feat: 초기 프로젝트 구조 추가

This commit is contained in:
Kim Min Jae
2026-06-10 16:18:41 +09:00
parent 5d985560c5
commit a48a4b5fe5
100 changed files with 10530 additions and 0 deletions

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names:
- 스크래치
- 이물
- 흑점
- 변형
nc: 4
path: e:\ANT\utils\ai\dataset
train: images/train
val: images/val

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0 0.227074 0.195219 0.401747 0.215139
1 0.853712 0.252988 0.257642 0.330677

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0 0.318598 0.542781 0.472561 0.754011

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0 0.233974 0.409524 0.339744 0.590476

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task: detect
mode: train
model: yolov8n.pt
data: e:\ANT\utils\ai\dataset\data.yaml
epochs: 5
time: null
patience: 100
batch: 16
imgsz: 640
save: true
save_period: -1
cache: false
device: null
workers: 0
project: e:\ANT\utils\ai\runs
name: train
exist_ok: true
pretrained: true
optimizer: auto
verbose: true
seed: 0
deterministic: true
single_cls: false
rect: false
cos_lr: false
close_mosaic: 10
resume: false
amp: false
fraction: 1.0
profile: false
freeze: null
multi_scale: 0.0
compile: false
overlap_mask: true
mask_ratio: 4
dropout: 0.0
val: true
split: val
save_json: false
conf: null
iou: 0.7
max_det: 300
half: false
dnn: false
plots: false
end2end: null
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
cls_pw: 0.0
dfl: 1.5
pose: 12.0
kobj: 1.0
rle: 1.0
angle: 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
cutmix: 0.0
copy_paste: 0.0
copy_paste_mode: flip
auto_augment: randaugment
erasing: 0.4
cfg: null
tracker: botsort.yaml
save_dir: E:\ANT\utils\ai\runs\train

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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
1,0.455317,2.31474,4.08107,2.28289,0.02041,1,0.4975,0.04975,3.2799,4.23304,3.16176,0,0,0
2,0.862726,2.30536,4.11057,2.05367,0.02041,1,0.4975,0.04975,3.26087,4.28545,3.03613,1.0025e-05,1.0025e-05,1.0025e-05
3,1.1759,2.77566,3.95724,3.15328,0.02083,1,0.4975,0.04975,3.25368,4.2721,3.07091,1.51e-05,1.51e-05,1.51e-05
4,1.48949,1.89878,3.81945,2.43286,0.02041,1,0.4975,0.04975,3.22409,4.21402,3.13953,1.5225e-05,1.5225e-05,1.5225e-05
5,1.80265,2.28623,4.60095,2.64542,0.02,1,0.4975,0.04975,3.17688,4.12774,3.17531,1.04e-05,1.04e-05,1.04e-05
1 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
2 1 0.455317 2.31474 4.08107 2.28289 0.02041 1 0.4975 0.04975 3.2799 4.23304 3.16176 0 0 0
3 2 0.862726 2.30536 4.11057 2.05367 0.02041 1 0.4975 0.04975 3.26087 4.28545 3.03613 1.0025e-05 1.0025e-05 1.0025e-05
4 3 1.1759 2.77566 3.95724 3.15328 0.02083 1 0.4975 0.04975 3.25368 4.2721 3.07091 1.51e-05 1.51e-05 1.51e-05
5 4 1.48949 1.89878 3.81945 2.43286 0.02041 1 0.4975 0.04975 3.22409 4.21402 3.13953 1.5225e-05 1.5225e-05 1.5225e-05
6 5 1.80265 2.28623 4.60095 2.64542 0.02 1 0.4975 0.04975 3.17688 4.12774 3.17531 1.04e-05 1.04e-05 1.04e-05

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