FSOD

Installation

create soft link for dataset

../FSOD$ mkdir data
../FSOD/data$ ln -s <PATH_OF_DATASET> <NAME_OF_DATASET>

find detailed description in https://github.com/rbgirshick/py-faster-rcnn#beyond-the-demo-installation-for-training-and-testing-models

install conda packages

befor the installation, make sure your cuda version is 10.0

conda env create -f env.yml

install coco api

$ git clone https://github.com/pdollar/coco.git
$ cd ../coco/PythonAPI
$ make
$ make install
$ cd ../FSOD/lib
../FSOD/lib$ mv <PATH_TO_FRESH_GIT_CLONE>/coco/PythonAPI/pycocotools .

install _C related packages

$ cd ../FSOD/lib
$ python setup.py build develop

Name		Name	Last commit message	Last commit date
Latest commit History 8 Commits
.idea		.idea
__pycache__		__pycache__
cfgs		cfgs
lib		lib
ros_camera		ros_camera
static		static
templates		templates
.gitignore		.gitignore
OCID_preprocess.ipynb		OCID_preprocess.ipynb
README.md		README.md
_init_paths.py		_init_paths.py
app.py		app.py
env.yml		env.yml
evaluation.ipynb		evaluation.ipynb
generate_coco_20_test.ipynb		generate_coco_20_test.ipynb
generate_coco_60_train.ipynb		generate_coco_60_train.ipynb
generate_support_data.ipynb		generate_support_data.ipynb
inference.py		inference.py
inference_visualization.ipynb		inference_visualization.ipynb
oracle_inference.py		oracle_inference.py
run_one_im.py		run_one_im.py
simulation_predict.py		simulation_predict.py
test_net.py		test_net.py
trainval_net.py		trainval_net.py

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FSOD

Installation

create soft link for dataset

install conda packages

install coco api

install _C related packages

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