outlined in the corresponding paper:
Marchand, Eric, Hideaki Uchiyama, and Fabien Spindler. "Pose estimation for augmented reality: a hands-on survey." IEEE transactions on visualization and computer graphics 22.12 (2016): 2633-2651.
A PDF can be found here: https://hal.inria.fr/hal-01246370/document
The part that is relevant (Pages 4 and 5) are screencapped below:
Here is what I have done. First, I’ve (hopefully) “corrected” some errors: (a) dt and dR can be passed by reference to exponential_map() (even though cv::Mat is essentially a pointer). (b) The last entry of each 2x6 Jacobian matrix, J.at(i*2+1,5), was -x[i].y but should be -x[i].x. (c) I’ve also tried using a different formula for the projection. Specifically, one that includes the focal length and principal point:
ANSWER
Answered 2019-May-13 at 08:40Edit: 2019/05/13
There is now solvePnPRefineVVS function in OpenCV.
Also, you should use x and y calculated from the current estimated pose instead.
In the cited paper, they expressed the measurements x in the normalized camera frame (at z=1).
When working with real data, you have:
(u,v): 2D image coordinates (e.g. keypoints, corner locations, etc.)K: the intrinsic parameters (obtained after calibrating the camera)D: the distortion coefficients (obtained after calibrating the camera)
To compute the 2D image coordinates in the normalized camera frame, you can use in OpenCV the function cv::undistortPoints() (link to my answer about cv::projectPoints() and cv::undistortPoints()).
When there is no distortion, the computation (also called "reverse perspective transformation") is:
x = (u - cx) / fxy = (v - cy) / fy
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Install pose-estimation
You can use pose-estimation like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
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