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config.py
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import os, sys
import multiprocessing
from datetime import datetime
from easydict import EasyDict as edict
__C = edict()
cfg = __C
# DIRECTORIES ============================================================================
__C.DIR = edict()
__C.DIR.ROOT = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
__C.DIR.LAMEM_ROOT = os.path.join(__C.DIR.ROOT, "datasets", "LaMem")
__C.DIR.MEMENTO_ROOT = os.path.join(__C.DIR.ROOT, "datasets", "Memento10k")
__C.DIR.VIDEOMEM_ROOT = os.path.join(__C.DIR.ROOT, "datasets", "VideoMem")
__C.DIR.WEIGHTS = os.path.join(__C.DIR.ROOT, "weights")
__C.DIR.PICKLE = os.path.join(__C.DIR.ROOT, "pickle")
__C.DIR.FIGURES = os.path.join(__C.DIR.ROOT, "figs")
__C.DIR.ROOT_DIRS = {"Memento10k": __C.DIR.MEMENTO_ROOT, "LaMem": __C.DIR.LAMEM_ROOT, "VideoMem": __C.DIR.VIDEOMEM_ROOT}
# CONSTANTS ==============================================================================
__C.CONST = edict()
__C.CONST.NUM_WORKERS = multiprocessing.cpu_count()
__C.CONST.DATE = datetime.now().strftime("%m%d-%H%M%S")
__C.CONST.WANDB_USERNAME = ""
__C.CONST.WANDB_PROJECT = ""
# SIMILARITY PARAMETERS =================================================================
__C.SIMILARITY = edict()
__C.SIMILARITY.OVERWRITE_PICKLE = False
__C.SIMILARITY.PCA = edict()
__C.SIMILARITY.PCA.COMP = 10
__C.SIMILARITY.FRACTIONAL = edict()
__C.SIMILARITY.FRACTIONAL.F = 0.5
__C.SIMILARITY.PROTO = edict()
__C.SIMILARITY.PROTO.CLASSES = edict()
__C.SIMILARITY.PROTO.CLASSES.KDE_THRESH = 780
__C.SIMILARITY.PROTO.KMEANS = edict()
__C.SIMILARITY.PROTO.KMEANS.K = 20
__C.SIMILARITY.DBSCAN = edict()
__C.SIMILARITY.DBSCAN.HRNET_EPS = 1.25
__C.SIMILARITY.DBSCAN.CSN_EPS = 0.9
# TRAIN PARAMETERS =======================================================================
__C.TRAIN = edict()
__C.TRAIN.SEED = None
__C.TRAIN.DATASET = "Memento10k"
# INPUT
__C.TRAIN.DATA_AUGMENTATION = False
# RAW
__C.TRAIN.USE_RAW = False # <==
__C.TRAIN.RAW_FEATURES = ["hog","brightness","contrast","blurriness","size_orig","meanOF"]
__C.TRAIN.NORMALIZE_RAW = True
__C.TRAIN.COMPUTE_RAW = False
__C.TRAIN.USE_TEMPORAL_STD = False
# HRNET & CSN
__C.TRAIN.FIXED_FEATURES = True
__C.TRAIN.USE_HRNET = False # <==
__C.TRAIN.USE_CSN = False # <==
__C.TRAIN.HRNET_FRAMES = 1
__C.TRAIN.CSN_ARCH = "ip_csn_152"
# SIMILARITY
__C.TRAIN.USE_SIMILARITY = False # <==
__C.TRAIN.SIMILARITY_METHODS = ["dbscan"]
__C.TRAIN.SIMILARITY_FEATURES = ["hrnet", "ip_csn_152"]
__C.TRAIN.NORMALIZE_SIMILARITY = True
# MLP
__C.TRAIN.HIDDEN_CHANNELS = [512, 64] # <==
__C.TRAIN.PREDICT_ALPHA = False
# TRAINING
__C.TRAIN.BATCH_SIZE = 32
__C.TRAIN.LOSS = "mse"
__C.TRAIN.MSETAILS = edict()
__C.TRAIN.MSETAILS.POW = 4
__C.TRAIN.MSETAILS.MULT_FACT = 2
__C.TRAIN.LEARNING_RATE = 0.001
__C.TRAIN.EPOCHS = 20
__C.TRAIN.OPTIMIZER = "Adam"
__C.TRAIN.WEIGHT_DECAY = 1e-5
__C.TRAIN.SCHEDULER = "StepLR"
__C.TRAIN.SCHEDULER_GAMMA = 0.2
__C.TRAIN.SCHEDULER_STEP_SIZE = 5
# CHECKPOINT
__C.TRAIN.CHECKPOINT_LOCAL = False
__C.TRAIN.CHECKPOINT_RUN_ID = None
__C.TRAIN.CHECKPOINT_EPOCH = None
# DATASETS ===============================================================================
__C.DATASET = edict()
__C.DATASET.MEAN_MEM_SCORE = edict()
__C.DATASET.MEAN_MEM_SCORE.MEMENTO10K = 0.80099205
__C.DATASET.MEAN_MEM_SCORE.VIDEOMEM = 0.85900025
# FEATURES & SIMILARITY ==================================================================
FEATURES_INFO = {
"hog": {"file_extension": ".npy", "folder_name": "hog", "nb_features": 10, "has_temporal_std": True},
"brightness": {"file_extension": ".txt", "folder_name": "brightness", "nb_features": 1, "has_temporal_std": True},
"contrast": {"file_extension": ".txt", "folder_name": "contrast", "nb_features": 1, "has_temporal_std": True},
"blurriness": {"file_extension": ".txt", "folder_name": "blurriness", "nb_features": 1, "has_temporal_std": True},
"meanOF": {"file_extension": ".txt", "folder_name": "meanOF", "nb_features": 1, "has_temporal_std": False},
"size_orig": {"file_extension": ".txt", "folder_name": "size_orig", "nb_features": 1, "has_temporal_std": False},
"hrnet": {"file_extension": ".npy", "folder_name": "hrnet", "nb_features": None, "has_temporal_std": None},
"ip_csn_152": {"file_extension": ".npy", "folder_name": "ip_csn_152", "nb_features": None, "has_temporal_std": None},
}
SIMILARITY_INFO = {
"kde": {"file_extension": ".txt", "folder_name": "kde", "nb_features": 1},
"cosine_mean": {"file_extension": ".txt", "folder_name": "cosine_mean", "nb_features": 1},
"cosine_threshold0.4": {"file_extension": ".txt", "folder_name": "cosine_threshold0.4", "nb_features": 1},
"cosine_threshold0.5": {"file_extension": ".txt", "folder_name": "cosine_threshold0.5", "nb_features": 1},
"cosine_threshold0.7": {"file_extension": ".txt", "folder_name": "cosine_threshold0.7", "nb_features": 1},
"fractional_mean": {"file_extension": ".txt", "folder_name": "fractional_mean", "nb_features": 1},
# "dbscan": {"file_extension": ".txt", "folder_name": "dbscan", "nb_features": 699 / 2}, # VideoMem
"dbscan": {"file_extension": ".txt", "folder_name": "dbscan", "nb_features": 852 / 2}, # Memento10k
# "euclidean_to_prototypes_classes": {"file_extension": ".npy", "folder_name": "euclidean_to_prototypes", "nb_features": 551},
# "fractional_to_prototypes_classes": {"file_extension": ".npy", "folder_name": "fractional_to_prototypes", "nb_features": 551},
# "kde_to_prototypes_classes150": {"file_extension": ".npy", "folder_name": "kde_to_prototypes_classes150", "nb_features": 31},
# "kde_to_prototypes_classes200": {"file_extension": ".npy", "folder_name": "kde_to_prototypes_classes200", "nb_features": 18},
# "kde_to_prototypes_classes500": {"file_extension": ".npy", "folder_name": "kde_to_prototypes_classes500", "nb_features": 4},
# "kde_to_prototypes_classes600": {"file_extension": ".npy", "folder_name": "kde_to_prototypes_classes600", "nb_features": 3},
# "kde_to_prototypes_classes700": {"file_extension": ".npy", "folder_name": "kde_to_prototypes_classes700", "nb_features": 2},
# "kde_to_prototypes_classes780": {"file_extension": ".npy", "folder_name": "kde_to_prototypes_classes780", "nb_features": 1},
# "kde_to_prototypes_kmeans10": {"file_extension": ".npy", "folder_name": "kde_to_prototypes_kmeans20", "nb_features": 10},
# "kde_to_prototypes_kmeans20": {"file_extension": ".npy", "folder_name": "kde_to_prototypes_kmeans20", "nb_features": 20},
# "kde_to_prototypes_kmeans100": {"file_extension": ".npy", "folder_name": "kde_to_prototypes_kmeans100", "nb_features": 100},
}
FEATURES_NORM = {
"Memento10k": {
"hog": {"mean": [-0.0382179, -0.22634703, -0.00150232, 0.0013018, -0.00560051, -0.00287241, -0.0159254, -0.00977024, 0.02961693, -0.00804713], "std": [0.95244716, 0.88563999, 0.90972137, 0.93445912, 0.89927394, 0.86414983, 0.83028538, 0.85960258, 0.88835483, 0.84949636], "temporal_std_mean": [0.14341384, 0.1638313, 0.2335052, 0.17836176, 0.26769911, 0.29168933, 0.25390074, 0.33578141, 0.29800854, 0.33817726], "temporal_std_std": [0.13432926, 0.15721098, 0.19555975, 0.20175324, 0.215271, 0.24034389, 0.20351628, 0.26407597, 0.24913998, 0.25800772]},
"brightness": {"mean": [97.13908673], "std": [33.66215848], "temporal_std_mean": [5.21281299], "temporal_std_std": [6.02105021]},
"contrast": {"mean": [55.5621269], "std": [16.47006963], "temporal_std_mean": [2.66262172], "temporal_std_std": [3.25779011]},
"blurriness": {"mean": [159369.90274394627], "std": [131901.81111343787], "temporal_std_mean": [2.03508193], "temporal_std_std": [3.24568579]},
"meanOF": {"mean": [1.56105642e+05], "std": [1.29022102e+05]},
"size_orig": {"mean": [192004.81357143], "std": [183295.11417806]},
},
"LaMem": {
"hog": {"mean": [1.40450614e-16, -2.23554508e-16, 1.01148719e-16, -6.24690423e-16, 7.80992555e-17, -3.79934356e-16, -7.09185797e-16, -2.55928612e-16, 6.81494367e-16, 6.57400060e-16], "std": [0.99998889, 0.99998889, 0.99998889, 0.9999889, 0.99998889, 0.99998893, 0.99998908, 0.99998924, 0.99998962, 0.99999899]},
"brightness": {"mean": [96.39162514], "std": [38.53091113]},
"contrast": {"mean": [57.84879775], "std": [15.49616822]},
"blurriness": {"mean": [19.0881984], "std": [12.0214119]},
"meanOF": {"mean": [0.], "std": [1.]},
"size_orig": {"mean": [46811.95104444], "std": [60458.10262618]},
},
"VideoMem": {
"hog": {"mean": [-0.17517713, -0.18438714, 0.02393828, 0.01537374, 0.01757276, 0.05515971, -0.04763976, 0.22417781, 0.06289709, -0.02335175], "std": [0.88695109, 0.91342727, 0.88481261, 0.86333332, 0.87152722, 0.88787376, 0.811698, 0.80004389, 0.85398853, 0.83688581], "temporal_std_mean": [0.16191116, 0.16150428, 0.20691784, 0.29213597, 0.26313414, 0.26835597, 0.349666, 0.20939079, 0.31025446, 0.32044117], "temporal_std_std": [0.14518682, 0.14145836, 0.18033176, 0.25559498, 0.21566336, 0.2129636, 0.29899839, 0.20482844, 0.23169207, 0.27375623]},
"brightness": {"mean": [103.64720883], "std": [26.90399581], "temporal_std_mean": [3.93361737], "temporal_std_std": [4.88398109]},
"contrast": {"mean": [52.10466492], "std": [15.25342803], "temporal_std_mean": [2.4982247], "temporal_std_std": [3.04715098]},
"blurriness": {"mean": [12.65053648], "std": [12.67609755], "temporal_std_mean": [1.91609483], "temporal_std_std": [2.98691579]},
"meanOF": {"mean": [7371403.97225931], "std": [7770817.85414596]},
"size_orig": {"mean": [844920.80646154], "std": [588518.23408164]},
},
}
SIMILARITY_NORM = {
"Memento10k": {
"kde": {"hrnet": {"mean": [14.13289021], "std": [0.82832219]}, "ip_csn_152": {"mean": [13.63923493], "std": [0.98586239]}},
"cosine_mean": {"hrnet": {"mean": [-0.0013218], "std": [0.31010361]}, "ip_csn_152": {"mean": [0.00517577], "std": [0.30699529]}},
"cosine_threshold0.4": {"hrnet": {"mean": [0.11885661], "std": [0.01205031]}, "ip_csn_152": {"mean": [0.1211845], "std": [0.01935108]}},
"cosine_threshold0.5": {"hrnet": {"mean": [0.07275114], "std": [0.01228284]}, "ip_csn_152": {"mean": [0.08137358], "std": [0.0165468]}},
"cosine_threshold0.7": {"hrnet": {"mean": [0.01857217], "std": [0.00867206]}, "ip_csn_152": {"mean": [0.02951553], "std": [0.01397899]}},
"fractional_mean": {"hrnet": {"mean": [69.89534288], "std": [16.76528599]},"ip_csn_152": {"mean": [68.8305914], "std": [20.12121926]}},
"dbscan": {"hrnet": {"mean": 434 * [0], "std": 434 * [1]}, "ip_csn_152": {"mean": 418 * [0], "std": 418 * [1]}},
# "euclidean_to_prototypes_classes": {"hrnet": {"mean": [4.15528278, 4.87425447, 3.55117751, 3.3001708, 3.23360811, 3.40316481, 3.25435629, 3.35443029, 4.08440181, 3.30251194, 3.30992964, 4.02940194, 3.28330086, 4.13599917, 3.4048463, 4.16359138, 3.18855803, 3.94561009, 3.24842093, 3.30052014, 3.94828582, 3.21980151, 4.24882258, 3.47441432, 4.54705222, 4.40772873, 3.79465117, 3.28035656, 3.49378176, 3.31639971, 3.35377333, 3.50786705, 3.57584738, 3.40585588, 3.12175036, 3.15487175, 3.38171198, 3.48641164, 3.44023164, 3.29100644, 3.57802157, 3.15237937, 3.2698516, 3.50382712, 3.54895845, 3.11609798, 3.47105636, 3.96730006, 3.39005426, 3.19399298, 3.42533819, 3.26774761, 3.59395989, 3.29637924, 3.51836899, 3.84466526, 3.45070242, 3.76241361, 3.47048079, 4.3682103, 3.26221896, 3.33371847, 3.59165039, 3.25373742, 3.24016296, 4.93156564, 3.36737751, 3.82117368, 3.41116757, 3.77713729, 3.27340045, 3.97522923, 3.3903892, 3.78634518, 3.32092746, 3.30716627, 3.38598703, 3.92813748, 3.43106228, 3.26642671, 3.35068798, 3.24288345, 4.17798301, 3.27020754, 3.2940334, 3.21445241, 3.63430154, 3.26678865, 4.0750684, 3.2878011, 4.07682943, 3.28816481, 3.40496762, 3.90459213, 3.76383899, 3.34816416, 3.66973382, 3.52937345, 3.59766337, 3.23814078, 4.97432074, 3.4901742, 3.94360086, 3.76126042, 3.23211026, 3.47068194, 3.56290865, 3.30334336, 3.31551521, 3.29418007, 3.84260374, 4.44666829, 3.52075779, 3.36322962, 3.37002534, 3.48644867, 5.16256195, 3.23726073, 3.32097883, 3.3216635, 3.83026305, 3.98485917, 4.28505581, 3.43342134, 3.53396297, 3.32070224, 4.46695559, 3.35601244, 3.16581183, 3.31420756, 3.72406672, 5.40664274, 3.45378712, 4.41990374, 3.90262083, 3.13534112, 3.21821053, 3.66708887, 3.35194695, 3.54792256, 3.22669983, 3.4166425, 3.26492305, 3.36197158, 3.41301881, 3.1757372, 3.34175646, 3.49731505, 3.31415694, 3.56232593, 3.25581809, 3.2367482, 4.47411426, 4.5575136, 3.3483189, 3.53578683, 3.53307058, 3.20333079, 3.50561127, 3.54709618, 3.57319425, 4.20306356, 3.76937797, 3.33996187, 3.17922767, 3.53030002, 4.67440479, 3.32817045, 3.51843746, 3.28425957, 3.25112147, 3.99905755, 3.27787163, 3.2837399, 3.36011529, 3.15021473, 3.34506338, 3.73690572, 3.82547581, 3.57349698, 3.16362142, 3.56109992, 3.45474138, 3.53161132, 3.52969377, 4.66494972, 3.24585129, 3.7439742, 3.58129896, 3.73065592, 3.56808725, 3.87349593, 3.49544382, 3.23464178, 3.16384016, 3.3504074, 3.20775558, 3.66518122, 4.44497181, 3.19148065, 4.30256722, 3.4224182, 3.52299466, 3.17715998, 3.53665407, 5.62932057, 3.30413414, 4.83646621, 3.5470925, 3.28462128, 3.53090448, 3.15468067, 3.90824656, 3.16108493, 3.37229332, 3.83505186, 3.65831876, 4.14984091, 4.29519038, 3.29664936, 3.54322562, 4.75941397, 3.34359379, 3.13915719, 4.45363678, 3.36008418, 3.34290223, 3.39453715, 3.3111802, 3.24623263, 3.87866852, 3.30772428, 3.29080058, 3.34118524, 3.31334789, 3.72571009, 4.266038, 3.29735624, 3.26302757, 3.35894326, 3.15787852, 3.85664848, 3.5157592, 3.54145311, 3.28212009, 3.72370989, 3.24497673, 3.92653296, 3.46113644, 4.24619947, 3.3424882, 3.49065494, 3.37372322, 5.15118948, 3.513655, 3.205621, 3.23120986, 3.8639885, 3.22980258, 3.46362962, 3.33460902, 3.28178199, 3.39486014, 3.30861728, 3.16261588, 3.69729912, 3.4592164, 3.50832175, 3.49584088, 3.26408481, 3.14030205, 3.27201907, 3.5385356, 3.47400748, 3.62500977, 3.54866563, 3.57584738, 3.50992147, 3.53108611, 3.24214983, 3.78187471, 3.67280169, 4.32537133, 3.45511659, 5.19273952, 3.11693697, 3.90978495, 4.00722021, 3.19439414, 3.64002002, 3.54524382, 3.33332088, 3.12753607, 3.27740646, 4.25965627, 3.45379748, 3.72772086, 4.01188838, 3.40875, 3.28337934, 3.49447587, 3.24099737, 4.14964571, 3.7356084, 4.03358312, 4.28505581, 3.49553469, 3.69286997, 4.41360901, 3.40456258, 4.15625998, 3.40876348, 4.37834639, 3.35947014, 3.38302902, 3.32174953, 3.18119079, 4.61514607, 3.54651449, 4.54494105, 4.12776741, 3.78611944, 3.32649222, 3.53050062, 3.17317659, 4.33162212, 3.19854721, 3.3360076, 3.84805272, 3.29899265, 3.37136702, 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22.69477948, 24.96249194, 22.34245039, 20.58640945, 21.88847767, 23.53200469, 25.31459679, 23.28146847, 21.76126172, 19.48588006, 21.02405527, 24.16099606, 20.15956842, 20.71166135, 25.57852197, 21.62011318, 22.38144101, 25.67866363, 24.41845116, 22.13119222, 27.15981882, 24.24727036, 25.67658906, 23.18990097, 28.30114956, 20.3036605, 19.86704791, 28.22719956, 20.24539519, 21.9251681, 25.61957242, 23.4073201, 21.27664218, 20.49662786, 21.95014926, 27.50632306, 21.30541307, 26.52805743, 23.11428114, 26.4252126, 24.22816863, 19.78773209, 25.64484147, 22.06691855, 22.73742575, 25.61958142, 23.51029555, 24.04266018, 23.13539499, 22.73015667, 23.64474898, 27.59576218]}},
# "kde_to_prototypes_classes150": {"hrnet": {"mean": [15.33654553, 16.43358429, 15.96255264, 15.60559235, 16.23126162, 15.50533406, 15.52833249, 15.33632729, 15.37133918, 15.93806476, 16.9051538, 14.91026522, 14.7152787, 14.96822446, 15.84258106, 14.75020603, 16.98383817, 15.8222063, 15.25110109, 15.42304396, 14.59129181, 16.67201982, 15.11616775, 14.54922884, 14.50605813, 14.17027901, 15.41513717, 16.4244924, 14.73062627, 15.03495944, 15.91698542], "std": [0.81946399, 6.31921616, 3.58142792, 3.03124908, 5.47292776, 4.43305037, 4.03951983, 4.12370512, 2.34091302, 1.68894966, 6.57352205, 1.31942012, 1.96785071, 1.39584005, 5.35266085, 1.60235252, 6.74942337, 3.47992787, 4.20665076, 2.17970805, 1.57444516, 7.85331525, 1.3071989, 1.12071092, 2.89359779, 2.79637197, 2.37508038, 4.73446573, 2.01207555, 0.94961215, 2.9651725]}, "ip_csn_152": {"mean": [14.72161593, 18.31994797, 16.86198242, 16.69094938, 16.80293194, 18.62055235, 20.96207711, 17.1262007, 16.82757083, 17.41371424, 17.08816073, 14.68897382, 15.17919362, 14.15221288, 17.14903666, 14.59615673, 19.34845134, 17.71446898, 15.51179461, 15.66798123, 14.70753083, 17.95256277, 14.51374755, 14.29228051, 15.29630915, 13.87423271, 16.79089082, 19.9454318, 15.77052384, 13.96413982, 16.25146552], "std": [1.64160624, 8.48986725, 3.24998211, 7.83064742, 7.18571742, 11.07576992, 11.62758959, 8.75030728, 8.20018824, 6.66647347, 4.38703772, 2.26862047, 1.5286806, 3.64064376, 8.87948065, 4.84725685, 10.83032804, 7.8283753, 3.58809479, 2.35583981, 1.45023346, 10.38851582, 2.53871755, 1.52556117, 1.31104394, 1.66272092, 6.62419554, 10.89346293, 1.22374374, 1.93966849, 5.90938704]}},
# "kde_to_prototypes_classes200": {"hrnet": {"mean": [16.23126162, 15.50533406, 15.52833249, 16.9051538, 14.91026522, 14.7152787, 15.84258106, 14.75020603, 15.25110109, 14.59129181, 16.67201982, 15.11616775, 14.54922884, 14.50605813, 14.17027901, 16.4244924, 14.73062627, 15.03495944], "std": [5.47292776, 4.43305037, 4.03951983, 6.57352205, 1.31942012, 1.96785071, 5.35266085, 1.60235252, 4.20665076, 1.57444516, 7.85331525, 1.3071989, 1.12071092, 2.89359779, 2.79637197, 4.73446573, 2.01207555, 0.94961215]}, "ip_csn_152": {"mean": [16.80293194, 18.62055235, 20.96207711, 17.08816073, 14.68897382, 15.17919362, 17.14903666, 14.59615673, 15.51179461, 14.70753083, 17.95256277, 14.51374755, 14.29228051, 15.29630915, 13.87423271, 19.9454318, 15.77052384, 13.96413982], "std": [7.18571742, 11.07576992, 11.62758959, 4.38703772, 2.26862047, 1.5286806, 8.87948065, 4.84725685, 3.58809479, 1.45023346, 10.38851582, 2.53871755, 1.52556117, 1.31104394, 1.66272092, 10.89346293, 1.22374374, 1.93966849]}},
# "kde_to_prototypes_classes500": {"hrnet": {"mean": [15.11616775, 14.50605813, 14.17027901, 15.03495944], "std": [1.3071989, 2.89359779, 2.79637197, 0.94961215]}, "ip_csn_152": {"mean": [14.51374755, 15.29630915, 13.87423271, 13.96413982], "std": [2.53871755, 1.31104394, 1.66272092, 1.93966849]}},
# "kde_to_prototypes_classes600": {"hrnet": {"mean": [15.11616775, 14.17027901, 15.03495944], "std": [1.3071989, 2.79637197, 0.94961215]}, "ip_csn_152": {"mean": [14.51374755, 13.87423271, 13.96413982], "std": [2.53871755, 1.66272092, 1.93966849]}},
# "kde_to_prototypes_classes700": {"hrnet": {"mean": [14.17027901, 15.03495944], "std": [2.79637197, 0.94961215]}, "ip_csn_152": {"mean": [13.87423271, 13.96413982], "std": [1.66272092, 1.93966849]}},
# "kde_to_prototypes_classes780": {"hrnet": {"mean": [15.03495944], "std": [0.94961215]}, "ip_csn_152": {"mean": [13.96413982], "std": [1.93966849]}},
# "kde_to_prototypes_kmeans10": {"hrnet": {"mean": [22.34404658, 23.32393717, 25.05344528, 26.28228829, 19.77518752, 28.91633101, 24.68429589, 26.00450343, 20.74952127, 28.0280111], "std": [12.54460885, 12.26281089, 12.94665937, 12.8510309, 10.77764458, 12.75964056, 12.71089526, 12.78862082, 11.45751004, 12.64915504]}, "ip_csn_152": {"mean": [22.53480481, 20.7729928, 23.51059946, 22.23555508, 20.5957774, 19.69265619, 30.73735828, 25.74919836, 18.19635059, 25.64240508], "std": [12.74190567, 12.14411597, 12.85587406, 12.26041677, 10.78404486, 9.14102503, 11.79962895, 12.90136629, 10.05282984, 12.52710312]}},
# "kde_to_prototypes_kmeans20": {"hrnet": {"mean": [31.69839842, 29.51855665, 25.13352641, 27.26374659, 30.25359399, 34.54778692, 27.57205635, 27.99430297, 31.84748829, 29.42226455, 28.60003402, 26.27126407, 26.76157359, 29.83490644, 25.77445773, 30.18783797, 22.53293527, 27.24613161, 31.10134186, 30.34930407], "std": [11.74770298, 12.81808885, 13.19437256, 13.0224404, 13.06814512, 9.8555354, 12.64231683, 12.98979078, 11.86388637, 12.55231065, 12.75768624, 12.85113407, 12.90071603, 11.9664967, 12.9926879, 11.187667, 11.98505335, 13.06676437, 12.32024275, 12.4558603]}, "ip_csn_152": {"mean": [27.82136884, 25.54362269, 25.37164949, 25.10819905, 30.51937167, 30.90559366, 32.35299407, 27.83862862, 24.71574132, 20.28692441, 27.3291217, 32.61718689, 25.53861938, 28.96719321, 23.60797242, 34.86281952, 23.0760265, 24.02476808, 28.41564282, 32.87464475], "std": [12.73015997, 13.05931946, 12.64430493, 12.90187176, 11.58583764, 11.91294632, 11.00213178, 10.14090567, 12.4943375, 10.31066217, 13.0164972, 9.79051657, 12.08657434, 12.50002143, 12.90749402, 10.05255596, 12.90158407, 12.43920307, 12.34283125, 11.90518241]}},
# "kde_to_prototypes_kmeans100": {"hrnet": {"mean": [11.51650465, 24.74514243, 27.51883169, 25.97178904, 11.31725194, 13.87194713, 14.62034483, 11.92172826, 9.20520639, 30.50808912, 12.29487818, 28.74730759, 13.00967303, 12.87377382, 10.36339639, 28.97818146, 13.06822447, 25.89808449, 11.53301842, 24.32070377, 31.38934371, 26.11882069, 11.43867242, 12.85366746, 11.01468504, 12.12410351, 11.00522818, 14.22570277, 11.31978803, 24.72001815, 11.49547369, 12.77695977, 12.04594129, 12.04245901, 11.76962055, 12.84280724, 28.74092166, 12.84942706, 12.24976226, 13.05081896, 12.36019271, 25.51715946, 24.25742462, 10.36439239, 12.98424855, 25.27499652, 25.44573651, 28.18075007, 12.99458985, 30.24841527, 14.46180985, 12.76151364, 11.42494888, 28.26574123, 12.99356359, 12.89439119, 12.56663157, 12.05120017, 12.16260737, 13.53108492, 11.42726582, 29.94052143, 11.93164773, 11.03575492, 10.79469548, 13.08070932, 13.03703147, 14.46314972, 25.12095769, 13.77110818, 27.48668507, 12.29402076, 13.86463529, 12.88956468, 11.76812248, 14.11122928, 11.32554886, 12.31140356, 11.89315698, 12.01736178, 11.37400478, 13.00082441, 10.75157389, 11.23768297, 11.80001406, 13.05685913, 12.14250171, 12.11370242, 33.02607832, 11.84779562, 13.1053964, 13.05621283, 11.12642011, 29.18021246, 11.99190531, 12.764033, 28.33108127, 29.15034937, 29.82593376, 27.30338024], "std": [0.49092909, 6.82615035, 10.70903685, 10.37115042, 0.43897617, 0.77953526, 0.76672508, 0.43873326, 0.35160674, 9.03321023, 0.58574533, 9.71979916, 0.72243651, 0.53143026, 0.47517272, 8.45334199, 0.53640073, 10.39240834, 0.46858744, 6.73869898, 8.22851825, 6.59953257, 0.49445379, 0.72482197, 0.39345436, 0.54085447, 0.35395006, 1.28073227, 0.39606489, 7.84796142, 0.40249157, 0.60439615, 0.50978739, 0.49712485, 0.48994422, 0.63536928, 7.36168791, 0.77890461, 0.71543686, 0.55127982, 0.54117303, 4.43357163, 6.39430675, 0.40813315, 0.56244739, 7.90249266, 11.02424609, 8.81427042, 0.55874052, 5.48580654, 0.728487, 0.67039014, 0.32618745, 8.56646793, 0.54587089, 0.54601918, 0.77019612, 0.51750958, 0.53762254, 0.86725738, 0.48919972, 9.60022378, 0.42634458, 0.43682883, 0.46320888, 0.71003576, 0.67485982, 1.17511784, 11.31784293, 0.58278495, 10.0975029, 0.57189848, 0.84571344, 0.83764659, 0.42757481, 0.8105792, 0.47508245, 0.55381513, 0.42106531, 0.39719168, 0.40376858, 0.62058073, 0.42670341, 0.38667883, 0.40932324, 0.68418474, 0.63332582, 0.66265245, 7.27640934, 0.6156686, 0.69243368, 0.58041577, 0.45765232, 9.97426774, 0.41296908, 0.4672443, 9.77406241, 9.7480854, 7.13034956, 9.08439411]}, "ip_csn_152": {"mean": [9.71196352, 23.49682686, 12.20497649, 27.30811566, 9.6768241, 12.71300952, 23.19116866, 10.27625701, 18.45187108, 10.39640529, 26.12820217, 10.62266453, 9.96216621, 11.62429935, 12.31618677, 11.71429545, 22.6193794, 9.36331088, 12.04280081, 11.50031833, 20.44984539, 12.77454967, 11.54437134, 12.32434809, 22.95827503, 12.48521474, 34.37430375, 10.52804711, 23.64631975, 22.41211752, 12.10819108, 32.55145605, 18.43707583, 10.13955925, 22.4802746, 7.49207547, 13.15195769, 9.60453505, 10.91161128, 14.72979442, 27.3910164, 11.08758654, 12.73135497, 10.91049171, 15.37516248, 22.66357352, 13.07787516, 9.35692617, 12.80331148, 23.29173204, 9.48304976, 24.94445156, 20.32623052, 11.21369236, 25.12899181, 10.0386579, 11.84749185, 29.21775295, 10.39098915, 15.4181837, 10.05664413, 9.42956467, 9.89781804, 11.59305828, 23.43559562, 12.29913503, 8.53839584, 13.53576889, 20.13605933, 22.40080207, 12.41672105, 9.02531008, 11.39821367, 10.39140086, 21.87520667, 13.00152503, 22.2816836, 10.36900506, 12.71919444, 8.18202956, 13.30966751, 12.94287041, 23.43780398, 21.99137234, 26.04542091, 13.23209106, 12.69062877, 13.5037309, 10.1159824, 13.7206379, 20.91834896, 14.60660537, 11.94814013, 13.87324268, 9.42039112, 7.94019339, 12.80619205, 10.38068606, 11.71681304, 13.63913737], "std": [0.44371355, 7.84626098, 0.53547688, 7.61292119, 0.4906708, 0.64290665, 7.72790794, 2.11283198, 3.15242979, 0.47599921, 8.47740115, 0.46972529, 0.60385977, 0.40539537, 0.74038112, 0.61651274, 10.44342268, 0.43760384, 0.59301809, 0.98446909, 4.63323347, 0.34794425, 0.53292785, 0.86930776, 3.97857218, 0.51692806, 5.4624556, 0.86530847, 6.69250877, 5.50833892, 0.49520848, 5.62079012, 4.69522188, 0.28579894, 7.18320748, 0.36967898, 0.88312358, 0.67693423, 0.54603837, 0.69325317, 7.0112788, 0.44255659, 0.52149815, 0.80064822, 0.98609139, 9.68867733, 0.70920289, 0.32790516, 0.52926554, 5.16090845, 0.58975543, 9.33730357, 3.99599893, 0.50381269, 7.4027068, 0.36220426, 0.61290422, 6.3607189, 0.58550753, 0.99622955, 0.64193776, 0.25618684, 0.63800844, 0.48879583, 4.28252955, 0.62576398, 0.35466235, 3.62003813, 4.11270336, 8.72230699, 0.38472287, 0.55993798, 0.7054085, 0.50172872, 6.52157419, 0.70327671, 6.2844722, 0.68237491, 0.71563476, 0.34690258, 0.86397421, 0.79091527, 4.87969614, 5.97961135, 10.82308237, 0.63577342, 0.93920458, 0.54790375, 0.49948656, 0.75131356, 8.27514337, 1.1219974, 0.71364729, 0.66729948, 0.49642449, 0.37810184, 0.87707742, 0.66650293, 0.56044579, 0.46618052]}},
},
"LaMem": {
# "kde": {"hrnet": {"mean": 13.80319794, "std": 1.02861296}, "ip_csn_152": {"mean": 19.65490083, "std": 0.7906878}},
# "cosine_mean": {"hrnet": {"mean": 0.0050153, "std": 0.31809763}, "ip_csn_152": {"mean": 0.02998678, "std": 0.31463383}},
# "cosine_threshold0.4": {"hrnet": {"mean": 0.11902919, "std": 0.01178971}, "ip_csn_152": {"mean": 0.13627782, "std": 0.0382218}},
# "cosine_threshold0.5": {"hrnet": {"mean": 0.07281225, "std": 0.01277754}, "ip_csn_152": {"mean": 0.08305019, "std": 0.0288385}},
# "cosine_threshold0.7": {"hrnet": {"mean": 0.01887391, "std": 0.01056589}, "ip_csn_152": {"mean": 0.01965894, "std": 0.0118553}},
# "fractional_mean": {"hrnet": {"mean": 69.89468558, "std": 18.0173414}, "ip_csn_152": {"mean": 61.35022618, "std": 38.17735851}},
},
"VideoMem": {
"dbscan": {"hrnet": {"mean": 376 * [0], "std": 376 * [1]}, "ip_csn_152": {"mean": 323 * [0], "std": 323 * [1]}},
},
}
# ASSERTIONS & TESTS =====================================================================
# directories
def check_dir_exists(dir_list):
for directory in dir_list:
if not os.path.isdir(directory):
print(f"Cannot find the {directory} directory. Please create it.")
sys.exit()
check_dir_exists([__C.DIR.ROOT, __C.DIR.MEMENTO_ROOT, __C.DIR.PICKLE])
# CSN & HRNet
__C.CONST.CSN_ARCH_LIST = ["ip_csn_152", "ir_csn_152"]
__C.CONST.HRNET_FRAMES_LIST = [1, 5, 9]
assert __C.TRAIN.CSN_ARCH in __C.CONST.CSN_ARCH_LIST
assert __C.TRAIN.HRNET_FRAMES in __C.CONST.HRNET_FRAMES_LIST
# training
__C.CONST.DATASET_LIST = ["Memento10k", "LaMem", "VideoMem"]
__C.CONST.RAW_FEATURES_LIST = ["hog", "brightness", "contrast", "meanOF", "blurriness", "size_orig"]
__C.CONST.LOSS_LIST = ["mse", "l1", "spearman", "mse_to_spearman", "mse_tails"]
__C.CONST.SIMILARITY_METHOD_LIST = ["kde", "cosine_mean", "dbscan", "cosine_threshold0.4", "cosine_threshold0.5", "cosine_threshold0.7", "fractional_mean", "euclidean_to_prototypes_classes", "fractional_to_prototypes_classes"]
__C.CONST.SIMILARITY_FEATURES_LIST = ["hrnet", "ip_csn_152"]
assert __C.TRAIN.DATASET in __C.CONST.DATASET_LIST
assert __C.TRAIN.LOSS in __C.CONST.LOSS_LIST
for raw_feature in __C.TRAIN.RAW_FEATURES : assert raw_feature in __C.CONST.RAW_FEATURES_LIST
for similarity_method in __C.TRAIN.SIMILARITY_METHODS : assert similarity_method in __C.CONST.SIMILARITY_METHOD_LIST
for similarity_features in __C.TRAIN.SIMILARITY_FEATURES: assert similarity_features in __C.CONST.SIMILARITY_FEATURES_LIST