I have been trying to import a model from onnx format to work with pytorch. I am finding it difficult to get an example for the same. As most of the resources in Internet talks about exporting a pytorch model to onnx.
I found that torch.onnx() can only export the model and the import method hasn't been implemented yet. A direct installation of onnx library, helps me to do onnx.load("model_name.onnx"). How do I use this model with pytorch? I am not able to move the model to GPU with model.to(device="GPU")
PyTorch doesn't currently support importing onnx models. As of writing this answer it's an open feature request.
While not guaranteed to work, a potential solution is to use a tool developed by Microsoft called MMdnn (no it's not windows only!) which supports conversion to and from various frameworks. Unfortunately onnx can only be a target of a conversion, and not a source. That said you may be able to import your model to another framework, then use MMdnn to convert from that framework to pytorch. Obviously this isn't ideal and the potential for success will depend on how other frameworks use onnx which may not be amenable to the way MMdnn works.
Update August 2022
Unfortunately it appears the feature request was rejected and Mmdnn has been abandoned. There are some more recent 3rd party tools that provide some ability to import onnx into pytorch like onnx2pytorch and onnx-pytorch. Neither of these tools appear to be actively developed, though pytorch and onnx are relatively stable at this point so hopefully these tools remain relevant in the future (official support would be better IMO). Note that both of these tools have unaddressed issues, so it may be necessary to try both of them if one doesn't work for you.
Update September 2022
Based on the comment from #DanNissenbaum there is a newer 3rd party tool onnx2torch that is being actively developed and maintained.
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In the latest version of the Anomaly Detection Service by Azure which supports the Multi-variate Cognitive Service, we need to train a model and then consume it.
The quickstart documentation for Python mentions a few libraries which are not getting imported:
from azure.ai.anomalydetector.models import DetectionRequest, ModelInfo
Both these libraries are throwing import errors.
How can we use the Multivariate Anomaly Detection Service using the Python SDK?
This error was with version azure-ai-anomalydetector==3.0.0b2. With version azure-ai-anomalydetector==3.0.0b3, this has been addressed.
The problem is because of the change of the response format recently. To solve that issue, you can change the line with error to
model_status = self.ad_client.get_multivariate_model(trained_model_id).model_info.status
There are a ton of questions dealing with OCR and Machine Learning, I am looking for guidance building my own from scratch.
I have an obscene number of photographs that contain text pertaining to the feature in the photo. The text is the latitude, longitude and id of the feature. I am looking for a way to extract this information into a text file to feed into my GIS.
I am sure Tesseract and Pytesseract would do exactly what I want, I however have a blocker in that I cannot load additional software onto the PC I am working on.
My PC is connected to a strictly controlled and secure network. I cannot install new software. I can however “pip install” any Python libraries needed, using a mobile hotspot. I have installed the Pytesseract library in Python. However if I have understood there is a dependency requiring a windows install file to be downloaded and installed before this works.
So I have decided to try (as a side project) create my own OCR model using Python and whatever libraries I need. The only issue is, there is a ton of information online and trying to find a focused and easy to follow process is not easy.
I am looking for resources detailing step by step what I need to do to create a training dataset, train a model and feed the images into the train model to get an output that makes sense.
I have been using OpenCv to process an image (crop, filter etc) to get bounding boxes of all the identifiable text in the test image. I am not sure where to go from there.
Are there any recommended tutorials online / resources that might make sense to a complete novice? I am using Python 3.5.
Bert is very powerful model for text classification but implementation of bert requires much more code than any other model. bert-text is pypi package to provide developer a ready-to-use solution.I have installed it properly.When I have tried to import ,it is throwing error ModuleNotFoundError: No module named 'bert_text'.I have properly written the name bert_text.
I have tried it in Kaggle,Colab and local machine but the error is same.
Hey as this is a refactor made by Yan Sun, This issue is already pending, you can go to this link and subscribe for an update when the developers will provide its solution. https://github.com/SunYanCN/bert-text/issues/1
I'm working with autodesk forge, because I have a project for the University, but I have a small problem now.
I read that the IFC Model Derivative processor is currently based on the Navisworks importer, but a better implementation is using Revit instead. As I work mostly with IFC Files this could make a big difference.
I made a small application with the help of the forge-apis npm package, which enables me to easily integrate the Forge APIs.
The Problem is that I don't see an option to use the new Model Derivative IFC pipeline. Is there a way to implement it in my application?
As this point, you'll need to make requests (e.g. using request package). When we completely move to Revit pipeline you can resume with the forge-api package.
I'm working on a project where my XNA 4.0 powered 3D engine needs to load external fbx models input by the user, in run time rather than in the default compile time way.
I understand XNA is built to bundle/process complex resources compile time to make the runtime smaller, but as I only need to target Windows I wonder if it is possible to load models with textures externally, and if so, how?
Yes, as #Andrew mentioned, using the built in content pipeline would require a developer install so that the content pipeline is available. Of course, you can parse it yourself and pull out the information at runtime to avoid that dependency. There are people out there doing it ... for example, the guys at sandswept studios have an API to do this, and are willing to discuss commercial agreements (just contact them):
http://thunderfist-podium.blogspot.com/2008/09/fbx-and-xna-part-1-fbx-format-and.html
I found the solution here:
http://create.msdn.com/en-US/education/catalog/sample/winforms_series_2