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two-to-tango

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0.0.4 two_to_tango-0.0.4-py3-none-any.whl

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Project: two-to-tango
Version: 0.0.4
Filename: two_to_tango-0.0.4-py3-none-any.whl
Download: [link]
Size: 32116
MD5: 4739598bcae04c607ec0b0d139614f44
SHA256: 7b41a7b04391427ef92edff7300e638d57d4331d23b7e71eeb31d9ce0e4e6406
Uploaded: 2021-02-13 19:31:33 +0000

dist-info

METADATA · WHEEL · RECORD · top_level.txt · entry_points.txt

METADATA

Metadata-Version: 2.1
Name: two-to-tango
Version: 0.0.4
Summary: Tango automatically detects duplicate bugs that are captured in bug reports that contain videos detailing the bug
Author: Nathan Cooper
Author-Email: nacooper01[at]email.wm.edu
Home-Page: https://github.com/ncoop57/two_to_tango
License: Apache Software License 2.0
Keywords: deep learning duplicate video detection android bug report
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Requires-Python: >=3.6
Requires-Dist: fastcore (==1.3.10)
Requires-Dist: fastprogress (==0.2.1)
Requires-Dist: ffmpeg-python (==0.2.0)
Requires-Dist: matplotlib (==3.1.1)
Requires-Dist: more-itertools (==8.0.2)
Requires-Dist: numpy (==1.19.1)
Requires-Dist: opencv-contrib-python (==3.4.1.15)
Requires-Dist: opencv-python (==3.4.1.15)
Requires-Dist: pandas (==0.25.3)
Requires-Dist: pytesseract (==0.3.5)
Requires-Dist: pytorch-lightning (==0.9.0)
Requires-Dist: requests (==2.25.0)
Requires-Dist: scikit-learn (==0.22.1)
Requires-Dist: torch (==1.6.0)
Requires-Dist: torchvision (==0.7.0)
Requires-Dist: tqdm (==4.41.1)
Description-Content-Type: text/markdown
[Description omitted; length: 9253 characters]

WHEEL

Wheel-Version: 1.0
Generator: bdist_wheel (0.36.2)
Root-Is-Purelib: true
Tag: py3-none-any

RECORD

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two_to_tango/approach.py sha256=iZTEz2tNLHlrlBdn3_RwZx4lDVGAQVFw9oVh-DyMpg8 11027
two_to_tango/cli.py sha256=w5n4tRg8UXLhWmxlqwx6u9Cu3G-C-ZQnsGca5f0M6Nw 9847
two_to_tango/combo.py sha256=SLcSnF1ggpui1PB1SCUcNhyxqEZP6cr3BX0hrDHvzNo 13298
two_to_tango/eval.py sha256=4DUkpglpxS8szCPFI9vu2tdHA7LjrFVr6puG1cTYiZE 9088
two_to_tango/features.py sha256=9u0w6Zr6gJf_VAdj1AN87O1mMdDL4UhPqzthbrq1BSI 6218
two_to_tango/model.py sha256=eCdtFlAQDucLaxrQGXOUueatWVHKeWz8lmcQZs8p-HI 9312
two_to_tango/prep.py sha256=Js3ax4A3RRVvfLqNkWQtq_XyCnV3AHqb2Z640XzMDKI 9309
two_to_tango/utils.py sha256=umkI8vOQL27qP32onzkRoVB4CJgPZ8Z_Bi1qmruNlIU 4599
two_to_tango-0.0.4.dist-info/LICENSE sha256=yYY3UzvIDr6uDWiyWCbw-Ml8EV2pjkNUaVgAxbGct1U 11340
two_to_tango-0.0.4.dist-info/METADATA sha256=CH7A80tmRlF02YZJdhP5nY_IWOwM9acnPM3kZDipqYE 10682
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two_to_tango-0.0.4.dist-info/entry_points.txt sha256=h1Aa6IOadmE2PUabweFXqyebXqdx5QsAjpYdmrsV3-Y 138
two_to_tango-0.0.4.dist-info/top_level.txt sha256=uZcm5Y3feiiXnw3unro_r8YOjwtmMjoOenKdjB2zCQA 13
two_to_tango-0.0.4.dist-info/RECORD — —

top_level.txt

two_to_tango

entry_points.txt

[console_scripts]
tango = two_to_tango.cli:tango
tango_download = two_to_tango.cli:download
tango_reproduce = two_to_tango.cli:reproduce