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Could not get models from the server

See original GitHub issue

My actions before raising this issue

[x ] Read/searched the docs
[x ] Searched past issues: I have checked all related issues

Expected Behaviour

I should see DL models in CVAT

Current Behaviour

After following the instructions, CVAT still cannot find any DL models. Whenever I open CVAT, it shows an error message Screenshot from 2020-09-30 12-13-44

Possible Solution

Not sure. Maybe I have missed something in installation?

Steps to Reproduce (for bugs)

Context

I want to use auto-segmentation for my segmentation tasks.

Your Environment

Git hash commit (git log -1): commit a5b2229039367e05cef7ea0f120bee2e33dd73ee (HEAD -> develop, origin/develop, origin/HEAD)
Docker version docker version (e.g. Docker 17.0.05): Docker 19.03.12
Are you using Docker Swarm or Kubernetes? No
Operating System and version (e.g. Linux, Windows, MacOS): Linux Ubuntu 20.04
Code example or link to GitHub repo or gist to reproduce problem:
Other diagnostic information / logs:

Some logs are in txt

error_dl_models.txt

Next steps

You may join our Gitter channel for community support.

Issue Analytics

State:
Created 3 years ago
Comments:5 (3 by maintainers)

Top GitHub Comments

4reactions

night-kuncommented, Oct 23, 2020

@yanmu2017 I run the command docker-compose -f docker-compose.yml -f components/serverless/docker-compose.serverless.yml up -d，but cvat still cannot find any DL models.

3reactions

yanmu2017commented, Oct 5, 2020

@azhavoro Thanks for the reply. Including the docker-compose command you mentioned solves the problem and I can see the models now.

One suggestion: Do you think it makes sense to include the docker-compose command docker-compose -f docker-compose.yml -f components/serverless/docker-compose.serverless.yml up -d" into the instruction of Semi-automatic and automatic annotation? Or at least a link to that webpage? For myself, I checked the instructions again and again but had never thought I should include another docker-compose command from a different webpage.

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