proj status

.gitignore

@@ -1,4 +1,6 @@
-/dataset/cats
-/dataset/cats.zip
+/dataset
 /output
-/yolov8n.pt
+/yolov8n.pt
+/runs/detect/*
+!/runs/detect/cat_detection
+!/runs/detect/val

cats_dataset.yaml

@@ -0,0 +1,6 @@
+path: E:/Facultate/Master/Anul 1/CV/Project/dataset # Root directory of your dataset
+train: images/train # Train image directory
+val: images/val # Validation image directory
+
+nc: 2 # Number of classes (2 cats in your case)
+names: ["Tom", "Garfield"] # Class names corresponding to cluster labels

dataset_download.py

@@ -0,0 +1,2 @@
+import tensorflow as tf
+import tensorflow_datasets as tfds

runs/detect/cat_detection/args.yaml

@@ -0,0 +1,106 @@
+task: detect
+mode: train
+model: yolov8n.pt
+data: cats_dataset.yaml
+epochs: 50
+time: null
+patience: 100
+batch: 16
+imgsz: 640
+save: true
+save_period: -1
+cache: false
+device: cuda:0
+workers: 4
+project: null
+name: cat_detection
+exist_ok: false
+pretrained: true
+optimizer: auto
+verbose: true
+seed: 0
+deterministic: true
+single_cls: false
+rect: false
+cos_lr: false
+close_mosaic: 10
+resume: false
+amp: true
+fraction: 1.0
+profile: false
+freeze: null
+multi_scale: false
+overlap_mask: true
+mask_ratio: 4
+dropout: 0.0
+val: true
+split: val
+save_json: false
+save_hybrid: false
+conf: null
+iou: 0.7
+max_det: 300
+half: false
+dnn: false
+plots: true
+source: null
+vid_stride: 1
+stream_buffer: false
+visualize: false
+augment: false
+agnostic_nms: false
+classes: null
+retina_masks: false
+embed: null
+show: false
+save_frames: false
+save_txt: false
+save_conf: false
+save_crop: false
+show_labels: true
+show_conf: true
+show_boxes: true
+line_width: null
+format: torchscript
+keras: false
+optimize: false
+int8: false
+dynamic: false
+simplify: true
+opset: null
+workspace: null
+nms: false
+lr0: 0.01
+lrf: 0.01
+momentum: 0.937
+weight_decay: 0.0005
+warmup_epochs: 3.0
+warmup_momentum: 0.8
+warmup_bias_lr: 0.1
+box: 7.5
+cls: 0.5
+dfl: 1.5
+pose: 12.0
+kobj: 1.0
+nbs: 64
+hsv_h: 0.015
+hsv_s: 0.7
+hsv_v: 0.4
+degrees: 0.0
+translate: 0.1
+scale: 0.5
+shear: 0.0
+perspective: 0.0
+flipud: 0.0
+fliplr: 0.5
+bgr: 0.0
+mosaic: 1.0
+mixup: 0.0
+copy_paste: 0.0
+copy_paste_mode: flip
+auto_augment: randaugment
+erasing: 0.4
+crop_fraction: 1.0
+cfg: null
+tracker: botsort.yaml
+save_dir: runs\detect\cat_detection

runs/detect/cat_detection/results.csv

@@ -0,0 +1,51 @@
+epoch,time,train/box_loss,train/cls_loss,train/dfl_loss,metrics/precision(B),metrics/recall(B),metrics/mAP50(B),metrics/mAP50-95(B),val/box_loss,val/cls_loss,val/dfl_loss,lr/pg0,lr/pg1,lr/pg2
+1,41.7603,2.54994,3.18243,2.51221,0.00543,0.60861,0.06066,0.01572,2.88929,3.47453,3.39482,0.00038341,0.00038341,0.00038341
+2,74.996,1.5829,2.20317,1.86498,0.35884,0.31878,0.215,0.07008,2.83816,2.78914,3.14487,0.000767977,0.000767977,0.000767977
+3,108.249,1.38431,1.86215,1.70799,0.62526,0.55407,0.58633,0.31948,1.5763,2.2232,1.98879,0.0011367,0.0011367,0.0011367
+4,138.046,1.24139,1.6498,1.58007,0.7061,0.69734,0.76866,0.51716,1.19157,1.55139,1.55139,0.00148958,0.00148958,0.00148958
+5,177.51,1.12757,1.55872,1.51474,0.8258,0.68903,0.83567,0.49045,1.28558,1.48416,1.67659,0.00153497,0.00153497,0.00153497
+6,213.163,1.05271,1.361,1.43795,0.81593,0.69091,0.824,0.55616,1.09991,1.34204,1.52969,0.00150197,0.00150197,0.00150197
+7,242.458,1.05077,1.38409,1.44457,0.79956,0.69286,0.79212,0.49044,1.22665,1.41692,1.60125,0.00146896,0.00146896,0.00146896
+8,270.991,1.01271,1.35862,1.41917,0.82757,0.7106,0.86499,0.62663,0.94366,1.22926,1.39691,0.00143595,0.00143595,0.00143595
+9,296.441,0.91474,1.24452,1.34834,0.85085,0.77679,0.87678,0.61598,1.03542,1.1298,1.49551,0.00140295,0.00140295,0.00140295
+10,323.314,0.86803,1.1113,1.30245,0.7953,0.84163,0.87429,0.64231,0.87863,1.09015,1.28995,0.00136994,0.00136994,0.00136994
+11,348.993,0.87972,1.05537,1.33899,0.87419,0.77573,0.85699,0.65747,0.85251,1.04036,1.27638,0.00133693,0.00133693,0.00133693
+12,374.694,0.92134,1.08425,1.34283,0.90352,0.80431,0.89774,0.69599,0.81858,0.8944,1.23589,0.00130393,0.00130393,0.00130393
+13,400.797,0.88226,1.04856,1.31014,0.88992,0.84843,0.91106,0.68552,0.82365,0.83574,1.26521,0.00127092,0.00127092,0.00127092
+14,427.968,0.81201,0.95926,1.29909,0.91449,0.85523,0.92765,0.71476,0.80232,0.81871,1.23408,0.00123791,0.00123791,0.00123791
+15,454.189,0.79519,0.96168,1.26909,0.84575,0.88301,0.90129,0.68346,0.79181,0.78937,1.24608,0.00120491,0.00120491,0.00120491
+16,479.954,0.86308,0.96065,1.31282,0.88634,0.82399,0.89899,0.70555,0.76829,0.81577,1.23144,0.0011719,0.0011719,0.0011719
+17,506.279,0.85551,0.92718,1.3078,0.87993,0.78278,0.89245,0.6706,0.84912,0.82797,1.25843,0.00113889,0.00113889,0.00113889
+18,534.252,0.84472,0.91935,1.28251,0.84172,0.80875,0.86914,0.64171,0.90884,0.83304,1.34577,0.00110589,0.00110589,0.00110589
+19,561.001,0.82708,0.87588,1.2796,0.7629,0.77727,0.85955,0.67344,0.83244,0.96993,1.28749,0.00107288,0.00107288,0.00107288
+20,598.281,0.77351,0.87018,1.23253,0.92505,0.87549,0.91505,0.73492,0.77467,0.66846,1.24465,0.00103987,0.00103987,0.00103987
+21,624.738,0.7427,0.83641,1.23337,0.89574,0.86978,0.91214,0.71788,0.77596,0.69304,1.2433,0.00100687,0.00100687,0.00100687
+22,653.387,0.75428,0.8537,1.23923,0.90535,0.75404,0.87979,0.71103,0.70279,0.82322,1.19686,0.000973861,0.000973861,0.000973861
+23,677.798,0.73519,0.79982,1.20099,0.93995,0.79148,0.88972,0.69598,0.74002,0.73455,1.21654,0.000940855,0.000940855,0.000940855
+24,703.367,0.71942,0.79011,1.20355,0.91963,0.79657,0.90314,0.70615,0.78578,0.6963,1.24998,0.000907848,0.000907848,0.000907848
+25,728.85,0.75508,0.79804,1.24131,0.9421,0.81162,0.91895,0.72437,0.74649,0.71008,1.22421,0.000874842,0.000874842,0.000874842
+26,755.27,0.68981,0.75245,1.17233,0.90671,0.86121,0.91712,0.73366,0.73208,0.63567,1.22266,0.000841835,0.000841835,0.000841835
+27,778.886,0.70801,0.74326,1.20027,0.95102,0.82554,0.90723,0.6996,0.79841,0.69897,1.22938,0.000808828,0.000808828,0.000808828
+28,804.012,0.69438,0.71202,1.17782,0.94963,0.86504,0.93251,0.75816,0.71698,0.65917,1.21462,0.000775822,0.000775822,0.000775822
+29,827.596,0.68358,0.72711,1.17863,0.94478,0.82232,0.92438,0.74928,0.71748,0.64451,1.18104,0.000742815,0.000742815,0.000742815
+30,850.945,0.69173,0.72918,1.17348,0.91018,0.87057,0.93745,0.76242,0.67573,0.61438,1.15435,0.000709809,0.000709809,0.000709809
+31,875.669,0.66821,0.66905,1.17224,0.95255,0.8251,0.93451,0.77284,0.63139,0.60749,1.11677,0.000676802,0.000676802,0.000676802
+32,901.456,0.65135,0.68664,1.16114,0.9364,0.79458,0.92021,0.74713,0.66189,0.64562,1.14592,0.000643795,0.000643795,0.000643795
+33,926.333,0.63677,0.64844,1.14138,0.92334,0.89741,0.94348,0.78891,0.65211,0.57955,1.13967,0.000610789,0.000610789,0.000610789
+34,949.914,0.66215,0.68526,1.16026,0.96318,0.85524,0.95244,0.78401,0.61719,0.57355,1.12666,0.000577782,0.000577782,0.000577782
+35,973.515,0.64566,0.65378,1.14951,0.97695,0.85901,0.95319,0.78117,0.65163,0.56723,1.15153,0.000544776,0.000544776,0.000544776
+36,997.299,0.60033,0.63096,1.12215,0.90017,0.881,0.9435,0.76913,0.65355,0.57331,1.15214,0.000511769,0.000511769,0.000511769
+37,1022.39,0.6187,0.61173,1.12676,0.95067,0.85356,0.94685,0.77863,0.64569,0.58735,1.14863,0.000478762,0.000478762,0.000478762
+38,1046.51,0.62408,0.64977,1.13398,0.9744,0.83322,0.93891,0.77845,0.63145,0.59304,1.14327,0.000445756,0.000445756,0.000445756
+39,1069.52,0.59965,0.62592,1.12855,0.9327,0.87231,0.92721,0.77809,0.63875,0.59236,1.14363,0.000412749,0.000412749,0.000412749
+40,1093.88,0.60368,0.61713,1.11117,0.96572,0.85427,0.93924,0.78961,0.6273,0.55367,1.11419,0.000379743,0.000379743,0.000379743
+41,1148.05,0.50324,0.62738,1.07458,0.97744,0.80879,0.90839,0.73295,0.72751,0.73311,1.20287,0.000346736,0.000346736,0.000346736
+42,1172.58,0.46432,0.5305,1.0149,0.94972,0.86703,0.94626,0.77272,0.62908,0.57454,1.13127,0.000313729,0.000313729,0.000313729
+43,1196.92,0.45396,0.5091,1.0216,0.95514,0.88087,0.94434,0.79231,0.61548,0.5314,1.11574,0.000280723,0.000280723,0.000280723
+44,1219.38,0.44166,0.46775,0.97879,0.91471,0.89346,0.9397,0.79357,0.60267,0.53682,1.10288,0.000247716,0.000247716,0.000247716
+45,1243.16,0.42041,0.46066,0.9959,0.91382,0.89782,0.94741,0.79596,0.60978,0.52438,1.13124,0.00021471,0.00021471,0.00021471
+46,1265.52,0.40657,0.4481,0.96549,0.93209,0.87258,0.95065,0.80079,0.59726,0.53471,1.11823,0.000181703,0.000181703,0.000181703
+47,1294.23,0.40389,0.43643,0.96607,0.94116,0.88465,0.94829,0.79693,0.585,0.54994,1.09351,0.000148696,0.000148696,0.000148696
+48,1324.01,0.38368,0.40904,0.96912,0.93682,0.89071,0.94641,0.79852,0.5988,0.53865,1.10804,0.00011569,0.00011569,0.00011569
+49,1350.25,0.40215,0.45338,0.99384,0.93855,0.89749,0.94677,0.80032,0.60052,0.53816,1.11297,8.26832e-05,8.26832e-05,8.26832e-05
+50,1373.09,0.40307,0.42498,0.98954,0.94335,0.89709,0.95056,0.80202,0.59766,0.53763,1.11256,4.96766e-05,4.96766e-05,4.96766e-05