Commit a43dff4d authored by nikhil_rayaprolu's avatar nikhil_rayaprolu
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*.h5 filter=lfs diff=lfs merge=lfs -text
# Data files and directories common in repo root
datasets/
logs/
results/
temp/
test/
ngrok
*.ipynb
data/*
*.h5
# Byte-compiled / optimized / DLL files
__pycache__/
*.py[cod]
*$py.class
# Distribution / packaging
.Python
env/
build/
develop-eggs/
dist/
downloads/
eggs/
.eggs/
lib/
lib64/
parts/
sdist/
var/
wheels/
*.egg-info/
.installed.cfg
*.egg
# Installer logs
pip-log.txt
pip-delete-this-directory.txt
# VS Studio Code
.vscode
# PyCharm
.idea/
# Dropbox
.dropbox.attr
# Jupyter Notebook
.ipynb_checkpoints
# pyenv
.python-version
# dotenv
.env
# virtualenv
.venv
venv/
ENV/
FROM nvidia/cuda:10.0-cudnn7-runtime-ubuntu18.04
ENV DEBIAN_FRONTEND=noninteractive
RUN apt-get update && apt-get install -y \
build-essential \
bzip2 \
cmake \
curl \
git \
g++ \
libboost-all-dev \
pkg-config \
rsync \
software-properties-common \
sudo \
tar \
timidity \
unzip \
wget \
locales \
zlib1g-dev \
python3-dev \
python3 \
python3-pip \
python3-tk \
libjpeg-dev \
libpng-dev
# Python3
RUN pip3 install pip --upgrade
RUN pip3 install cython aicrowd_api timeout_decorator \
numpy \
matplotlib \
aicrowd-repo2docker \
pillow
RUN pip3 install git+https://github.com/AIcrowd/coco.git#subdirectory=PythonAPI
RUN pip3 install tensorflow-gpu
# Unicode support:
RUN locale-gen en_US.UTF-8
ENV LANG en_US.UTF-8
ENV LANGUAGE en_US:en
ENV LC_ALL en_US.UTF-8
# Enables X11 sharing and creates user home directory
ENV USER_NAME aicrowd
ENV HOME_DIR /home/$USER_NAME
#
# Replace HOST_UID/HOST_GUID with your user / group id (needed for X11)
ENV HOST_UID 1000
ENV HOST_GID 1000
RUN export uid=${HOST_UID} gid=${HOST_GID} && \
mkdir -p ${HOME_DIR} && \
echo "$USER_NAME:x:${uid}:${gid}:$USER_NAME,,,:$HOME_DIR:/bin/bash" >> /etc/passwd && \
echo "$USER_NAME:x:${uid}:" >> /etc/group && \
echo "$USER_NAME ALL=(ALL) NOPASSWD: ALL" > /etc/sudoers.d/$USER_NAME && \
chmod 0440 /etc/sudoers.d/$USER_NAME && \
chown ${uid}:${gid} -R ${HOME_DIR}
USER ${USER_NAME}
WORKDIR ${HOME_DIR}
COPY . .
RUN sudo chown ${HOST_UID}:${HOST_GID} -R *
RUN sudo chmod 775 -R *
\ No newline at end of file
Mask R-CNN
The MIT License (MIT)
Copyright (c) 2017 Matterport, Inc.
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in
all copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
THE SOFTWARE.
include README.md
include LICENSE
include requirements.txt
\ No newline at end of file
![CrowdAI-Logo](https://github.com/crowdAI/crowdai/raw/master/app/assets/images/misc/crowdai-logo-smile.svg?sanitize=true)
# crowdAI Mapping Challenge : Baseline
This repository contains the details of implementation of the Baseline submission using [Mask RCNN](https://arxiv.org/abs/1703.06870) which obtains a score of `[AP(IoU=0.5)=0.697 ; AR(IoU=0.5)=0.479]` for the [crowdAI Mapping Challenge](https://www.crowdai.org/challenges/mapping-challenge).
# Installation
```
git clone https://github.com/crowdai/crowdai-mapping-challenge-mask-rcnn
cd crowdai-mapping-challenge-mask-rcnn
# Please ensure that you use python3.6
pip install -r requirements.txt
python setup.py install
```
# Notebooks
Please follow the instructions on the relevant notebooks for the training, prediction and submissions.
* [Training](Training.ipynb)
* [Prediction and Submission](Prediction-and-Submission.ipynb)
(_pre-trained weights for baseline submission included_)
# Results
![sample_predictions](images/predictions.png)
# Citation
```
@misc{crowdAIMappingChallengeBaseline2018,
author = {Mohanty, Sharada Prasanna},
title = {CrowdAI Mapping Challenge 2018 : Baseline with Mask RCNN},
year = {2018},
publisher = {GitHub},
journal = {GitHub repository},
howpublished = {\url{https://github.com/crowdai/crowdai-mapping-challenge-mask-rcnn}},
commit = {bac1cf19adbc9d078122c6933da6f808c4ee590d}
}
```
# Acknowledgements
This repository heavily reuses code from the amazing [tensorflow Mask RCNN implementation](https://github.com/matterport/Mask_RCNN) by [@waleedka](https://github.com/waleedka/).
Many thanks to all the contributors of that project.
You are encouraged to checkout [https://github.com/matterport/Mask_RCNN](https://github.com/matterport/Mask_RCNN) for documentation on many other aspects of this code.
# Author
Sharada Mohanty [sharada.mohanty@epfl.ch](sharada.mohanty@epfl.ch)
{
"challenge_id" : "aicrowd-food-recognition-challenge",
"grader_id": "aicrowd-food-recognition-challenge",
"authors" : ["aicrowd-user"],
"description" : "Food Recognition Challenge Submission",
"license" : "MIT",
"gpu": true
}
\ No newline at end of file
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