YOLO: docker-compose up fails - cannot get current_repodata.json from repo.anaconda.com
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When running within ../examples/yolo, docker-compose up fails with:
CondaHTTPError: HTTP 000 CONNECTION FAILED for url https://repo.anaconda.com/pkgs/main/linux-64/current_repodata.json
Looks like this URL might be stale:
curl -is http://repo.anaconda.com/pkgs/main/linux-64/current_repodata.json | head -n 1
HTTP/1.1 301 Moved Permanently
Possibly the required file is http://repo.anaconda.com/pkgs/main/linux-64/repodata.json
Have you tried to build the docker again? Probably, it was a temporary issue, I can't reproduce it on my side.
The problem persists.
sudo docker-compose up
...
=> ERROR [yolo stage-0 3/14] RUN conda update conda -y
CondaHTTPError: HTTP 000 CONNECTION FAILED for url <https://repo.anaconda.com/pkgs/main/linux-64/current_repodata.json>
When I check for the existence of current_repodata.json, I get this:
curl -is http://repo.anaconda.com/pkgs/main/linux-64/current_repodata.json | head -n 1
HTTP/1.1 301 Moved Permanently
Are you on windows?
Try solutions from this thread:
In your Dockerfile before RUN conda update conda -y try adding
RUN conda config --set ssl_verify no
if the line above doesn't work, try this:
RUN conda config --remove-key channels
if the lines above don't work, try this:
RUN conda config --remove-key proxy_servers
RUN conda clean --source-cache
Rebuild docker:
docker-compose build --no-cache
docker-compose up
@makseq , Thanks so much for your help.
I am running Linux (Ubuntu 22.04).
Tried all your suggested modifications to Dockerfile, but still no go.
Hm.. I am on ubuntu 22 as well, just tried to build it with --no-cache option, everything is ok..
My docker version:
makseq@makseq-ubnt:~$ docker version
Client: Docker Engine - Community
Version: 24.0.2
API version: 1.43
Go version: go1.20.4
Git commit: cb74dfc
Built: Thu May 25 21:52:13 2023
OS/Arch: linux/amd64
Context: default
Server: Docker Engine - Community
Engine:
Version: 24.0.2
API version: 1.43 (minimum version 1.12)
Go version: go1.20.4
Git commit: 659604f
Built: Thu May 25 21:52:13 2023
OS/Arch: linux/amd64
Experimental: false
containerd:
Version: 1.6.21
GitCommit: 3dce8eb055cbb6872793272b4f20ed16117344f8
runc:
Version: 1.1.7
GitCommit: v1.1.7-0-g860f061
docker-init:
Version: 0.19.0
GitCommit: de40ad0
You can try using it without docker. Create a new python virtual env and do these:
cd label_studio_ml/examples/yolo
pip install -r requirements.txt
python ./_wsgi.py
@makseq thanks for your help.
I created a virtual env and saved it in env in the top directory (label-studio-ml-backend).
I then execute these commands:
cd label_studio_ml/examples/yolo
pip install -r requirements.txt
python ./_wsgi.py
Got this result:
(env) aubrey@aubrey-PC5x-7xHP-HR-HS:~/label-studio-ml-backend$ /home/aubrey/label-studio-ml-backend/env/bin/python /home/aubrey/label-studio-ml-backend/label_studio_ml/examples/yolo/_wsgi.py
Traceback (most recent call last):
File "/home/aubrey/label-studio-ml-backend/label_studio_ml/examples/yolo/_wsgi.py", line 35, in <module>
from label_studio_ml.api import init_app
ModuleNotFoundError: No module named 'label_studio_ml'
I see that label_studio_ml/api is a couple of levels up the directory structure. After adding label_studio/api to my path,
Python got a little further but stopped when it could not find Flask.
Here's a list of my installed modules.
(env) aubrey@aubrey-PC5x-7xHP-HR-HS:~/label-studio-ml-backend$ pip list
Package Version
------------------------ -----------
certifi 2024.8.30
charset-normalizer 3.3.2
contourpy 1.3.0
cycler 0.12.1
filelock 3.16.1
fonttools 4.54.1
fsspec 2024.9.0
idna 3.10
Jinja2 3.1.4
kiwisolver 1.4.7
lightning-utilities 0.11.7
MarkupSafe 2.1.5
matplotlib 3.9.2
mpmath 1.3.0
networkx 3.3
numpy 1.26.4
nvidia-cublas-cu12 12.1.3.1
nvidia-cuda-cupti-cu12 12.1.105
nvidia-cuda-nvrtc-cu12 12.1.105
nvidia-cuda-runtime-cu12 12.1.105
nvidia-cudnn-cu12 9.1.0.70
nvidia-cufft-cu12 11.0.2.54
nvidia-curand-cu12 10.3.2.106
nvidia-cusolver-cu12 11.4.5.107
nvidia-cusparse-cu12 12.1.0.106
nvidia-nccl-cu12 2.20.5
nvidia-nvjitlink-cu12 12.6.77
nvidia-nvtx-cu12 12.1.105
opencv-python 4.10.0.84
packaging 24.1
pandas 2.2.3
pillow 10.4.0
pip 22.0.2
psutil 6.0.0
py-cpuinfo 9.0.0
pyparsing 3.1.4
python-dateutil 2.9.0.post0
pytz 2024.2
PyYAML 6.0.2
requests 2.32.3
scipy 1.14.1
seaborn 0.13.2
setuptools 59.6.0
six 1.16.0
sympy 1.13.3
torch 2.4.1
torchmetrics 1.4.2
torchvision 0.19.1
tqdm 4.66.5
triton 3.0.0
typing_extensions 4.12.2
tzdata 2024.2
ultralytics 8.2.103
ultralytics-thop 2.0.9
urllib3 2.2.3
wheel 0.37.1
Not quite sure how to proceed. Should I just continue by adding missing modules as they are detected?
cd label-studio-ml-backend
pip install -e .
Still struggling to get the yolo example working.
When I run docker-compose in for the yolo example dir, it errors out:
~/label-studio-ml-backend/label_studio_ml/examples/yolo$ docker-compose up
...
CondaHTTPError: HTTP 000 CONNECTION FAILED for url <https://repo.anaconda.com/pkgs/main/linux-64/current_repodata.json>
However, when I run docker-compose for the easyocr example, everything seems run perfectly. Does this indicate a problem with the yolo docker file?
aubrey@tensorbook2:~/label-studio-ml-backend/label_studio_ml/examples/easyocr$ docker-compose up
WARN[0000] The "TEST_ENV" variable is not set. Defaulting to a blank string.
[+] Running 14/14
✔ easyocr 13 layers [⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿] 0B/0B Pulled 330.2s
✔ 302e3ee49805 Pull complete 4.8s
✔ 4aeebc636537 Pull complete 2.5s
✔ 2aee89346c42 Pull complete 2.3s
✔ 0538735e543f Pull complete 3.6s
✔ 944b6eec9034 Pull complete 3.9s
✔ 5f8dc2ca6173 Pull complete 23.0s
✔ 9914c9719cd7 Pull complete 5.2s
✔ 35203abae53d Pull complete 26.4s
✔ c314f41d7225 Pull complete 7.9s
✔ 5502fbc37251 Pull complete 292.9s
✔ b5716c300228 Pull complete 24.3s
✔ 4f4fb700ef54 Pull complete 25.7s
✔ 3f039ec6f635 Pull complete 27.0s
[+] Running 2/2
✔ Network easyocr_default Created 0.1s
✔ Container easyocr Created 1.2s
Attaching to easyocr
easyocr | [2024-10-09 03:53:37 +0000] [6] [INFO] Starting gunicorn 22.0.0
easyocr | [2024-10-09 03:53:37 +0000] [6] [INFO] Listening at: http://0.0.0.0:9090 (6)
easyocr | [2024-10-09 03:53:37 +0000] [6] [INFO] Using worker: gthread
easyocr | [2024-10-09 03:53:38 +0000] [29] [INFO] Booting worker with pid: 29
Finally got docker-compose for the yolo example to run to completion on 2 Ubuntu laptops, but only after running docker compose for the easyocr example.
(base) aubrey@tensorbook2:~$ docker ps
CONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES
c3d5f18524d8 humansignal/yolo:v0 "/app/start.sh" 2 hours ago Up 2 hours 0.0.0.0:9090->9090/tcp, :::9090->9090/tcp yolo
I think it was related to your local problem with network. I am not sure it was related to easyocr, because easyocr uses completely different codebase and libraries.
Do I understand correctly that yolo docker compose run after you run easyocr?
@makseq Yes, yolo docker compose run only after I ran easyocr. Same result on 2 laptops.