commit
566a56a2cb
|
@ -1,3 +1,4 @@
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|||
.idea/
|
||||
# Byte-compiled / optimized / DLL files
|
||||
__pycache__/
|
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*.py[cod]
|
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|
|
|
@ -0,0 +1,22 @@
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FROM nvidia/cuda:11.1.1-cudnn8-devel-ubuntu18.04
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ENV DEBIAN_FRONTEND noninteractive
|
||||
RUN apt-get update && apt-get install -y \
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python3-opencv ca-certificates python3-dev git wget sudo ninja-build
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||||
RUN ln -sv /usr/bin/python3 /usr/bin/python
|
||||
|
||||
COPY . /home/appuser
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||||
WORKDIR /home/appuser
|
||||
|
||||
# https://github.com/facebookresearch/detectron2/issues/3933
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ENV PATH="/home/appuser/.local/bin:${PATH}"
|
||||
RUN wget https://bootstrap.pypa.io/pip/3.6/get-pip.py && \
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||||
python3 get-pip.py && \
|
||||
rm get-pip.py
|
||||
|
||||
# install dependencies
|
||||
# See https://pytorch.org/ for other options if you use a different version of CUDA
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||||
RUN pip install -r requirements.txt
|
||||
RUN pip install torch==1.10 torchvision==0.11.1 -f https://download.pytorch.org/whl/cu111/torch_stable.html
|
||||
RUN pip install setuptools==59.5.0
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||||
RUN python setup.py develop
|
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@ -0,0 +1,8 @@
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|||
clean:
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||||
docker rm -f $$(docker ps -qa)
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||||
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||||
build-image:
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||||
docker build -t=deeppreid:v0 .
|
||||
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run:
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||||
nvidia-docker run -v ${PWD}:/home/appuser --name=deeppreid --net=host --ipc=host -it deeppreid:v0
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|
@ -84,6 +84,10 @@ Make sure `conda <https://www.anaconda.com/distribution/>`_ is installed.
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|||
# install torchreid (don't need to re-build it if you modify the source code)
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python setup.py develop
|
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|
||||
Another way to install is to run everything inside docker container:
|
||||
|
||||
- build: ``make build-image``
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||||
- run: ``make run``
|
||||
|
||||
Get started: 30 seconds to Torchreid
|
||||
-------------------------------------
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||||
|
|
|
@ -14,7 +14,7 @@ flake8
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|||
yapf
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||||
isort==4.3.21
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imageio
|
||||
|
||||
chardet
|
||||
# Export --------------------------------------
|
||||
# onnx
|
||||
# onnx-simplified
|
||||
|
|
Loading…
Reference in New Issue