Comments (2)
FROM dc/mxnet:cuda8.0
# docker build -t dc/mxnet:ctc-ocr .
# nvidia-docker run dc/mxnet:ctc-ocr python /mxnet/example/warpctc/lstm_ocr.py --gpus 0
RUN apt-get update && apt-get install -y cmake
# Install baidu warpctc
RUN cd / \
&& git clone https://github.com/baidu-research/warp-ctc \
&& cd warp-ctc \
&& mkdir build \
&& cd build \
&& cmake .. \
&& make \
&& make install \
&& cp ./libwarpctc.so /usr/lib
ADD ./warpctc-inl.h /mxnet/plugin/warpctc/
RUN cd /mxnet \
&& echo "WARPCTC_PATH = /warp-ctc" >>config.mk \
&& echo "MXNET_PLUGINS += plugin/warpctc/warpctc.mk" >>config.mk \
&& make clean \
&& make -j$(nproc)
RUN apt-get install -y python-pip python-dev
RUN pip install -i https://pypi.tuna.tsinghua.edu.cn/simple captcha
from awesome-ocr.
#FROM nvidia/cuda:7.5-cudnn4-devel
FROM nvidia/cuda:8.0-cudnn5-devel-ubuntu14.04
# docker build -t dc/mxnet:cuda8.0 .
# nvidia-docker run dc/mxnet:cuda8.0 python /mxnet/example/image-classification/train_mnist.py --gpus 0
MAINTAINER Mu Li <[email protected]>
RUN apt-get update && apt-get install -y apt-transport-https
ADD ./sources.list /etc/apt/sources.list
# install the core library
RUN apt-get update && apt-get install -y build-essential git libopenblas-dev libopencv-dev
RUN git clone --recursive https://github.com/wanghaisheng/mxnet/ && cd mxnet && \
cp make/config.mk . && \
echo "USE_CUDA=1" >>config.mk && \
echo "USE_CUDA_PATH=/usr/local/cuda" >>config.mk && \
echo "USE_CUDNN=1" >>config.mk && \
echo "USE_BLAS=openblas" >>config.mk && \
make -j$(nproc) ADD_LDFLAGS=-L/usr/local/cuda/lib64/stubs
ENV LD_LIBRARY_PATH /usr/local/cuda/lib64:$LD_LIBRARY_PATH
# python pakcage
RUN apt-get install -y python-numpy wget unzip
ENV PYTHONPATH /mxnet/python
sources.list
# 默认注释了源码镜像以提高 apt update 速度,如有需要可自行取消注释
deb https://mirrors.tuna.tsinghua.edu.cn/ubuntu/ trusty main restricted universe multiverse
# deb-src https://mirrors.tuna.tsinghua.edu.cn/ubuntu/ trusty main main restricted universe multiverse
deb https://mirrors.tuna.tsinghua.edu.cn/ubuntu/ trusty-updates main restricted universe multiverse
# deb-src https://mirrors.tuna.tsinghua.edu.cn/ubuntu/ trusty-updates main restricted universe multiverse
deb https://mirrors.tuna.tsinghua.edu.cn/ubuntu/ trusty-backports main restricted universe multiverse
# deb-src https://mirrors.tuna.tsinghua.edu.cn/ubuntu/ trusty-backports main restricted universe multiverse
deb https://mirrors.tuna.tsinghua.edu.cn/ubuntu/ trusty-security main restricted universe multiverse
# deb-src https://mirrors.tuna.tsinghua.edu.cn/ubuntu/ trusty-security main restricted universe multiverse
# 预发布软件源,不建议启用
# deb https://mirrors.tuna.tsinghua.edu.cn/ubuntu/ trusty-proposed main restricted universe multiverse
# deb-src https://mirrors.tuna.tsinghua.edu.cn/ubuntu/ trusty-proposed main restricted universe multiverse
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Related Issues (20)
- OCR basics HOT 1
- EAST:An Efficient and Accurate Scene Text Detector HOT 1
- Robust, Simple Page Segmentation using Hybrid Convolutional MDLSTM Networks
- PixelLink: Detecting Scene Text via Instance Segmentation
- Table-to-Text: Describing Table Region with Natural Language
- lable tools
- how to modify the connectionist Temporal Classification (CTC) layer of the network to also give us a confidence score? HOT 2
- Confidence Prediction for Lexicon-Free OCR HOT 1
- 工业制造——Workplace of automated control of vibration output circular trays HOT 3
- Tesseract for R HOT 1
- Cut, Paste and Learn: Surprisingly Easy Synthesis for Instance Detection
- 【Rosetta:大规模图像文字检测识别系统】《Rosetta: Large scale system for text detection and recognition in images》[Facebook] (2018) O HOT 4
- Radical analysis network for zero-shot learning in printed Chinese character recognition HOT 3
- DenseRAN for Offline Handwritten Chinese Character Recognition HOT 3
- Deep TextSpotter: An End-to-End Trainable Scene Text Localization and Recognition Framework
- in marmot data set the table BBOX are not matching with original images
- dhSegment: A generic deep-learning approach for document segmentation
- null
- 2018年末撸串计划 HOT 5
- 希望可以增加PaddleOCR、AgentOCR HOT 3
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