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yolov10-models

Object Detection
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KorRyu bknk524 commited on
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Co-authored-by: KonishiYuto <[email protected]>

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  1. training/yolov10b-sugarcane14 Best/F1_curve.png +0 -0
  2. training/yolov10b-sugarcane14 Best/PR_curve.png +0 -0
  3. training/yolov10b-sugarcane14 Best/P_curve.png +0 -0
  4. training/yolov10b-sugarcane14 Best/R_curve.png +0 -0
  5. training/yolov10b-sugarcane14 Best/args.yaml +107 -0
  6. training/yolov10b-sugarcane14 Best/confusion_matrix.png +0 -0
  7. training/yolov10b-sugarcane14 Best/confusion_matrix_normalized.png +0 -0
  8. training/yolov10b-sugarcane14 Best/labels.jpg +0 -0
  9. training/yolov10b-sugarcane14 Best/labels_correlogram.jpg +0 -0
  10. training/yolov10b-sugarcane14 Best/results.csv +151 -0
  11. training/yolov10b-sugarcane14 Best/results.png +0 -0
  12. training/yolov10b-sugarcane14 Best/train_batch0.jpg +0 -0
  13. training/yolov10b-sugarcane14 Best/train_batch1.jpg +0 -0
  14. training/yolov10b-sugarcane14 Best/train_batch2.jpg +0 -0
  15. training/yolov10b-sugarcane14 Best/val_batch0_labels.jpg +0 -0
  16. training/yolov10b-sugarcane14 Best/val_batch0_pred.jpg +0 -0
  17. training/yolov10b-sugarcane14 Best/val_batch1_labels.jpg +0 -0
  18. training/yolov10b-sugarcane14 Best/val_batch1_pred.jpg +0 -0
  19. training/yolov10b-sugarcane14 Best/val_batch2_labels.jpg +0 -0
  20. training/yolov10b-sugarcane14 Best/val_batch2_pred.jpg +0 -0
  21. training/yolov10b-sugarcane14 Best/weights/best.pt +3 -0
  22. training/yolov10b-sugarcane14 Best/weights/last.pt +3 -0
  23. training/yolov10b-sugarcane14 Best/{86606882-0549-488D-9AF7-EEDCBD0EA6AB}.png +0 -0
training/yolov10b-sugarcane14 Best/F1_curve.png ADDED
training/yolov10b-sugarcane14 Best/PR_curve.png ADDED
training/yolov10b-sugarcane14 Best/P_curve.png ADDED
training/yolov10b-sugarcane14 Best/R_curve.png ADDED
training/yolov10b-sugarcane14 Best/args.yaml ADDED
@@ -0,0 +1,107 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ task: detect
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+ mode: train
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+ model: weights/yolov10b.pt
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+ data: data/sugarcane.yaml
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+ epochs: 300
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+ time: null
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+ patience: 100
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+ batch: 8
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+ imgsz: 640
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+ save: true
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+ save_period: -1
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+ val_period: 1
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+ cache: false
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+ device: 0
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+ workers: 8
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+ project: null
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+ name: yolov10b-sugarcane14
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+ exist_ok: false
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+ pretrained: true
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+ optimizer: SGD
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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: None
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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: 0.25
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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: 0.001
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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: 10.0
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+ cls: 0.7
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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: 0.01
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+ hsv_s: 0.5
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+ hsv_v: 0.3
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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: 0.8
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+ mixup: 0.1
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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: e:\yolov10\runs\detect\yolov10b-sugarcane14
training/yolov10b-sugarcane14 Best/confusion_matrix.png ADDED
training/yolov10b-sugarcane14 Best/confusion_matrix_normalized.png ADDED
training/yolov10b-sugarcane14 Best/labels.jpg ADDED
training/yolov10b-sugarcane14 Best/labels_correlogram.jpg ADDED
training/yolov10b-sugarcane14 Best/results.csv ADDED
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+ epoch, train/box_om, train/cls_om, train/dfl_om, train/box_oo, train/cls_oo, train/dfl_oo, metrics/precision(B), metrics/recall(B), metrics/mAP50(B), metrics/mAP50-95(B), val/box_om, val/cls_om, val/dfl_om, val/box_oo, val/cls_oo, val/dfl_oo, lr/pg0, lr/pg1, lr/pg2
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+ 1, 4.6423, 5.9525, 2.428, 4.3469, 7.0309, 2.0227, 0.00102, 0.0062, 0.00053, 0.00016, 4.369, 4.9847, 2.3689, 3.9788, 5.8917, 1.9884, 0.07327, 0.00027, 0.00027
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+ 2, 4.3339, 4.8343, 2.2033, 4.1501, 5.9502, 1.862, 0.04426, 0.04752, 0.01981, 0.00599, 3.8235, 4.7246, 1.9786, 3.7179, 5.0383, 1.7137, 0.045548, 0.00054819, 0.00054819
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+ 3, 3.834, 3.4978, 1.9601, 3.7928, 4.9277, 1.6916, 0.06159, 0.09091, 0.04363, 0.01268, 3.5346, 3.11, 1.7854, 3.3559, 4.4793, 1.5169, 0.017825, 0.00082452, 0.00082452
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+ 4, 3.613, 2.9503, 1.7605, 3.5291, 4.2045, 1.5379, 0.13796, 0.13946, 0.09622, 0.03102, 3.483, 2.7211, 1.6134, 3.285, 3.9224, 1.4404, 0.0009901, 0.0009901, 0.0009901
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+ 5, 3.4851, 2.8559, 1.645, 3.4262, 3.9344, 1.4901, 0.15031, 0.16529, 0.12472, 0.04155, 3.3984, 2.6919, 1.5061, 3.26, 3.5601, 1.4118, 0.0009901, 0.0009901, 0.0009901
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+ 6, 3.4457, 2.8183, 1.6056, 3.423, 3.6315, 1.4764, 0.16497, 0.16735, 0.13575, 0.04504, 3.3338, 2.8071, 1.5288, 3.2025, 3.4085, 1.3949, 0.0009868, 0.0009868, 0.0009868
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+ 7, 3.3853, 2.68, 1.5508, 3.3462, 3.4697, 1.4084, 0.1624, 0.15909, 0.13989, 0.0473, 3.2268, 2.6591, 1.5011, 3.1252, 3.4605, 1.3788, 0.0009835, 0.0009835, 0.0009835
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+ 8, 3.2379, 2.5881, 1.5172, 3.26, 3.3401, 1.4006, 0.66992, 0.17735, 0.1549, 0.05238, 3.1812, 2.7712, 1.4679, 3.1115, 3.5836, 1.3597, 0.0009802, 0.0009802, 0.0009802
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+ 9, 3.2614, 2.5523, 1.4745, 3.3074, 3.2809, 1.3581, 0.67249, 0.1906, 0.16852, 0.05568, 3.165, 2.4685, 1.4311, 3.1216, 3.5365, 1.3477, 0.0009769, 0.0009769, 0.0009769
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+ 10, 3.1482, 2.4831, 1.454, 3.219, 3.1584, 1.3537, 0.65847, 0.22211, 0.19417, 0.06342, 3.1366, 2.6432, 1.4437, 3.1087, 3.3708, 1.3445, 0.0009736, 0.0009736, 0.0009736
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+ 11, 3.1646, 2.4345, 1.4418, 3.231, 3.0918, 1.3438, 0.30103, 0.29153, 0.23587, 0.08, 3.13, 2.3654, 1.3931, 3.0752, 3.0084, 1.3121, 0.0009703, 0.0009703, 0.0009703
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+ 12, 3.1393, 2.3787, 1.4094, 3.2295, 3.0253, 1.3174, 0.27676, 0.3303, 0.24549, 0.08397, 3.1036, 2.4574, 1.3991, 3.0724, 3.0627, 1.3154, 0.000967, 0.000967, 0.000967
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+ 13, 3.1501, 2.4489, 1.4363, 3.2207, 3.1021, 1.3422, 0.3544, 0.3334, 0.27613, 0.09549, 3.0767, 2.3754, 1.4035, 3.0717, 2.9569, 1.3164, 0.0009637, 0.0009637, 0.0009637
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+ 14, 3.0747, 2.3307, 1.414, 3.1398, 2.916, 1.3173, 0.36287, 0.31739, 0.28871, 0.1009, 3.0696, 2.3548, 1.3965, 3.0183, 2.8816, 1.3005, 0.0009604, 0.0009604, 0.0009604
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+ 15, 3.1246, 2.3357, 1.4573, 3.1242, 2.9518, 1.345, 0.36676, 0.37425, 0.3146, 0.10835, 3.0538, 2.3401, 1.3915, 3.0027, 2.9402, 1.2957, 0.0009571, 0.0009571, 0.0009571
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+ 16, 3.0084, 2.2324, 1.3991, 3.101, 2.8112, 1.3071, 0.40398, 0.34146, 0.32063, 0.11009, 3.073, 2.2742, 1.3828, 3.0401, 2.8485, 1.2989, 0.0009538, 0.0009538, 0.0009538
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+ 17, 3.0939, 2.2316, 1.4072, 3.1722, 2.8113, 1.3171, 0.45094, 0.34236, 0.33465, 0.11544, 3.0788, 2.2592, 1.3827, 3.0319, 2.9404, 1.3005, 0.0009505, 0.0009505, 0.0009505
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+ 18, 3.0285, 2.2063, 1.4075, 3.1213, 2.7802, 1.3182, 0.47678, 0.37189, 0.36621, 0.1282, 3.0483, 2.1792, 1.3857, 3.0075, 2.7487, 1.298, 0.0009472, 0.0009472, 0.0009472
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+ 19, 3.028, 2.2383, 1.3909, 3.1335, 2.8263, 1.3105, 0.49175, 0.40229, 0.3851, 0.13907, 3.0581, 2.1744, 1.379, 2.9916, 2.7045, 1.2928, 0.0009439, 0.0009439, 0.0009439
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+ 20, 2.9808, 2.1382, 1.3855, 3.0793, 2.696, 1.302, 0.50811, 0.41323, 0.40909, 0.146, 3.0415, 2.1835, 1.3836, 2.9704, 2.7607, 1.2867, 0.0009406, 0.0009406, 0.0009406
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+ 21, 2.9474, 2.1118, 1.3817, 3.0464, 2.6498, 1.302, 0.49345, 0.39167, 0.39132, 0.14027, 3.0671, 2.1821, 1.3808, 2.991, 2.7336, 1.2868, 0.0009373, 0.0009373, 0.0009373
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+ 22, 2.9633, 2.0941, 1.3728, 3.0797, 2.6418, 1.3028, 0.45951, 0.42821, 0.4032, 0.14692, 3.0523, 2.1527, 1.3934, 3.0116, 2.6738, 1.3123, 0.000934, 0.000934, 0.000934
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+ 23, 2.9907, 2.0817, 1.3521, 3.1321, 2.5923, 1.2773, 0.47928, 0.41834, 0.39766, 0.14212, 3.0585, 2.2268, 1.3861, 3.0336, 2.7391, 1.301, 0.0009307, 0.0009307, 0.0009307
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+ 24, 2.897, 2.0594, 1.3454, 3.0027, 2.5741, 1.2787, 0.48832, 0.42473, 0.40033, 0.14755, 3.0245, 2.189, 1.386, 3.0024, 2.6664, 1.2994, 0.0009274, 0.0009274, 0.0009274
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+ 25, 2.9387, 2.0541, 1.3608, 3.0498, 2.5653, 1.2803, 0.5088, 0.41977, 0.40236, 0.14799, 3.0726, 2.218, 1.3895, 3.0244, 2.6866, 1.2926, 0.0009241, 0.0009241, 0.0009241
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+ 26, 2.8967, 1.9994, 1.3467, 3.0423, 2.5341, 1.2795, 0.53125, 0.39953, 0.40714, 0.15152, 3.0845, 2.1495, 1.3912, 3.0384, 2.623, 1.301, 0.0009208, 0.0009208, 0.0009208
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+ 27, 2.8695, 1.9809, 1.3417, 2.999, 2.4931, 1.2772, 0.48973, 0.44214, 0.42095, 0.15413, 3.0758, 2.1827, 1.3775, 3.0312, 2.6221, 1.2944, 0.0009175, 0.0009175, 0.0009175
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+ 28, 2.8752, 1.978, 1.3365, 3.0369, 2.4587, 1.2688, 0.48824, 0.39329, 0.40534, 0.14272, 3.0668, 2.225, 1.3794, 3.0379, 2.6977, 1.2929, 0.0009142, 0.0009142, 0.0009142
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+ 29, 2.8897, 1.9813, 1.3463, 3.05, 2.51, 1.2795, 0.56944, 0.40238, 0.4248, 0.15278, 3.0638, 2.1626, 1.3753, 3.015, 2.6354, 1.2839, 0.0009109, 0.0009109, 0.0009109
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+ 30, 2.8446, 1.9262, 1.3393, 2.992, 2.4178, 1.2804, 0.5438, 0.42511, 0.43833, 0.15791, 3.0605, 2.1017, 1.4066, 3.0244, 2.5735, 1.3161, 0.0009076, 0.0009076, 0.0009076
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+ 31, 2.8643, 1.9117, 1.3328, 3.0481, 2.4089, 1.2716, 0.52791, 0.42322, 0.42421, 0.15152, 3.1013, 2.1234, 1.4025, 3.0863, 2.6299, 1.3184, 0.0009043, 0.0009043, 0.0009043
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+ 32, 2.827, 1.913, 1.3322, 2.9722, 2.4352, 1.2719, 0.55989, 0.40423, 0.42666, 0.14953, 3.1221, 2.1802, 1.3962, 3.1113, 2.6943, 1.3147, 0.000901, 0.000901, 0.000901
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+ 33, 2.7903, 1.8606, 1.3205, 2.9486, 2.3624, 1.2642, 0.54179, 0.45724, 0.43878, 0.15678, 3.0951, 2.1249, 1.4103, 3.0908, 2.6054, 1.3265, 0.0008977, 0.0008977, 0.0008977
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+ 34, 2.7659, 1.866, 1.3242, 2.9004, 2.3507, 1.2624, 0.51903, 0.45743, 0.43004, 0.15414, 3.1061, 2.1344, 1.4204, 3.0948, 2.5988, 1.3333, 0.0008944, 0.0008944, 0.0008944
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+ 35, 2.7957, 1.8665, 1.3281, 2.9371, 2.3555, 1.268, 0.52305, 0.41064, 0.41452, 0.14755, 3.1185, 2.0925, 1.4128, 3.1223, 2.5812, 1.3282, 0.0008911, 0.0008911, 0.0008911
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+ 36, 2.7366, 1.7929, 1.292, 2.9127, 2.2715, 1.2445, 0.50389, 0.43136, 0.40559, 0.13741, 3.1623, 2.1921, 1.4074, 3.1707, 2.7129, 1.3381, 0.0008878, 0.0008878, 0.0008878
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+ 37, 2.7278, 1.8131, 1.3172, 2.8776, 2.2843, 1.2666, 0.53185, 0.41859, 0.40923, 0.14572, 3.1744, 2.1208, 1.4392, 3.1186, 2.5962, 1.3427, 0.0008845, 0.0008845, 0.0008845
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+ 38, 2.7153, 1.7334, 1.2952, 2.9166, 2.2048, 1.2564, 0.52286, 0.45262, 0.41357, 0.14665, 3.1885, 2.1217, 1.4349, 3.1465, 2.5637, 1.3408, 0.0008812, 0.0008812, 0.0008812
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+ 39, 2.7336, 1.7378, 1.2915, 2.9606, 2.2274, 1.2492, 0.5202, 0.46119, 0.41766, 0.14782, 3.209, 2.1347, 1.4313, 3.1591, 2.6037, 1.3402, 0.0008779, 0.0008779, 0.0008779
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+ 40, 2.7448, 1.7505, 1.2906, 2.9463, 2.249, 1.2554, 0.51962, 0.45086, 0.42991, 0.14984, 3.2224, 2.1225, 1.457, 3.1715, 2.5229, 1.3601, 0.0008746, 0.0008746, 0.0008746
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+ 41, 2.6945, 1.6925, 1.2643, 2.9203, 2.1211, 1.2332, 0.5067, 0.4689, 0.42267, 0.1487, 3.2537, 2.0713, 1.47, 3.1904, 2.5154, 1.3701, 0.0008713, 0.0008713, 0.0008713
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+ 42, 2.6504, 1.6781, 1.2818, 2.8559, 2.1368, 1.2503, 0.50504, 0.46373, 0.4284, 0.14623, 3.239, 2.1069, 1.4631, 3.1976, 2.5332, 1.3685, 0.000868, 0.000868, 0.000868
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+ 43, 2.7773, 1.741, 1.2764, 2.9915, 2.2431, 1.2375, 0.50232, 0.47206, 0.43156, 0.14296, 3.2774, 2.0187, 1.5051, 3.2098, 2.5272, 1.3851, 0.0008647, 0.0008647, 0.0008647
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+ 44, 2.6439, 1.6272, 1.2768, 2.8721, 2.0461, 1.2435, 0.53091, 0.47246, 0.4484, 0.15266, 3.2609, 2.061, 1.501, 3.2148, 2.4922, 1.387, 0.0008614, 0.0008614, 0.0008614
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+ 45, 2.6533, 1.6162, 1.2495, 2.9046, 2.0623, 1.2188, 0.54301, 0.47225, 0.4396, 0.14959, 3.2697, 2.0679, 1.5039, 3.1944, 2.55, 1.3906, 0.0008581, 0.0008581, 0.0008581
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+ 46, 2.6558, 1.639, 1.2911, 2.8719, 2.0896, 1.256, 0.56716, 0.47027, 0.46164, 0.15585, 3.2363, 2.0546, 1.4861, 3.1683, 2.545, 1.3799, 0.0008548, 0.0008548, 0.0008548
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+ 47, 2.577, 1.5814, 1.2681, 2.7807, 1.9705, 1.2381, 0.54537, 0.44617, 0.4466, 0.1495, 3.2969, 2.1674, 1.4818, 3.2681, 2.6241, 1.3975, 0.0008515, 0.0008515, 0.0008515
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+ 48, 2.5931, 1.5852, 1.2454, 2.8388, 2.0061, 1.2204, 0.59913, 0.46215, 0.45837, 0.15483, 3.2717, 2.0199, 1.4855, 3.2428, 2.4709, 1.3869, 0.0008482, 0.0008482, 0.0008482
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+ 51, 2.5673, 1.5624, 1.2526, 2.8053, 2.0044, 1.2274, 0.54448, 0.49253, 0.45668, 0.15686, 3.3064, 2.1057, 1.507, 3.2878, 2.4837, 1.4108, 0.0008383, 0.0008383, 0.0008383
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+ 52, 2.5574, 1.5267, 1.2425, 2.8351, 1.9394, 1.2195, 0.57923, 0.46717, 0.44937, 0.15105, 3.2883, 2.0178, 1.5228, 3.2765, 2.4594, 1.4144, 0.000835, 0.000835, 0.000835
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55
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56
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57
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58
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59
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60
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61
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62
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63
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64
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65
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66
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67
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68
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69
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70
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71
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72
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73
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74
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75
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76
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77
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78
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79
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80
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81
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82
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83
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84
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85
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86
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87
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88
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89
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90
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91
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92
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93
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94
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95
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96
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97
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98
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99
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100
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101
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102
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103
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104
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105
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106
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107
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108
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109
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110
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111
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112
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113
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114
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115
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116
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117
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118
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119
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120
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121
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122
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123
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124
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125
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126
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127
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128
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129
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130
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131
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132
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133
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134
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