FaceForensicsDataProcessing/poetry.lock at master · ondyari/FaceForensicsDataProcessing · GitHub

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[[package]]
category = "main"
description = "Composable command line interface toolkit"
name = "click"
optional = false
python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
version = "7.0"

[[package]]
category = "main"
description = "A toolkit for making real world machine learning and data analysis applications"
name = "dlib"
optional = false
python-versions = "*"
version = "19.18.0"

[[package]]
category = "main"
description = "Recognize faces from Python or from the command line"
name = "face-recognition"
optional = false
python-versions = "*"
version = "1.2.3"

[package.dependencies]
Click = ">=6.0"
Pillow = "*"
dlib = ">=19.7"
face-recognition-models = ">=0.3.0"
numpy = "*"

[[package]]
category = "main"
description = "Models used by the face_recognition package."
name = "face-recognition-models"
optional = false
python-versions = "*"
version = "0.3.0"

[[package]]
category = "main"
description = "Clean single-source support for Python 3 and 2"
name = "future"
optional = false
python-versions = ">=2.6, !=3.0.*, !=3.1.*, !=3.2.*"
version = "0.18.2"

[[package]]
category = "main"
description = "Lightweight pipelining: using Python functions as pipeline jobs."
name = "joblib"
optional = false
python-versions = "*"
version = "0.14.0"

[[package]]
category = "main"
description = "NumPy is the fundamental package for array computing with Python."
name = "numpy"
optional = false
python-versions = ">=3.5"
version = "1.17.4"

[[package]]
category = "main"
description = "Wrapper package for OpenCV python bindings."
name = "opencv-python"
optional = false
python-versions = "*"
version = "4.1.2.30"

[package.dependencies]
numpy = ">=1.11.1"

[[package]]
category = "main"
description = "Python Imaging Library (Fork)"
name = "pillow"
optional = false
python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*"
version = "6.2.1"

[[package]]
category = "main"
description = "Python 2 and 3 compatibility utilities"
name = "six"
optional = false
python-versions = ">=2.6, !=3.0.*, !=3.1.*"
version = "1.13.0"

[[package]]
category = "main"
description = "Tensors and Dynamic neural networks in Python with strong GPU acceleration"
name = "torch"
optional = false
python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*"
version = "1.3.1"

[package.dependencies]
future = "*"
numpy = "*"

[[package]]
category = "main"
description = "image and video datasets and models for torch deep learning"
name = "torchvision"
optional = false
python-versions = "*"
version = "0.4.2"

[package.dependencies]
numpy = "*"
pillow = ">=4.1.1"
six = "*"
torch = "1.3.1"

[[package]]
category = "main"
description = "Fast, Extensible Progress Meter"
name = "tqdm"
optional = false
python-versions = ">=2.6, !=3.0.*, !=3.1.*"
version = "4.38.0"

[metadata]
content-hash = "9f0c236b864871cc33e4ab14f9f6f38b97c08a41cd7d7ff79d465e1ba804a0bf"
python-versions = "^3.7"

[metadata.hashes]
click = ["2335065e6395b9e67ca716de5f7526736bfa6ceead690adf616d925bdc622b13", "5b94b49521f6456670fdb30cd82a4eca9412788a93fa6dd6df72c94d5a8ff2d7"]
dlib = ["8ca127253a0ca82a3d847148515f82ff2c504ed77a6385ec4f38c7f8e5360860"]
face-recognition = ["08c41397d3b899ed5b4a801646abd20935a2610ac4ba8643173db0aef6372f21", "a03eb709d1280bc3ca648add274ff741761b4c56f5317167252fc90cb519eda1"]
face-recognition-models = ["b79bd200a88c87c9a9d446c990ae71c5a626d1f3730174e6d570157ff1d896cf"]
future = ["b1bead90b70cf6ec3f0710ae53a525360fa360d306a86583adc6bf83a4db537d"]
joblib = ["006108c7576b3eb6c5b27761ddbf188eb6e6347696325ab2027ea1ee9a4b922d", "6fcc57aacb4e89451fd449e9412687c51817c3f48662c3d8f38ba3f8a0a193ff"]
numpy = ["0a7a1dd123aecc9f0076934288ceed7fd9a81ba3919f11a855a7887cbe82a02f", "0c0763787133dfeec19904c22c7e358b231c87ba3206b211652f8cbe1241deb6", "3d52298d0be333583739f1aec9026f3b09fdfe3ddf7c7028cb16d9d2af1cca7e", "43bb4b70585f1c2d153e45323a886839f98af8bfa810f7014b20be714c37c447", "475963c5b9e116c38ad7347e154e5651d05a2286d86455671f5b1eebba5feb76", "64874913367f18eb3013b16123c9fed113962e75d809fca5b78ebfbb73ed93ba", "683828e50c339fc9e68720396f2de14253992c495fdddef77a1e17de55f1decc", "6ca4000c4a6f95a78c33c7dadbb9495c10880be9c89316aa536eac359ab820ae", "75fd817b7061f6378e4659dd792c84c0b60533e867f83e0d1e52d5d8e53df88c", "7d81d784bdbed30137aca242ab307f3e65c8d93f4c7b7d8f322110b2e90177f9", "8d0af8d3664f142414fd5b15cabfd3b6cc3ef242a3c7a7493257025be5a6955f", "9679831005fb16c6df3dd35d17aa31dc0d4d7573d84f0b44cc481490a65c7725", "a8f67ebfae9f575d85fa859b54d3bdecaeece74e3274b0b5c5f804d7ca789fe1", "acbf5c52db4adb366c064d0b7c7899e3e778d89db585feadd23b06b587d64761", "ada4805ed51f5bcaa3a06d3dd94939351869c095e30a2b54264f5a5004b52170", "c7354e8f0eca5c110b7e978034cd86ed98a7a5ffcf69ca97535445a595e07b8e", "e2e9d8c87120ba2c591f60e32736b82b67f72c37ba88a4c23c81b5b8fa49c018", "e467c57121fe1b78a8f68dd9255fbb3bb3f4f7547c6b9e109f31d14569f490c3", "ede47b98de79565fcd7f2decb475e2dcc85ee4097743e551fe26cfc7eb3ff143", "f58913e9227400f1395c7b800503ebfdb0772f1c33ff8cb4d6451c06cabdf316", "fe39f5fd4103ec4ca3cb8600b19216cd1ff316b4990f4c0b6057ad982c0a34d5"]
opencv-python = ["04bec0a6d3a00360a7fb769b755ff4489a4ac8291821b785151f63e6d8bb59ea", "1a2d1801c038f055852bd2379186ca8b19b4ea24afb0b8410293bc802211579b", "1c7d235faef511aca7669f1aa650897b6c058dfde6412ea3fc58feb0fce78814", "22c2ee5f97f85903bfb28c056566b2ecaa1d2f804b880ab39ebf94528a402992", "25127990671dc8bd27ae8b880d7a39f9aae863052a8fbebe8977c6ce8e5fc0c9", "3cef82b6a1f748d2f4527f5932a86d54ebd10bd89f6cf59b003c36b1015055f7", "499a0413e7110a934ab56e635252a4c86f8be64de59f94a62318a7b895dc809e", "5f2cf5a0ab244a0a1dbe5ec426c277b55e06ac6a472ad61be77ef643a238cbd3", "5fec35916a6b9ce935f2e2806084303fd4e3fbb0c973a8db8f54b5aca54613cb", "6183c9c7fab4590e0651bc941cde780988c3ad9889bd62de19d581a6f59523ea", "67a236db8db84d7fb0f6e127f360ce6669350ef324839132e22879ec90588dab", "6c32d36f52a6e0c02d1ab0bb95223cb4dd5525a7e8292a747116126b3d34c578", "73a467a78ffd902d2c0265ab6b2e2cdda423d61b3d08685e0c7d0b4572142ff1", "76de8a247970d150b1672c6646cda91217d562682e713721fc9b9bf1434553c4", "919d5c3ec1a62258ba8c68b869b1056186e2355c4474739b199c295547e66cc1", "982d4e80c14356098cde57a6c7d18fe0928a1c3118675bac2252ef38f152e1ab", "9d025e6bf2989bcbc7744c26d8bd90c2629a92d8de3ba2416f62ce2a94615dd9", "bb59f98205cd81e29f45eed043cf0f98531486dc0b3f671c9e06fecf08f7ccef", "c8119248457e909dcd7b598621ed1d139419d69377e8cb4e2b2c49c819de287d", "ce7b1f25be04b04f2e678b2bf23a975137f77406dcee66a88a2daeb77cda3e76", "d64428bf59ab4d27620b00a2ad6fea2b4d62016a17849c82a7517ec12db97d55", "e2ffa3161b8662112f1880734e8b9549d0c9e818e59f652a9d1c5bf31e36586a", "e6fc00ac42c800fad5fb3927cfb9bf4e60bb3302cb9805f45b826d5d2546119a", "e793df2e12093b3a01006b5b27f321e306193c7a5c9e2a6c8bf652e1ad2d6a86", "eae543b3e9253ff702103333aabd87736b5ed5e46ab834d8e0b929f08f494dee", "f0af656402b73ead2d9f593c2774c04b01e2d0c63e4f99e0dc2f3fde99be22b4"]
pillow = ["047d9473cf68af50ac85f8ee5d5f21a60f849bc17d348da7fc85711287a75031", "0f66dc6c8a3cc319561a633b6aa82c44107f12594643efa37210d8c924fc1c71", "12c9169c4e8fe0a7329e8658c7e488001f6b4c8e88740e76292c2b857af2e94c", "248cffc168896982f125f5c13e9317c059f74fffdb4152893339f3be62a01340", "27faf0552bf8c260a5cee21a76e031acaea68babb64daf7e8f2e2540745082aa", "285edafad9bc60d96978ed24d77cdc0b91dace88e5da8c548ba5937c425bca8b", "384b12c9aa8ef95558abdcb50aada56d74bc7cc131dd62d28c2d0e4d3aadd573", "38950b3a707f6cef09cd3cbb142474357ad1a985ceb44d921bdf7b4647b3e13e", "4aad1b88933fd6dc2846552b89ad0c74ddbba2f0884e2c162aa368374bf5abab", "4ac6148008c169603070c092e81f88738f1a0c511e07bd2bb0f9ef542d375da9", "4deb1d2a45861ae6f0b12ea0a786a03d19d29edcc7e05775b85ec2877cb54c5e", "59aa2c124df72cc75ed72c8d6005c442d4685691a30c55321e00ed915ad1a291", "5a47d2123a9ec86660fe0e8d0ebf0aa6bc6a17edc63f338b73ea20ba11713f12", "5cc901c2ab9409b4b7ac7b5bcc3e86ac14548627062463da0af3b6b7c555a871", "6c1db03e8dff7b9f955a0fb9907eb9ca5da75b5ce056c0c93d33100a35050281", "7ce80c0a65a6ea90ef9c1f63c8593fcd2929448613fc8da0adf3e6bfad669d08", "809c19241c14433c5d6135e1b6c72da4e3b56d5c865ad5736ab99af8896b8f41", "83792cb4e0b5af480588601467c0764242b9a483caea71ef12d22a0d0d6bdce2", "846fa202bd7ee0f6215c897a1d33238ef071b50766339186687bd9b7a6d26ac5", "9f5529fc02009f96ba95bea48870173426879dc19eec49ca8e08cd63ecd82ddb", "a423c2ea001c6265ed28700df056f75e26215fd28c001e93ef4380b0f05f9547", "ac4428094b42907aba5879c7c000d01c8278d451a3b7cccd2103e21f6397ea75", "b1ae48d87f10d1384e5beecd169c77502fcc04a2c00a4c02b85f0a94b419e5f9", "bf4e972a88f8841d8fdc6db1a75e0f8d763e66e3754b03006cbc3854d89f1cb1", "c6414f6aad598364aaf81068cabb077894eb88fed99c6a65e6e8217bab62ae7a", "c710fcb7ee32f67baf25aa9ffede4795fd5d93b163ce95fdc724383e38c9df96", "c7be4b8a09852291c3c48d3c25d1b876d2494a0a674980089ac9d5e0d78bd132", "c9e5ffb910b14f090ac9c38599063e354887a5f6d7e6d26795e916b4514f2c1a", "e0697b826da6c2472bb6488db4c0a7fa8af0d52fa08833ceb3681358914b14e5", "e9a3edd5f714229d41057d56ac0f39ad9bdba6767e8c888c951869f0bdd129b0"]
six = ["1f1b7d42e254082a9db6279deae68afb421ceba6158efa6131de7b3003ee93fd", "30f610279e8b2578cab6db20741130331735c781b56053c59c4076da27f06b66"]
torch = ["0cec2e13a2e95c24c34f17d437f354ee2a40902e8d515a524556b350e12555dd", "134e8291a97151b1ffeea09cb9ddde5238beb4e6d9dfb66657143d6990bfb865", "31062923ac2e60eac676f6a0ae14702b051c158bbcf7f440eaba266b0defa197", "3b05233481b51bb636cee63dc761bb7f602e198178782ff4159d385d1759608b", "458f1d87e5b7064b2c39e36675d84e163be3143dd2fc806057b7878880c461bc", "72a1c85bffd2154f085bc0a1d378d8a54e55a57d49664b874fe7c949022bf071", "77fd8866c0bf529861ffd850a5dada2190a8d9c5167719fb0cfa89163e23b143", "b6f01d851d1c5989d4a99b50ae0187762b15b7718dcd1a33704b665daa2402f9", "d8e1d904a6193ed14a4fed220b00503b2baa576e71471286d1ebba899c851fae"]
torchvision = ["0f8245d6378acc86917f58492675f93df5279abae8bc5f832e3510722191f6c9", "1ad7593d94f6612ccb84a59467f0d10cdc213fb3e2bb91f1e773eb844787fa4c", "2553405b9afe3cedb410873b9877eb18b1526f8b01cb7c2747e51b69a936e0b5", "276a385f2f5fe484bf08467b5d081d9144b97eb458ba5b4a11e4640389e53149", "66deba9c577e36f4f071decdd894bf7ba794ac133dae64b3fd02fc3f0c6b989d", "7a458330e4efcd66f9f70127ab21fcf8cfea84acda8e707322fd2843aa6dd396", "8ff715c2323d9eca89126824ebfa74b282a95d6f64a4743fbe9b738d2de21c77", "dca4aadc12a123730957b501f9c5c2870d2f6727a2c28552cb7907b68b0ea10c", "dda25ce304978bba19e6543f7dcfee4f37d2f128ec83d4ab0c7e8f991d64865f"]
tqdm = ["9de4722323451eb7818deb0161d9d5523465353a6707a9f500d97ee42919b902", "c1d677f3a85fa291b34bdf8f770f877119b9754b32673699653556f85e2c2f13"]