{
 "format": "oscr-script-manifest/1",
 "repository": "github.com/roc-hci/ufnet",
 "url": "https://github.com/ROC-HCI/UFNet",
 "host": "github.com",
 "commit": "5ece2c65ba184faccf6c8cdccdc03132427c464b",
 "license": "MIT",
 "license_confirmed_by": "license file LICENSE",
 "redistribution": "yes",
 "files": [
  {
   "path": "LICENSE",
   "sha256": "41ad449ead031774dcabfdc1fdb282aab6e39bc0457fd2c727386672672e50e7",
   "language": "License",
   "lines": 21,
   "truncated": false,
   "block": 6,
   "row": 1373
  },
  {
   "path": "README.md",
   "sha256": "bc9b4e0e02536b116a6790be4b9c2feda662c123f7402a4272ee78c6d6ce70a4",
   "language": "Text",
   "lines": 49,
   "truncated": false,
   "block": 8,
   "row": 10368
  },
  {
   "path": "code/constants.py",
   "sha256": "e43863bb682f0be57b0577f4db62367301d87fcdbe0c4355e1095a81f2afb9ed",
   "language": "Python",
   "lines": 24,
   "truncated": false,
   "block": 6,
   "row": 25828
  },
  {
   "path": "code/demographic_details/demography_summary_table.py",
   "sha256": "aceb474d7d7540021bb526a3917b945a2b966d8739cfcfe76c3788bbbc5a1929",
   "language": "Python",
   "lines": 227,
   "truncated": false,
   "block": 6,
   "row": 45477
  },
  {
   "path": "code/demographic_details/prepare_demographic_info_for_fusion_participants.py",
   "sha256": "18665716f643b888fa813342bca58224847debb7118c4759e7abf3b1e553f8fe",
   "language": "Python",
   "lines": 109,
   "truncated": false,
   "block": 6,
   "row": 38683
  },
  {
   "path": "code/fusion_models/baselines/majority_voting.py",
   "sha256": "aa1b5cacccccc087b592b11cd291804d3b5e05f86085cb5b0df49dab2fcd38a0",
   "language": "Python",
   "lines": 796,
   "truncated": false,
   "block": 7,
   "row": 10819
  },
  {
   "path": "code/fusion_models/baselines/majority_voting_drop_preds.py",
   "sha256": "6caf9ac6254c01a5c7d8c047afa08af9dcf04b53d446a9edaf6cc55a7ea407cf",
   "language": "Python",
   "lines": 805,
   "truncated": false,
   "block": 7,
   "row": 10867
  },
  {
   "path": "code/fusion_models/baselines/neural_early_fusion.py",
   "sha256": "20bfdfb7d9ee199e6269781ecdc007b308c200808785da17a7ac2d9972d36057",
   "language": "Python",
   "lines": 780,
   "truncated": false,
   "block": 7,
   "row": 10764
  },
  {
   "path": "code/fusion_models/baselines/neural_hybrid_fusion.py",
   "sha256": "f60f080bebb9d39ca3754a6fbdf0dd5b3ed939360e187307dda055b7cb6d17b8",
   "language": "Python",
   "lines": 852,
   "truncated": false,
   "block": 7,
   "row": 11108
  },
  {
   "path": "code/fusion_models/baselines/neural_late_fusion.py",
   "sha256": "1139925b2de1eb14ae6d53a0e272bdd651c9192b723c5dc46f1542870fe245d5",
   "language": "Python",
   "lines": 890,
   "truncated": false,
   "block": 7,
   "row": 11259
  },
  {
   "path": "code/fusion_models/ufnet/UFNet_no_withhold.py",
   "sha256": "17ada6a594ba5c0250c320733b2497f965eea5e950afe6a29108202352e02aa2",
   "language": "Python",
   "lines": 978,
   "truncated": false,
   "block": 7,
   "row": 11630
  },
  {
   "path": "code/fusion_models/ufnet/UFNet_withhold_predictions.py",
   "sha256": "b16df24fcac19d4e553bc9b80eee1798195ebe4832c52fd3c55b00081048b632",
   "language": "Python",
   "lines": 996,
   "truncated": false,
   "block": 7,
   "row": 11701
  },
  {
   "path": "code/fusion_models/ufnet/YoutubePD/uncertainty_aware_fusion_no_drop_youtubePD.py",
   "sha256": "a023b87adf63ae1e5c9b91613ba524addb2f5b21896f77f9a77ee8c43e5e8494",
   "language": "Python",
   "lines": 988,
   "truncated": false,
   "block": 7,
   "row": 11656
  },
  {
   "path": "code/fusion_models/ufnet/ablations/lrformer_attention_fusion_no_drops.py",
   "sha256": "2dd1debf393d863ced44a1aeef58194334b9c8c4ae3dcaa27b706cf4cf15bb03",
   "language": "Python",
   "lines": 1018,
   "truncated": false,
   "block": 7,
   "row": 11681
  },
  {
   "path": "code/fusion_models/ufnet/ablations/previous_attention_approach.py",
   "sha256": "24aaf84d15cba90ef63c97a243e15c7064f65a6d9e8ec170e8461660bfc01fad",
   "language": "Python",
   "lines": 963,
   "truncated": false,
   "block": 7,
   "row": 11600
  },
  {
   "path": "code/fusion_models/ufnet/ablations/uncertainty_aware_early_fusion.py",
   "sha256": "6b62f6d0e2605e29fea9503d4e0a83e968647c53d45110b36c059f0fed2fb776",
   "language": "Python",
   "lines": 978,
   "truncated": false,
   "block": 7,
   "row": 11615
  },
  {
   "path": "code/fusion_models/ufnet/ablations/uncertainty_aware_early_fusion_no_drops.py",
   "sha256": "ad4e645dc95494ea16b2c4ed7756c11abded241ee31f6d6204a21b81d70226a6",
   "language": "Python",
   "lines": 979,
   "truncated": false,
   "block": 7,
   "row": 11619
  },
  {
   "path": "code/fusion_models/ufnet/ablations/uncertainty_aware_fusion_conformal_preds.py",
   "sha256": "b0af4ffc2525d679fdf82dd8e0f3e27f2f5fceb88ea3709d4e301528aa75ba41",
   "language": "Python",
   "lines": 1072,
   "truncated": false,
   "block": 7,
   "row": 11891
  },
  {
   "path": "code/fusion_models/ufnet/ablations/uncertainty_aware_fusion_label_smoothing.py",
   "sha256": "c9cb43cd8950d7a999bb92c3d1c2c6d3fb06f138108f7d0cc9b4526788ed8f22",
   "language": "Python",
   "lines": 1021,
   "truncated": false,
   "block": 7,
   "row": 11762
  },
  {
   "path": "code/fusion_models/ufnet/ablations/uncertainty_aware_fusion_label_smoothing_conformal_prediction.py",
   "sha256": "f8898afa1c81c40f11950a7e939861653e795076da6e8a6504f0c5bf2ddd164c",
   "language": "Python",
   "lines": 1109,
   "truncated": false,
   "block": 8,
   "row": 57
  },
  {
   "path": "code/fusion_models/ufnet/ablations/uncertainty_aware_fusion_label_smoothing_platt_scaling_conformal_prediction.py",
   "sha256": "22c4932a40ce68df0239c860c090f79acc9e7e822808390aeddefbd4cf2d40b1",
   "language": "Python",
   "lines": 1155,
   "truncated": false,
   "block": 8,
   "row": 140
  },
  {
   "path": "code/fusion_models/ufnet/ablations/uncertainty_aware_fusion_no_drop_ece_loss.py",
   "sha256": "8bc4a5d307f1254da370c8a62a9ba89593fff154c38c24a178b0da5f34e97491",
   "language": "Python",
   "lines": 1031,
   "truncated": false,
   "block": 7,
   "row": 11809
  },
  {
   "path": "code/fusion_models/ufnet/ablations/uncertainty_aware_fusion_platt_scaling_conformal_preds.py",
   "sha256": "70421d70b0b075fc2e45087641a52594dced59cb37e68409af5e017f6024a217",
   "language": "Python",
   "lines": 1138,
   "truncated": false,
   "block": 8,
   "row": 103
  },
  {
   "path": "code/fusion_models/ufnet/analysis/analysis.py",
   "sha256": "ec020e216368bad8bd7ccd305ae562ecd8fbb37d730a95a105505d2b22845ae3",
   "language": "Python",
   "lines": 999,
   "truncated": false,
   "block": 7,
   "row": 11702
  },
  {
   "path": "code/fusion_models/ufnet/analysis/draw_final_plots.py",
   "sha256": "8a08b6653f237d3b655e88329edbb3bdff2332d203b10edecfa7e3bed68b4d5f",
   "language": "Python",
   "lines": 326,
   "truncated": false,
   "block": 7,
   "row": 5230
  },
  {
   "path": "code/fusion_models/ufnet/constants.py",
   "sha256": "cb28d4f811c9342a7b718c55d9aea9b45eecb87a6f573d566c9895da0f698812",
   "language": "Python",
   "lines": 24,
   "truncated": false,
   "block": 6,
   "row": 25974
  },
  {
   "path": "code/fusion_models/ufnet/count_trainable_params.py",
   "sha256": "faa5a8454db0f7bc23b8cb5072fcdffbdd7570dac1276a326b32e09b53cd9b51",
   "language": "Python",
   "lines": 880,
   "truncated": false,
   "block": 7,
   "row": 11257
  },
  {
   "path": "code/fusion_models/ufnet/multi_task_combinations.py",
   "sha256": "59e1f47ce94a5b2b178b01dc73d4b4ee5ff3f0ebb6cf6040a3bdb2a30622dfe4",
   "language": "Python",
   "lines": 972,
   "truncated": false,
   "block": 7,
   "row": 11614
  },
  {
   "path": "code/performance_analysis/bias_analysis.py",
   "sha256": "c6b8372b2dbcc525e1d85196b157d71138bdd2b776f50b636824defd0091068d",
   "language": "Python",
   "lines": 398,
   "truncated": false,
   "block": 7,
   "row": 5758
  },
  {
   "path": "code/performance_analysis/confidence_interval_using_random_seeds.py",
   "sha256": "390bdd0b142ff8138bf9aa0f0d8b283c949ffa337493f867cfa5e053a9ca8aff",
   "language": "Python",
   "lines": 38,
   "truncated": false,
   "block": 6,
   "row": 27550
  },
  {
   "path": "code/performance_analysis/sensitivity_specificity.py",
   "sha256": "2bf2e604ed9c43c880cc7e09cc21d014fbf2855e94658aa33a59a72603cf2155",
   "language": "Python",
   "lines": 91,
   "truncated": false,
   "block": 6,
   "row": 36076
  },
  {
   "path": "code/performance_analysis/threshold_vs_accuracy.py",
   "sha256": "aa682a60f2cb7d1e2da57e47bec46695788779482358ae5e7e3d8683279966fb",
   "language": "Python",
   "lines": 76,
   "truncated": false,
   "block": 6,
   "row": 34522
  },
  {
   "path": "code/unimodal_models/facial_expression_smile/constants.py",
   "sha256": "7a386f39540d0910110125ca9bcea5345b4aae2ab9e0d9c6b28bee3810349e97",
   "language": "Python",
   "lines": 19,
   "truncated": false,
   "block": 6,
   "row": 23327
  },
  {
   "path": "code/unimodal_models/facial_expression_smile/constants_baal.py",
   "sha256": "a45119e3db8db9d77ae50391dc100f0cfd742a4783662f2013bfc2f161b2ec67",
   "language": "Python",
   "lines": 19,
   "truncated": false,
   "block": 6,
   "row": 23359
  },
  {
   "path": "code/unimodal_models/facial_expression_smile/count_final_model_parameters.py",
   "sha256": "b93e427ca4392fc609bc077a188227130ded8af10e20a1db03050f7a25886fc1",
   "language": "Python",
   "lines": 518,
   "truncated": false,
   "block": 7,
   "row": 8028
  },
  {
   "path": "code/unimodal_models/facial_expression_smile/unimodal_smile.py",
   "sha256": "98bdd6584ab94594bd883cc6d6ee97bf57adf733860b80c0bf537d7b9a68572c",
   "language": "Python",
   "lines": 607,
   "truncated": false,
   "block": 7,
   "row": 9023
  },
  {
   "path": "code/unimodal_models/facial_expression_smile/unimodal_smile_baal.py",
   "sha256": "2e3431067b11ab46f3c7a1edbe558c4c27243fedd827923020abf499291b8cdd",
   "language": "Python",
   "lines": 595,
   "truncated": false,
   "block": 7,
   "row": 9120
  },
  {
   "path": "code/unimodal_models/facial_expression_smile/unimodal_smile_baal_youtubePD.py",
   "sha256": "2fc178655bf1cb71ea085111e0f3609c9e67eca587214582c11dbe7422c906a8",
   "language": "Python",
   "lines": 706,
   "truncated": false,
   "block": 7,
   "row": 10166
  },
  {
   "path": "code/unimodal_models/facial_expression_smile/unimodal_smile_video_embedding.py",
   "sha256": "3221b5ebf552ba8e73735428977340e1561dd1297aeefec4abefd8eeeee7a101",
   "language": "Python",
   "lines": 569,
   "truncated": false,
   "block": 7,
   "row": 8650
  },
  {
   "path": "code/unimodal_models/finger_tapping/constants.py",
   "sha256": "58891a093a428ddfa71f4319a4b4c44206fd0872b57dc30bf690bfb85de794e6",
   "language": "Python",
   "lines": 12,
   "truncated": false,
   "block": 6,
   "row": 23282
  },
  {
   "path": "code/unimodal_models/finger_tapping/constants_baal.py",
   "sha256": "9477f7b7dee5b5d0c6be5a1bbb9926bd667e63223fce5e4136da73b71d82309f",
   "language": "Python",
   "lines": 12,
   "truncated": false,
   "block": 6,
   "row": 23268
  },
  {
   "path": "code/unimodal_models/finger_tapping/count_trainable_params.py",
   "sha256": "66a138968cc9fef28023800ff8f47ac185d27431ec1788fbffca572dd67c0122",
   "language": "Python",
   "lines": 561,
   "truncated": false,
   "block": 7,
   "row": 8815
  },
  {
   "path": "code/unimodal_models/finger_tapping/unimodal_finger.py",
   "sha256": "8c63992a8573e58caa9f0de4c2df11bff6318d455de71a0bb5d4781dcd6b3d2c",
   "language": "Python",
   "lines": 652,
   "truncated": false,
   "block": 7,
   "row": 9666
  },
  {
   "path": "code/unimodal_models/finger_tapping/unimodal_finger_baal.py",
   "sha256": "1579f3f9356429ddadef7a08883759ae6406522bf4eeaff78ef1cbede8a8045e",
   "language": "Python",
   "lines": 643,
   "truncated": false,
   "block": 7,
   "row": 9697
  },
  {
   "path": "code/unimodal_models/finger_tapping/unimodal_finger_video_embedding.py",
   "sha256": "b1505662dea2588366b7e58c9b45857ef568a29946d302d27f4fdd93f300a0c7",
   "language": "Python",
   "lines": 588,
   "truncated": false,
   "block": 7,
   "row": 8903
  },
  {
   "path": "code/unimodal_models/quick_brown_fox/constants.py",
   "sha256": "a29b28ee5a824e7d046c1d90f5a500d80a81a6a9ce01263c770bbc1d96b0c5ec",
   "language": "Python",
   "lines": 15,
   "truncated": false,
   "block": 6,
   "row": 24408
  },
  {
   "path": "code/unimodal_models/quick_brown_fox/constants_baal.py",
   "sha256": "97e182e08acdac93c366804c533ddd46b926a76b3b7964feca3e2ba8b6bea7b0",
   "language": "Python",
   "lines": 15,
   "truncated": false,
   "block": 6,
   "row": 24427
  },
  {
   "path": "code/unimodal_models/quick_brown_fox/count_trainable_params.py",
   "sha256": "890d596867c977d52e122550fe11ba65d6753a66f1650fb84d260bd260054ff2",
   "language": "Python",
   "lines": 541,
   "truncated": false,
   "block": 7,
   "row": 8398
  },
  {
   "path": "code/unimodal_models/quick_brown_fox/unimodal_fox.py",
   "sha256": "73af009f0e6bf5d610b711f7b5a9218fd0023f55b35cb0a5af3046e70b86116e",
   "language": "Python",
   "lines": 618,
   "truncated": false,
   "block": 7,
   "row": 9231
  },
  {
   "path": "code/unimodal_models/quick_brown_fox/unimodal_fox_baal.py",
   "sha256": "0f72176b3d965af150ed4b3991a7e73b4d3341ea62143eee441cbf811ef49945",
   "language": "Python",
   "lines": 617,
   "truncated": false,
   "block": 7,
   "row": 9338
  },
  {
   "path": "code/unimodal_models/quick_brown_fox/unimodal_fox_baal_YouTubePD.py",
   "sha256": "8646c46ffb28afb5eb12710085559be9505f234345c44367f8324e20f2afecdf",
   "language": "Python",
   "lines": 610,
   "truncated": false,
   "block": 7,
   "row": 9241
  },
  {
   "path": "code/unimodal_models/quick_brown_fox/unimodal_fox_baal_YouTubePD_k_fold.py",
   "sha256": "ab6a3cfccd7c15f3afd5bcff2d7f2069a95936a5dfce23a97744ba987bd37ca9",
   "language": "Python",
   "lines": 699,
   "truncated": false,
   "block": 7,
   "row": 10036
  }
 ]
}