What does inference.py produce ?
See original GitHub issueHi,
First, thanks for sharing and congratulation for your paper.
I’m trying to replicate your results using your code and after running for 1h the inference using:
python inference.py -lo 11
I’m only getting purple or black png images of depth, segmentation and normal. (Also, I’m wondering where in the code you used a Neural Network to produce the 2D layout proposal.)
Thanks, Elias
Issue Analytics
- State:
- Created 5 years ago
- Comments:6 (2 by maintainers)
Top Results From Across the Web
Create inference code and deploy code for machine learning ...
Create inference code and deploy code for machine learning in python · 1.Save the Model that was built using pickle as pickle file...
Read more >What is Machine Learning Inference? - Hazelcast
Machine learning inference is the process of running live data into a machine learning algorithm to calculate output such as a single numerical...
Read more >Inference Pipeline with Scikit-learn and Linear Learner
In many cases, when the trained model is used for processing real time or batch prediction requests, the model receives data in a...
Read more >Understanding Machine Learning Inference - Run:AI
Machine learning inference is the process of using a pre-trained ML algorithm to make predictions. How Does Machine Learning Inference Work? You need...
Read more >rdn4depth/inference.py at master - GitHub
INFERENCE_MODE_TRIPLETS = 'triplets' # Take image triplets as input. # For KITTI, we just resize input images and do not perform cropping. For....
Read more >Top Related Medium Post
No results found
Top Related StackOverflow Question
No results found
Troubleshoot Live Code
Lightrun enables developers to add logs, metrics and snapshots to live code - no restarts or redeploys required.
Start FreeTop Related Reddit Thread
No results found
Top Related Hackernoon Post
No results found
Top Related Tweet
No results found
Top Related Dev.to Post
No results found
Top Related Hashnode Post
No results found
Top GitHub Comments
Hi, We will push ‘osmesa.pyx’ file to the repo, you can try it again with this file. Usually inference.py could produce reasonable result if you can pass the test example of osmesa. Can you try to add ‘osmesa.render()’ in your example?
I encounter the same problem with nestarz, and I use the same way which replace the osmesa content with osmesa.py. But I get the following fault: infer 3D room layout and 3D object for sample 11 enter infer_pg loading CAD model 66cdea8432907e9fb99d331574136d26 bed exists and align success f1b1e6d1cb875b9f11c3739edd52fa3 dresser exists and align success 1316780d9b4a8ca71bb088904f7cb154 night_stand exists and align success b3836ad467e9f3157199c3a1b4ff8300 lamp exists and align success 859e9c3a93ad1f03e1f4f9b641386c6a picture exists and align success 3d6b55fe2deb2aa3a1c746794f191dc8 night_stand exists and align success b3836ad467e9f3157199c3a1b4ff8300 lamp exists and align success CAD model loaded successfully Depth=16 Stencil=8 Accum=0 Width=730 Height=530 Segmentation fault
I have already correct the scikit-learn version with “pip install scikit-learn==0.19.0”. So could you please give me some advice?
Thanks a lot!
The problem has already been solved with the solution of the “netstarz” that uses the osmesa.py file to replace the original osmesa content. But besides that, in order to be incompatible with the osmesa python file, some modifications should be made to the render_scene.py file as following: Line 787 osmesa.init_ctx(width, height) should be replaced with: ctx, buf = osmesa.init_ctx(width, height) Line 804: GL.glFlush() should be commented. Line 806 osmesa.free_ctx(“end”) should be replaced with: osmesa.free_ctx(ctx,buf)