tleyden / docker Goto Github PK
View Code? Open in Web Editor NEWDocker files
docker's People
Contributors
Stargazers
Watchers
Forkers
chauthai bx5974 nakosung shuggiefisher freakthemighty boechat107 haiyangwang ajpierce teamvosh foremap xzw delta2323 orian trackdr vitorarins mainyaa malcolmgreaves wgqimut jamesli21 neowaylabs ftenaf maciejjaskowski sanjay-tiptur huhoo keer2012 halisyilboga1 4quant leopoldodonnell xuchongbo singularitymatrix khaiql wzh9801 sunatthegilddotcom liyong3forever cvdreamer ggamaral mstat adamsimet billym0rris gopishravs speedfl oyyf suneel453 kranthisai xoneso thanksmonica thiagozs amirsdream avisheka93 sfcodes ta2ozg sidwar76 subash211docker's Issues
duplicated pip install
Probably one pip install -r python/requirements.txt; is redundant.
line 98
RUN cd /opt/caffe && \
(pip install -r python/requirements.txt; easy_install numpy; pip install -r python/requirements.txt) && \pip flag provided but not defined
I got this message when trying to
$ sudo docker run -ti $DOCKER_NVIDIA_DEVICES tleyden5iwx/caffe-gpu /bin/bash
flag provided but not defined: --device /dev/nvidia0:/dev/nvidia0
Thanks.
Launcher script
The readme points to incorrect shell script...
https://raw.githubusercontent.com/tleyden/open-ocr/master/launcher/launcher.sh
The section "Launch docker images" links to launcher.sh script which is not available.
GPU installation failure
root@4258334d0ac4:/opt/caffe# ./examples/mnist/train_lenet.sh
I0206 03:58:44.393172 70 caffe.cpp:184] Using GPUs 0
modprobe: ERROR: ../libkmod/libkmod.c:556 kmod_search_moddep() could not open moddep file '/lib/modules/3.19.0-49-generic/modules.dep.bin'
F0206 03:58:44.400676 70 common.cpp:142] Check failed: error == cudaSuccess (38 vs. 0) no CUDA-capable device is detected
*** Check failure stack trace: ***
@ 0x7fdf188acb8d google::LogMessage::Fail()
@ 0x7fdf188aec8f google::LogMessage::SendToLog()
@ 0x7fdf188ac77c google::LogMessage::Flush()
@ 0x7fdf188af52d google::LogMessageFatal::~LogMessageFatal()
@ 0x7fdf18e92e17 caffe::Caffe::SetDevice()
@ 0x409f59 train()
@ 0x405fbb main
@ 0x7fdf17ddfec5 (unknown)
@ 0x406585 (unknown)
Aborted (core dumped)
root@4258334d0ac4:/opt/caffe# nvcc --version
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2014 NVIDIA Corporation
Built on Thu_Jul_17_21:41:27_CDT_2014
Cuda compilation tools, release 6.5, V6.5.12
lspci | grep -i nvidia
01:00.0 VGA compatible controller: NVIDIA Corporation GM107 [GeForce GTX 750 Ti] (rev a2)
01:00.1 Audio device: NVIDIA Corporation Device 0fbc (rev a1)
Using unofficial Tesseract4 PPA instead of compiling it
Thanks for Tesseract4 version of Open-OCR! I have some opinion for Tesseract4 Dockerfile. As mentioned in this issue title, how do you think to use an unofficial PPA for Tesseract4? The PPA is https://launchpad.net/~alex-p/+archive/ubuntu/tesseract-ocr and enable PPA and just install like Tesseract3:
RUN apt-get update && apt-get install -y software-properties-common && add-apt-repository ppa:alex-p/tesseract-ocr && apt-get update
# Get tesseract-ocr packages
RUN apt-get install -y \
libleptonica-dev \
libtesseract4 \
libtesseract-dev \
tesseract-ocr
# Get language data.
RUN apt-get install -y \
tesseract-ocr-ara \
tesseract-ocr-bel \
tesseract-ocr-ben \
tesseract-ocr-bul \
tesseract-ocr-ces \
tesseract-ocr-dan \
tesseract-ocr-deu \
tesseract-ocr-ell \
tesseract-ocr-fin \
tesseract-ocr-fra \
tesseract-ocr-heb \
tesseract-ocr-hin \
tesseract-ocr-ind \
tesseract-ocr-isl \
tesseract-ocr-ita \
tesseract-ocr-jpn \
tesseract-ocr-kor \
tesseract-ocr-nld \
tesseract-ocr-nor \
tesseract-ocr-pol \
tesseract-ocr-por \
tesseract-ocr-ron \
tesseract-ocr-rus \
tesseract-ocr-spa \
tesseract-ocr-swe \
tesseract-ocr-tha \
tesseract-ocr-tur \
tesseract-ocr-ukr \
tesseract-ocr-vie \
tesseract-ocr-chi-sim \
tesseract-ocr-chi-tra \
tesseract-ocr-eng
In this way, we don't install dev packages on Docker image.
Thanks.
Flag provided but not defined: -d
Greetings.
After upgrading wing version 1.10 the -d flag is not recognized.
docker -d
flag provided but not defined: -d
See 'docker --help'.
Add volume to the image
Hi,
I think it's very useful to have an volume in the image so that I can mount them to my host computer. In this way, we can put all the training/testing data or even log into that volume (aka shared folder), and then we can access these files outside the docker image. Also, we don't need to commit the process into image everytime we finish the traning/testing.
How do you feel about this?
Thanks.
Recommend Projects
-
React
A declarative, efficient, and flexible JavaScript library for building user interfaces.
-
Vue.js
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
-
Typescript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
-
TensorFlow
An Open Source Machine Learning Framework for Everyone
-
Django
The Web framework for perfectionists with deadlines.
-
Laravel
A PHP framework for web artisans
-
D3
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
-
Recommend Topics
-
javascript
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
-
web
Some thing interesting about web. New door for the world.
-
server
A server is a program made to process requests and deliver data to clients.
-
Machine learning
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
-
Visualization
Some thing interesting about visualization, use data art
-
Game
Some thing interesting about game, make everyone happy.
Recommend Org
-
Facebook
We are working to build community through open source technology. NB: members must have two-factor auth.
-
Microsoft
Open source projects and samples from Microsoft.
-
Google
Google ❤️ Open Source for everyone.
-
Alibaba
Alibaba Open Source for everyone
-
D3
Data-Driven Documents codes.
-
Tencent
China tencent open source team.