Currently I was following these steps to get the Forge Viewer into PowerBi. I was able to successfully get that to work but now I am attempting to get the properties out of the revit models.
I am following these steps found here
by editing this package forge-model-properties-excel
I am putting in a revit model that shows up as a 3D model in Forge viewer, and I know it has the material properties that I need. But when i run it i get the error that reads
this model has no {3D} view
I'm not sure why I am receiving this error if the model does have a 3D view.
Many thanks in advance.
The sample application is looking for a 3D view that is actually called "{3D}": https://github.com/xiaodongliang/forgeviewer_embed_in_powerbi_report/blob/70c58ab3217cdf4b10c475abf2721871984ed4e0/forge-model-properties-excel/index.js#L27.
Is it possible that the 3D views in your Revit model are named differently? If they are, make sure to update that line of code with the expected name.
Related
I'm thinking of generate a uml model for all models in my project. I tried the following packages but they didn't work for LoopBack4.
loopback-component-model-diagram
loopback-component-explorer
I added mountPath to component-config.json file. But it did not work!
I only see the swagger page, I can't see any uml model generated page.
{ "mountPath": "/modeldiagram" }
What should I do other than add mountpath or do you know of any package that generates uml model for the models?
I am working on deploy an ML that I trained using tensorflow (in Python). The model is saved as an .h5 file. After converting the model using the tensorflowjs_converter --input_format=keras ./model/myFile.h5 /JS_model/ command.
I imported the tensorflow library using the following:
<script src="https://cdn.jsdelivr.net/npm/#tensorflow/tfjs/dist/tf.min.js"> </script>
After this, I ws able to load the model using the loadLayersModel() function. However, when using the loadGraphModel, it does not work. It outputs this error on the browser:
''
I also tried using the tf.models.save_model.save() function in python which it outputs the variables and assets folders, as well as the .pb file. However, an error still occurs. Using the code above, changing only the path to 'THE_classifier' (which is the name of the folder where asset, variables and the .pb is located), the output is:
I want to work with the loadGraphModel() function because according to various sources, it provides a faster inference time.
layers models and graph models have different internal layout, they are not compatible and interchangable. if its a layers model, it must be loaded with tf.loadLayersModel and if its a graph model, it must be loaded with tf.loadGraphModel
graph models are frozen models - so if you want to convert keras model to graph, you need to freeze it first, else it can only be converted to layers model
(and thats where difference in inference time comes from - its faster to evaluate a frozen model than one that is still using variables)
I'm new to tensorflow and I have one question, My project has two majors part, first written in NodeJs that train my model from dataset and save model to local storage, so I have two files:
model.json
wights.bin
The second part is written in c++, After couple of days I could build tensorflow with bazel and add it to my OpenCv project, so here is my question :
I want to train my model in NodeJs part and use these models in my C++ part. Is this possible ?
also I saw tjs converter but it converts models to use in NodeJs not vice versa.
Update :
After searching a lot I figured out that I should convert my models to protobuff file, but tfjs-Converter does not support this type of conversion and another point is that I want to use my model with opencv library.
Update 2
Finally I could change my model to .pb file, first I use tfjs_converter to convert to keras model(.h5 file) and after that use this python script to convert to .pb file and opencv can successfully load model. But I got this error in using model :
libc++abi.dylib: terminating with uncaught exception of type
cv::Exception: OpenCV(4.1.0)
/tmp/opencv-20190505-12101-14vk1fh/opencv-4.1.0/modules/dnn/src/dnn.cpp:524:
error: (-2:Unspecified error) Can't create layer
"flatten_Flatten1/Shape" of type "Shape" in function
'getLayerInstance'
Any help ?
thanks
Finally i solved my own problem.
Here is the steps that I've done :
Convert my tfjs model to keras model using tfjs-converter
Using this python scripts to change keras(.h5) model to frozen model(.pb)
Use this tutorial to optimize my .pb model
Finally everything works great!
I am trying to understand Worklist/Demokit application https://sapui5.netweaver.ondemand.com/test-resources/sap/m/demokit/worklist/demokit.html from the source code in SAPUI5 SDK.
But some misunderstanding remains. E.g. where are the data coming from ? In usual Java applications it is clear - where are the service layer with Data Transfer Objects, where are the data repositories, where is the data access layer with ORM mapping and so on. But with this SAPUI5 example those notions seem to be irrelevant ?
I guess that source code should have data initialization code that creates records for Object 1, Object 2 and so on, but I can't find it.
It could be great to have detailed tutorial for this sample application.
The data is a static file as it's just a demo and comes from here: https://sapui5.netweaver.ondemand.com/test-resources/sap/m/demokit/worklist/test/service/Objects.json
I'm playing with rewriting part of a web application in Rails + Ext. However, I'm having trouble getting an associated models' name to display in the grid view.
I've been able to successfully convert several models and arrange the views nicely using tabs and Ext's layout helpers.
However, I'm in the middle of setting up an association -- I've followed along with Jon Barket's tutorial on how to do this using Ext -- and I've made all the Rails and JS changes suggested (with appropriate name changes for my models,) the result being that the combo box is now being correctly populated with the names of the associated models, and changes are actually written correctly to database, BUT the data doesn't show up in the column, it's just empty. However, the correct data is there in the 'detail' view.
Really just wondering if anyone else ran into this, or had any thoughts on what could be happening. Definitely willing to post code if requested; just note that (AFAIK) my changes follow the tutorial pretty closely.
Thanks in advance!
UPDATE:
Alright, slight progress - kind of. I can get the associated model id # displaying properly -- just by modifying the column model slightly. But I can't get the virtual attribute displayed in the main table (in Jon's example it's country_name.) It still goes blank when I change the data source for that column from
dataIndex: 'model[associated_model_id]'
to
dataIndex: 'virtual_attributes[associated_model_name]'
ANOTHER UPDATE:
Bump. Has NOBODY here tried integrating Ext with Rails?
OK, I should've paid closer attention to the tutorial and how I was using the API and other information available.
If you're using tabs to distinguish between several grid views, don't neglect to export to json any helper methods (you MUST do this in the controller for the model) -- especially ones for retrieving associated models' name!