ActiveLearning

Active Learning using Openset Recognition

TO RUN

python new_main.py --work-path=experiments/yaml file of your choice

All the YAML files are present in the experiments folder. Separate folder has been created for each experiment.

Some of the code for AL AND OPENSET RECOGNITION HAS been taken from the following repositories

Name		Name	Last commit message	Last commit date
Latest commit History 30 Commits
.ipynb_checkpoints		.ipynb_checkpoints
CrossDatasets		CrossDatasets
Dataparalle_lib		Dataparalle_lib
__pycache__		__pycache__
experiements		experiements
lib		lib
plots		plots
.DS_Store		.DS_Store
.gitignore		.gitignore
Final_Plots.ipynb		Final_Plots.ipynb
README.md		README.md
Untitled.ipynb		Untitled.ipynb
VAAL_Jupyter.ipynb		VAAL_Jupyter.ipynb
arguments.py		arguments.py
arguments_yaml.py		arguments_yaml.py
avg_meter.py		avg_meter.py
caltech101.py		caltech101.py
caltech256main.py		caltech256main.py
cifar100Resnet.py		cifar100Resnet.py
cifar100_5percent_budget.py		cifar100_5percent_budget.py
cifar100_biased_intial_pool.py		cifar100_biased_intial_pool.py
cifar100_corrupted_labels.py		cifar100_corrupted_labels.py
cross_dataset_evaluate_open.py		cross_dataset_evaluate_open.py
custom_datasets.py		custom_datasets.py
initialization.py		initialization.py
jupyter.yaml		jupyter.yaml
main.py		main.py
model.py		model.py
newmain.py		newmain.py
resenet.py		resenet.py
sampler.py		sampler.py
secondSample.py		secondSample.py
solver.py		solver.py
utils.py		utils.py
vgg.py		vgg.py
visualization.py		visualization.py

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