initial commit

.gitignore

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+.ipynb_checkpoints
+*/.ipynb_checkpoints
+*.pyc
+
+.DS_Store
+
+test*.png
+test.ipynb
+test.py
+
+
+dist/
+visualpriors.egg-info
+MANIFEST
+

LICENSE

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+MIT License
+
+Copyright (c) Alexander Sax, Bradley Emi, Jeffrey Zhang, Amir R. Zamir, Silvio Savarese, Leonidas Guibas, Jitendra Malik.
+
+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.

MANIFEST.in

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+include README.md
+include LICENSE
+include requirements.txt
+include setup.cfg
+include setup.py

README.md

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+# Visual Priors
+
+
+# Intro
+This package contains the code for the paper:
+
+**Mid-Level Visual Representations Improve Generalization and Sample Efficiency for Learning Visuomotor Policies**. Arxiv preprint 2018. Alexander Sax, Bradley Emi, Amir R. Zamir, Silvio Savarese, Leonidas Guibas, Jitendra Malik.
+
+- For a fuller description and useful results and demos, and much more, see the website [http://perceptual.actor](http://perceptual.actor).
+- For the code for this repository, see [https://github.com/alexsax/visual-prior](https://github.com/alexsax/visual-prior).
+- For the full code from the paper, dockers to reproduce experiments, and more, see [https://github.com/alexsax/midlevel-reps](https://github.com/alexsax/midlevel-reps).
+
+
+### Citation
+If you find this repository or toolkit useful, then please cite:
+```
+@inproceedings{midLevelReps2018,
+ title={Mid-Level Visual Representations Improve Generalization and Sample Efficiency for Learning Visuomotor Policies.},
+ author={Alexander Sax and Bradley Emi and Amir R. Zamir and Leonidas J. Guibas and Silvio Savarese and Jitendra Malik},
+ year={2018},
+}
+```
+
+

requirements.txt

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+torch>=0.3.0

setup.cfg

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+# Inside of setup.cfg
+[metadata]
+description-file = README.md

setup.py

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+#!/usr/bin/env python3
+
+# Copyright (c) Alexander Sax, Bradley Emi, Jeffrey Zhang, Amir R. Zamir, Silvio Savarese, Leonidas Guibas, Jitendra Malik.
+# This source code is licensed under the MIT license found in the
+# LICENSE file in the root directory of this source tree.
+
+import glob
+import os.path
+import sys
+
+from distutils.core import setup
+
+
+sys.path.insert(0, os.path.join(os.path.dirname(__file__), "visualpriors"))
+
+with open("README.md", 'rb') as f:
+    readme = f.read().decode("UTF-8")
+
+with open("LICENSE") as f:
+    license = f.read()
+
+with open("requirements.txt") as f:
+    reqs = f.read()
+
+DISTNAME = "visualpriors"
+LONG_DESCRIPTION = readme
+REQUIREMENTS = reqs.strip().split("\n")
+
+if __name__ == "__main__":
+    setup(
+      name =         DISTNAME,
+      packages =     [DISTNAME],
+      version =      '0.3',
+      license=       'MIT',
+      description =  'The official implementation of visual priors from the paper Mid-Level Visual Representations Improve Generalization and Sample Efficiency for Learning Visuomotor Policies. Arxiv preprint 2018.',   
+      long_description_content_type='text/markdown',
+      long_description=LONG_DESCRIPTION,
+      author =       'Alexander Sax, Bradley Emi, Jeffrey Zhang, Amir R. Zamir, Silvio Savarese, Leonidas Guibas, Jitendra Malik', 
+      url =          'https://github.com/alexsax/midlevel-reps',
+      download_url = 'https://github.com/alexsax/visual-prior/archive/v0.2-alpha.tar.gz',
+      keywords =     ['computer vision',
+                      'robotics',
+                      'perception',
+                      'midlevel',
+                      'mid-level',
+                      'reinforcement learning',
+                      'machine learning', 
+                      'representation learning'],
+      install_requires=REQUIREMENTS,
+      classifiers=[
+        'Development Status :: 4 - Beta',
+        'Intended Audience :: Developers',
+        'Topic :: Software Development :: Build Tools',
+        'License :: OSI Approved :: MIT License', 
+        'Programming Language :: Python :: 2.7',
+        'Programming Language :: Python :: 3',
+        'Programming Language :: Python :: 3.4',
+        'Programming Language :: Python :: 3.5',
+        'Programming Language :: Python :: 3.6',
+        'Programming Language :: Python :: 3.7',
+      ],
+    )

visualpriors/__init__.py

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+from .transforms import representation_transform, multi_representation_transform, max_coverage_featureset_transform
+from .transforms import feature_readout, multi_feature_readout