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ualerr
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N-A-I

Object Detection
game
naruto
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  1. args.yaml +106 -0
  2. results.csv +31 -0
  3. val_batch0_labels.jpg +0 -0
  4. val_batch0_pred.jpg +0 -0
args.yaml ADDED
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+ task: detect
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+ mode: train
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+ model: yolov8n.pt
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+ data: among.yaml
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+ epochs: 30
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+ time: null
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+ patience: 100
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+ batch: 16
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+ imgsz: 640
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+ save: true
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+ save_period: -1
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+ cache: false
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+ device: null
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+ workers: 8
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+ project: null
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+ name: train2
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+ exist_ok: false
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+ pretrained: true
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+ optimizer: auto
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+ verbose: true
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+ seed: 0
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+ deterministic: true
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+ single_cls: false
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+ rect: false
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+ cos_lr: false
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+ close_mosaic: 10
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+ resume: false
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+ amp: true
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+ fraction: 1.0
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+ profile: false
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+ freeze: null
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+ multi_scale: false
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+ overlap_mask: true
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+ mask_ratio: 4
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+ dropout: 0.0
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+ val: true
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+ split: val
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+ save_json: false
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+ save_hybrid: false
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+ conf: null
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+ iou: 0.7
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+ max_det: 300
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+ half: false
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+ dnn: false
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+ plots: true
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+ source: null
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+ vid_stride: 1
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+ stream_buffer: false
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+ visualize: false
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+ augment: false
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+ agnostic_nms: false
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+ classes: null
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+ retina_masks: false
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+ embed: null
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+ show: false
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+ save_frames: false
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+ save_txt: false
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+ save_conf: false
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+ save_crop: false
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+ show_labels: true
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+ show_conf: true
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+ show_boxes: true
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+ line_width: null
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+ format: torchscript
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+ keras: false
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+ optimize: false
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+ int8: false
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+ dynamic: false
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+ simplify: false
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+ opset: null
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+ workspace: 4
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+ nms: false
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+ lr0: 0.01
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+ lrf: 0.01
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+ momentum: 0.937
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+ weight_decay: 0.0005
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+ warmup_epochs: 3.0
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+ warmup_momentum: 0.8
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+ warmup_bias_lr: 0.1
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+ box: 7.5
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+ cls: 0.5
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+ dfl: 1.5
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+ pose: 12.0
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+ kobj: 1.0
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+ label_smoothing: 0.0
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+ nbs: 64
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+ hsv_h: 0.015
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+ hsv_s: 0.7
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+ hsv_v: 0.4
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+ degrees: 0.0
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+ translate: 0.1
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+ scale: 0.5
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+ shear: 0.0
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+ perspective: 0.0
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+ flipud: 0.0
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+ fliplr: 0.5
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+ bgr: 0.0
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+ mosaic: 1.0
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+ mixup: 0.0
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+ copy_paste: 0.0
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+ auto_augment: randaugment
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+ erasing: 0.4
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+ crop_fraction: 1.0
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+ cfg: null
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+ tracker: botsort.yaml
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+ save_dir: runs\detect\train2
results.csv ADDED
@@ -0,0 +1,31 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ epoch, 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
2
+ 1, 2.054, 3.7544, 1.7151, 0.00636, 0.875, 0.21038, 0.12648, 1.6194, 3.3018, 1.3166, 3.334e-05, 3.334e-05, 3.334e-05
3
+ 2, 2.1249, 3.6698, 1.7244, 0.00625, 0.875, 0.35931, 0.20826, 1.6451, 3.297, 1.2921, 8.0599e-05, 8.0599e-05, 8.0599e-05
4
+ 3, 1.872, 3.4882, 1.5972, 0.006, 0.875, 0.42969, 0.22476, 1.5687, 3.322, 1.2437, 0.00012456, 0.00012456, 0.00012456
5
+ 4, 1.7067, 2.9983, 1.4485, 0.00525, 0.79167, 0.524, 0.28127, 1.5511, 3.2668, 1.2258, 0.00016522, 0.00016522, 0.00016522
6
+ 5, 1.8656, 2.7249, 1.58, 0.00524, 0.79167, 0.49297, 0.2898, 1.524, 3.0795, 1.2032, 0.00020257, 0.00020257, 0.00020257
7
+ 6, 2.0011, 2.7181, 1.6001, 0.00529, 0.79167, 0.46748, 0.29858, 1.4023, 3.0113, 1.1901, 0.00023663, 0.00023663, 0.00023663
8
+ 7, 1.7105, 2.3112, 1.403, 0.00576, 0.875, 0.54152, 0.33705, 1.3626, 3.0309, 1.1851, 0.00026739, 0.00026739, 0.00026739
9
+ 8, 1.7044, 2.3039, 1.3755, 0.00531, 0.79167, 0.52185, 0.31617, 1.3829, 3.0385, 1.1934, 0.00029484, 0.00029484, 0.00029484
10
+ 9, 1.6739, 2.3051, 1.4105, 0.00531, 0.79167, 0.51722, 0.29871, 1.3867, 3.0962, 1.2331, 0.000319, 0.000319, 0.000319
11
+ 10, 1.6635, 2.216, 1.4038, 0.0053, 0.79167, 0.47935, 0.28123, 1.4907, 3.0247, 1.2295, 0.00033985, 0.00033985, 0.00033985
12
+ 11, 1.5889, 2.1615, 1.3576, 0.00534, 0.79167, 0.44996, 0.24785, 1.7484, 3.127, 1.38, 0.0003574, 0.0003574, 0.0003574
13
+ 12, 1.5844, 2.0286, 1.3526, 0.36192, 0.52083, 0.42462, 0.23154, 1.7114, 3.179, 1.3937, 0.00037166, 0.00037166, 0.00037166
14
+ 13, 1.5923, 2.0845, 1.3091, 0.5, 0.15871, 0.36473, 0.20579, 1.6925, 3.3169, 1.4573, 0.00038261, 0.00038261, 0.00038261
15
+ 14, 1.4415, 1.7986, 1.2446, 0.27277, 0.08333, 0.32634, 0.17618, 1.6863, 3.3196, 1.4474, 0.00039026, 0.00039026, 0.00039026
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+ 15, 1.564, 1.8156, 1.2812, 0.49641, 0.33243, 0.40324, 0.22835, 1.5117, 3.2005, 1.3599, 0.00039461, 0.00039461, 0.00039461
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+ 16, 1.4233, 1.9507, 1.2661, 0.00572, 0.875, 0.53064, 0.3122, 1.3628, 3.1558, 1.3072, 0.00039566, 0.00039566, 0.00039566
18
+ 17, 1.4735, 1.7803, 1.235, 0.00528, 0.79167, 0.60204, 0.31981, 1.4786, 3.0603, 1.2889, 0.00039341, 0.00039341, 0.00039341
19
+ 18, 1.4902, 1.7898, 1.2422, 0.00593, 0.875, 0.57484, 0.27501, 1.5, 3.011, 1.2859, 0.00038786, 0.00038786, 0.00038786
20
+ 19, 1.4272, 1.8, 1.2252, 0.69471, 0.41931, 0.574, 0.24557, 1.4645, 3.0245, 1.2951, 0.00037901, 0.00037901, 0.00037901
21
+ 20, 1.3374, 1.5829, 1.1915, 0.79029, 0.30037, 0.59592, 0.2491, 1.5116, 2.9965, 1.3151, 0.00036686, 0.00036686, 0.00036686
22
+ 21, 1.3559, 2.041, 1.1766, 0.64414, 0.30124, 0.52617, 0.22255, 1.5581, 3.0895, 1.3736, 0.0003514, 0.0003514, 0.0003514
23
+ 22, 1.3301, 1.9897, 1.2086, 0.58695, 0.28221, 0.4516, 0.19332, 1.5764, 3.1777, 1.437, 0.00033265, 0.00033265, 0.00033265
24
+ 23, 1.3085, 1.834, 1.1726, 0.53355, 0.22917, 0.37036, 0.15906, 1.6169, 3.2092, 1.4749, 0.0003106, 0.0003106, 0.0003106
25
+ 24, 1.2488, 1.8444, 1.1444, 0.45902, 0.17041, 0.41598, 0.18856, 1.5867, 3.1755, 1.4572, 0.00028524, 0.00028524, 0.00028524
26
+ 25, 1.2511, 1.8768, 1.1516, 0.65939, 0.0625, 0.42405, 0.21294, 1.5323, 3.1027, 1.4047, 0.00025658, 0.00025658, 0.00025658
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+ 26, 1.333, 1.9397, 1.2695, 0.33327, 0.14616, 0.41743, 0.21078, 1.518, 3.0271, 1.3756, 0.00022463, 0.00022463, 0.00022463
28
+ 27, 1.2751, 1.7845, 1.1207, 0.63745, 0.34132, 0.46361, 0.27195, 1.4732, 2.8776, 1.3358, 0.00018937, 0.00018937, 0.00018937
29
+ 28, 1.197, 1.6667, 1.1359, 0.67511, 0.4127, 0.57092, 0.33509, 1.4707, 2.7683, 1.3245, 0.00015081, 0.00015081, 0.00015081
30
+ 29, 1.1963, 1.6237, 1.1825, 0.67511, 0.4127, 0.57092, 0.33509, 1.4707, 2.7683, 1.3245, 0.00010896, 0.00010896, 0.00010896
31
+ 30, 1.2833, 1.7501, 1.1851, 0.73028, 0.51357, 0.62534, 0.3861, 1.4612, 2.6296, 1.3052, 6.3796e-05, 6.3796e-05, 6.3796e-05
val_batch0_labels.jpg ADDED
val_batch0_pred.jpg ADDED