I’m trying to create simple model in 3dsmax. My model is just a square with two bones.
I wonder how to export it (whatever format), import to Away3d and control the bones.
I know that it’s must load a skeleton and get the bones by a name.
I was trying to use Prefab, but it didn’t work.
Any ideas or examples will very usefull.
Thanks!
Related
I am trying to build a key-points detection model for human, as there are many pretrained networks available to generate key-points, but i want to practice myself to create a keypoint detection model with custom dataset, cant find anything in web if someone have some info's then please share.
I want more points specified to the human body, but to do so i need to create a custom model to generate such kind of key-points in human body, i checked some annotation tools but those annotation tool helps to adjust the points they have already specified when taking dataset like COCO etc, i think we cant add more points to the image. i just want to build a new model with custom key-points.
please share your views about my view on to the problem and please suggest some links if you have any idea about the same
I have created a detailed github repo Custom Keypoint Detection for dataset preparation, model training and inference on Centernet-hourglass104 keypoint detection model based on Tensorflow Object detection API with examples.
This could help you in training your keypoint detection model on custom dataset.
Any issues related to the project can be raised in the github itself and doubts can be cleared here.
I’m new to deep learning and I was reading some state of art papers and I found that mask r-cnn is utterly used in segmentation and classification of images. I would like to apply it to my MSc project but I got some questions that you may be able to answer. I apologize if this isn’t the right place to do it.
First, I would like to know what are the best strategy to get the annotations. It seems kind of labor intensive and I’m not understanding if there is any easy way. Following that, I want to know if you know any annotation tool for mask r-cnn that generates the binary masks that are manually done by the user.
I hope this can turn into a productive and informative thread so any suggestion, experience would be highly appreciated.
Regards
You can use MASK-RCNN, I recommend it, is a two-stage framework, first you can scan the image and generate areas likely contain an object. And the second stage classifies the proposal drawing bounding boxes.
But the two-big question
how to train a model from scratch? And What happens when we want to
train our own dataset?
You can use annotations downloaded from the internet, or you can start creating your own annotations, this takes a lot of time!
You have tools like:
VIA GGC image annotator
http://www.robots.ox.ac.uk/~vgg/software/via/via_demo.html
it's online and you don't have to download any program. It is the one that I recommend you, save the images in a .json file, and so you can use the class of ballons that comes by default in SAMPLES in the framework MASK R-CNN, you would only have to put your json file and your images and to train your dataset.
But there are always more options, you have labellimg which is also used for annotation and is very well known but save the files in xml, you will have to make a few changes to your Class in python. You also have labelme, labelbox, etc.
I currently have 6 animated models each between 5Mb and 8Mb each. When using each one individually it can take a little time to download them. I need to load these models up as and when I need them and not in the preloader of libGdx. All 6 models will take a long time to download in the preloader so I'm trying to bypass it.
I've used both GWT and libGdx many times but not together. This project is purely a html one and I'm familiar with classes that need to be serialised so data can be transferred back and forth using GWT's RPC methods.
So far I've come up with 2 ideas of doing this:
Transfer the model data and rebuild the mesh from scratch. This
would take a lot of time and just wouldn't work. Plus it's likely I'll lose such data like animations.
Using LibGdx's
ModelData class which would work perfect, but unfortunately non of
the main class and sub classes are serialised.
The current project has interfaces that bridge the platform specific from the 'core' to the 'html' which can then async the RPC calls. These work with libGdx just great.
Is there a way of skipping the preloader and loading the models on demand when they are needed?
If you need anymore information I'll be glad to add that in.
Take a look at the Dynamic Asset Loading with libGDX and GWT example by MonsterOfCookie: https://github.com/MonsterOfCookie/libGDXGwtHtmlExample
Disadvantage is that you have to compile your own libGDX fork because Monster's PR was not merged. (But for working seriously with libGDX' GWT backend you'll probably need your own fork anyway)
I was consulting several references to discover how I may output trained Weka models into Java source code so that I may use the classifiers I am training in actual code for research applications I have been developing.
As I was playing with Weka 3.7, I noticed that while it does output Java code to its main text buffer when use simpler classification (supervised in my case this time) methods such as J48 decision tree, it removes the option (rather, it voids it by removing the ability to checkmark it and fades the text) to output Java code for RandomTree and RandomForest (which are the ones that give me the best performance in my situation).
Note: I am clicking on the "More Options" button and checking "Output source code:".
Does Weka not allow you to output RandomTree or RandomForest as Java code? If so, why? Or if it does and just doesn't put it in the output buffer (since RF is multiple decision trees which I imagine it doesn't want to waste buffer space), how does one go digging up where in the file system Weka outputs java code by default?
Are there any tricks to get Weka to give me my trained RandomForest as Java code? Or is Serialization of the output *.model files my only hope when it comes to RF and RandomTree?
Thanks in advance to those who provide help.
NOTE: (As an addendum to the answer provided below) If you run across a similar situation (requiring you to use your trained classifier/ML model in your code), I recommend following the links posted in the answer that was provided in response to my question. If you do not specifically need the Java code for the RandomForest, as an example, de-serializing the model works quite nicely and fits into Java application code, fulfilling its task as a trained model/hardened algorithm meant to predict future unlabelled instances.
RandomTree and RandomForest can't be output as Java code. I'm not sure for the reasoning why, but they don't implement the "Sourceable" interface.
This explains a little about outputting a classifier as Java code: Link 1
This shows which classifiers can be output as Java code: Link 2
Unfortunately I think the easiest route will be Serialization, although, you could maybe try implementing "Sourceable" for other classifiers on your own.
Another, but perhaps inconvenient solution, would be to use Weka to build the classifier every time you use it. You wouldn't need to load the ".model" file, but you would need to load your training data and relearn the model. Here is a starters guide to building classifiers in your own java code http://weka.wikispaces.com/Use+WEKA+in+your+Java+code.
Solved the problem for myself by turning the output of WEKA's -printTrees option of the RandomForest classifier into Java source code.
http://pielot.org/2015/06/exporting-randomforest-models-to-java-source-code/
Since I am using classifiers with Android, all of the existing options had disadvantages:
shipping Android apps with serialized models didn't reliably work across devices
computing the model on the phone took too much resources
The final code will consist of three classes only: the class with the generated model + two classes to make the classification work.
I'm looking for some simple (free!) entry level software that will allow me to create simple 3d models and export them in a format (JSON?) that can then be read into a webGL programme.
Simple geometry would be a start, then textures would be nice too... I've looked at Blender, and it's just far too advanced for me, and the tutorials I've found are hopeless.
Something simple like sketchup would be good, but afaik you can't export in JSON. I've found some converters that will do .dae to .json, but the ones I've found seem to be for advanced users.
WebGL is new enough that there aren't many packages like this built up around it just yet. That doesn't mean you don't have some options though:
Blender is a good modeler, and if you are willing to put a little bit more time into learning it you can use exporters from Three.js or some others that are around the net. This seems to be the most popular option at the moment.
Unity 3D is more of a scene builder than a modeling app, but it has a lot of ways to get content into it and both J3D and myself have implemented exporters from it.
Maya is a great modeling tool if you have a way to get access to it (it's commercial), and has Inka to get WebGL content out.
If you want to use something like SketchUp, it should be able to export to COLLADA, which can then be imported into Blender/Unity/What have you and exported from there using one of the previous methods.
As far as formats go, there's no real standards just yet. Most of the exporters will spit out JSON, mine uses a mix of JSON and Binary for speed/size, and some will actually give you Javascript code to execute. Which format to use probably depends on what you want to do with it. I encourage you to experiment with several and see what you like and what you don't.