update1
hy.kim
1 year ago
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9d74d9e51a
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# 지능화 캡스톤 프로젝트 #2 - YOLOv5 안전모 검출
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-----
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[PINBlog Gitea Repository](https://gitea.pinblog.codes/CBNU/19_YOLOv5)
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* 제출했던 프로젝트 코드가 날라가서 일부만 존재함;;
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-----
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### YOLOv5 GitHub
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[YOLOv5](https://github.com/ultralytics/yolov5)
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# 프로젝트 목표
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* YOLOv5 모델을 학습하여 영상의 안전모와 마스크를 검출
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# 구현 방법
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* 일반적인 1개의 모델로 여러 클래스를 학습하지 않고, Detect Model로 머리를 검출하여 ROI 취득 후,
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해당 ROI를 Crop하여 Classification Model로 안전모, 마스크, 미착용 등을 분류한다.
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# 데이터셋
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* YouTube, Google, AIHub, Kaggle에서 안전모 관련 데이터셋 확보
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* Roboflow에서 데이터셋 라벨링 진행
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[Roboflow](https://roboflow.com/)
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# 클래스
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### Detect Model
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* 1개의 뚝배기 클래스
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* 0: dduk
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### Classification Model
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* 5개의 클래스
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* 0: head
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* 1: helmet
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* 2: face
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* 3: mask
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* 4: helmet & mask
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# 프로젝트 코드 (Validation)
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<details>
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<summary></summary>
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<div markdown="1">
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``` planetext
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```
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</div>
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</details>
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### 참고[¶]()
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- 지능화캡스톤 과목, 김현용 교수
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|
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Before Width: | Height: | Size: 88 KiB After Width: | Height: | Size: 88 KiB |
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Before Width: | Height: | Size: 91 KiB After Width: | Height: | Size: 91 KiB |
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Before Width: | Height: | Size: 80 KiB After Width: | Height: | Size: 80 KiB |
@ -1,28 +1,28 @@
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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: 0.05
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cls: 0.5
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cls_pw: 1.0
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obj: 1.0
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obj_pw: 1.0
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iou_t: 0.2
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anchor_t: 4.0
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fl_gamma: 0.0
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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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mosaic: 1.0
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mixup: 0.0
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copy_paste: 0.0
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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: 0.05
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cls: 0.5
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cls_pw: 1.0
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obj: 1.0
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obj_pw: 1.0
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iou_t: 0.2
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anchor_t: 4.0
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fl_gamma: 0.0
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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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mosaic: 1.0
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mixup: 0.0
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copy_paste: 0.0
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Before Width: | Height: | Size: 125 KiB After Width: | Height: | Size: 125 KiB |
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Before Width: | Height: | Size: 264 KiB After Width: | Height: | Size: 264 KiB |
@ -1,68 +1,68 @@
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weights: yolov5s.pt
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cfg: ''
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data: datasets/DDukbaegi2/data.yaml
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hyp:
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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: 0.05
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cls: 0.5
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cls_pw: 1.0
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obj: 1.0
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obj_pw: 1.0
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iou_t: 0.2
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anchor_t: 4.0
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fl_gamma: 0.0
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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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mosaic: 1.0
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mixup: 0.0
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copy_paste: 0.0
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epochs: 80
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batch_size: 60
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imgsz: 640
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rect: false
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resume: false
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nosave: false
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noval: false
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noautoanchor: false
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noplots: false
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evolve: null
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bucket: ''
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cache: null
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image_weights: false
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device: ''
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multi_scale: false
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single_cls: false
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optimizer: SGD
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sync_bn: false
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workers: 8
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project: runs\train
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name: dduk_64_
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exist_ok: false
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quad: false
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cos_lr: false
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label_smoothing: 0.0
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patience: 100
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freeze:
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- 0
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save_period: -1
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seed: 0
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local_rank: -1
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entity: null
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upload_dataset: false
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bbox_interval: -1
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artifact_alias: latest
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save_dir: runs\train\dduk_64_
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weights: yolov5s.pt
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cfg: ''
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data: datasets/DDukbaegi2/data.yaml
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hyp:
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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: 0.05
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cls: 0.5
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cls_pw: 1.0
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obj: 1.0
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obj_pw: 1.0
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iou_t: 0.2
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anchor_t: 4.0
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fl_gamma: 0.0
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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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mosaic: 1.0
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mixup: 0.0
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copy_paste: 0.0
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epochs: 80
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batch_size: 60
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imgsz: 640
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rect: false
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resume: false
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nosave: false
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noval: false
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noautoanchor: false
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noplots: false
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evolve: null
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bucket: ''
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cache: null
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image_weights: false
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device: ''
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multi_scale: false
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single_cls: false
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optimizer: SGD
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sync_bn: false
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workers: 8
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project: runs\train
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name: dduk_64_
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exist_ok: false
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quad: false
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cos_lr: false
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label_smoothing: 0.0
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patience: 100
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freeze:
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- 0
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save_period: -1
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seed: 0
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local_rank: -1
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entity: null
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upload_dataset: false
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bbox_interval: -1
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artifact_alias: latest
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save_dir: runs\train\dduk_64_
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@ -1,81 +1,81 @@
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epoch, train/box_loss, train/obj_loss, train/cls_loss, metrics/precision, metrics/recall, metrics/mAP_0.5,metrics/mAP_0.5:0.95, val/box_loss, val/obj_loss, val/cls_loss, x/lr0, x/lr1, x/lr2
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0, 0.068575, 0.039993, 0, 0.70102, 0.58071, 0.60196, 0.2519, 0.048167, 0.021189, 0, 0.070096, 0.0033226, 0.0033226
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1, 0.048822, 0.031577, 0, 0.83348, 0.67616, 0.75758, 0.3812, 0.038854, 0.019978, 0, 0.040014, 0.0065736, 0.0065736
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2, 0.041754, 0.02902, 0, 0.77593, 0.62288, 0.69313, 0.32412, 0.041876, 0.02355, 0, 0.0098492, 0.009742, 0.009742
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3, 0.037026, 0.02777, 0, 0.83418, 0.71955, 0.80302, 0.42477, 0.035953, 0.01995, 0, 0.0096288, 0.0096288, 0.0096288
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4, 0.034654, 0.02614, 0, 0.85591, 0.7205, 0.81403, 0.45105, 0.034349, 0.019149, 0, 0.0096288, 0.0096288, 0.0096288
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5, 0.033087, 0.02533, 0, 0.84811, 0.7377, 0.81351, 0.45187, 0.03501, 0.019692, 0, 0.009505, 0.009505, 0.009505
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6, 0.031878, 0.024502, 0, 0.84654, 0.76661, 0.83513, 0.46097, 0.035043, 0.018774, 0, 0.0093813, 0.0093813, 0.0093813
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7, 0.03092, 0.023962, 0, 0.85534, 0.75749, 0.83288, 0.46915, 0.034133, 0.019144, 0, 0.0092575, 0.0092575, 0.0092575
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8, 0.03049, 0.02335, 0, 0.85638, 0.77501, 0.84568, 0.48421, 0.033064, 0.01893, 0, 0.0091337, 0.0091337, 0.0091337
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9, 0.029464, 0.022836, 0, 0.87385, 0.75689, 0.83902, 0.47473, 0.033736, 0.019446, 0, 0.00901, 0.00901, 0.00901
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10, 0.028927, 0.022414, 0, 0.87058, 0.76291, 0.83836, 0.46732, 0.03437, 0.019651, 0, 0.0088863, 0.0088863, 0.0088863
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11, 0.028566, 0.022261, 0, 0.86504, 0.77011, 0.84318, 0.47604, 0.033465, 0.019213, 0, 0.0087625, 0.0087625, 0.0087625
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12, 0.027956, 0.021923, 0, 0.85476, 0.77168, 0.84491, 0.48466, 0.032688, 0.01882, 0, 0.0086388, 0.0086388, 0.0086388
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13, 0.02772, 0.02173, 0, 0.86119, 0.79026, 0.85609, 0.4882, 0.033376, 0.019337, 0, 0.008515, 0.008515, 0.008515
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14, 0.027131, 0.021128, 0, 0.87567, 0.78199, 0.85549, 0.49365, 0.03306, 0.01928, 0, 0.0083913, 0.0083913, 0.0083913
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15, 0.026691, 0.021199, 0, 0.87045, 0.78705, 0.85453, 0.48935, 0.032743, 0.019439, 0, 0.0082675, 0.0082675, 0.0082675
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16, 0.026246, 0.020844, 0, 0.86617, 0.79394, 0.85683, 0.50459, 0.032289, 0.019477, 0, 0.0081437, 0.0081437, 0.0081437
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17, 0.026001, 0.020515, 0, 0.87474, 0.79456, 0.8614, 0.50697, 0.032548, 0.019612, 0, 0.00802, 0.00802, 0.00802
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18, 0.025843, 0.020263, 0, 0.87164, 0.78985, 0.85977, 0.49572, 0.03286, 0.019747, 0, 0.0078963, 0.0078963, 0.0078963
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19, 0.025307, 0.019814, 0, 0.88386, 0.78371, 0.8613, 0.50808, 0.032641, 0.020164, 0, 0.0077725, 0.0077725, 0.0077725
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20, 0.02506, 0.019861, 0, 0.87474, 0.79407, 0.86474, 0.51026, 0.032239, 0.019819, 0, 0.0076488, 0.0076488, 0.0076488
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21, 0.024831, 0.019605, 0, 0.88838, 0.79337, 0.86771, 0.52199, 0.032118, 0.020042, 0, 0.007525, 0.007525, 0.007525
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22, 0.02415, 0.019298, 0, 0.87602, 0.79356, 0.8673, 0.51608, 0.031688, 0.020088, 0, 0.0074013, 0.0074013, 0.0074013
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23, 0.024106, 0.019282, 0, 0.8797, 0.7958, 0.864, 0.51646, 0.032165, 0.02007, 0, 0.0072775, 0.0072775, 0.0072775
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24, 0.023864, 0.019081, 0, 0.88117, 0.79456, 0.86429, 0.51661, 0.031982, 0.02004, 0, 0.0071538, 0.0071538, 0.0071538
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25, 0.023603, 0.018897, 0, 0.88311, 0.80146, 0.8721, 0.52056, 0.031827, 0.019855, 0, 0.00703, 0.00703, 0.00703
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26, 0.023432, 0.018633, 0, 0.88739, 0.80151, 0.87221, 0.52409, 0.031854, 0.02001, 0, 0.0069063, 0.0069063, 0.0069063
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27, 0.023217, 0.018547, 0, 0.87712, 0.80711, 0.87094, 0.51917, 0.03161, 0.020015, 0, 0.0067825, 0.0067825, 0.0067825
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28, 0.022933, 0.018421, 0, 0.8834, 0.80401, 0.87038, 0.52186, 0.031668, 0.020249, 0, 0.0066587, 0.0066587, 0.0066587
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29, 0.022767, 0.018128, 0, 0.88202, 0.80417, 0.87323, 0.52412, 0.031704, 0.020196, 0, 0.006535, 0.006535, 0.006535
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30, 0.022603, 0.018222, 0, 0.8803, 0.81024, 0.87504, 0.5244, 0.031576, 0.020058, 0, 0.0064112, 0.0064112, 0.0064112
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31, 0.022335, 0.01796, 0, 0.88668, 0.80744, 0.87393, 0.52537, 0.03154, 0.020176, 0, 0.0062875, 0.0062875, 0.0062875
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32, 0.022157, 0.017577, 0, 0.87766, 0.81433, 0.87665, 0.52844, 0.031462, 0.020093, 0, 0.0061637, 0.0061637, 0.0061637
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33, 0.022158, 0.017984, 0, 0.88273, 0.81092, 0.87597, 0.5282, 0.031602, 0.020117, 0, 0.00604, 0.00604, 0.00604
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34, 0.021801, 0.017571, 0, 0.88569, 0.81222, 0.87736, 0.5294, 0.031389, 0.020136, 0, 0.0059163, 0.0059163, 0.0059163
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35, 0.021742, 0.017489, 0, 0.88152, 0.81317, 0.87553, 0.52937, 0.031372, 0.020244, 0, 0.0057925, 0.0057925, 0.0057925
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36, 0.02136, 0.017304, 0, 0.88046, 0.81354, 0.87724, 0.53145, 0.031391, 0.020415, 0, 0.0056688, 0.0056688, 0.0056688
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37, 0.02128, 0.017268, 0, 0.88673, 0.80465, 0.87544, 0.53091, 0.031355, 0.020477, 0, 0.005545, 0.005545, 0.005545
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38, 0.021174, 0.017063, 0, 0.88437, 0.81057, 0.87682, 0.5323, 0.031347, 0.020434, 0, 0.0054212, 0.0054212, 0.0054212
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39, 0.020998, 0.017043, 0, 0.88227, 0.81226, 0.87718, 0.53318, 0.03129, 0.020569, 0, 0.0052975, 0.0052975, 0.0052975
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40, 0.020624, 0.016898, 0, 0.88607, 0.8081, 0.87692, 0.53286, 0.031339, 0.020679, 0, 0.0051737, 0.0051737, 0.0051737
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41, 0.020378, 0.016884, 0, 0.88768, 0.80611, 0.87717, 0.53119, 0.031375, 0.020792, 0, 0.00505, 0.00505, 0.00505
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42, 0.020381, 0.016592, 0, 0.89306, 0.80343, 0.8783, 0.53234, 0.031363, 0.02084, 0, 0.0049263, 0.0049263, 0.0049263
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43, 0.020335, 0.016549, 0, 0.88844, 0.80837, 0.87809, 0.53205, 0.031374, 0.020924, 0, 0.0048025, 0.0048025, 0.0048025
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44, 0.020108, 0.016316, 0, 0.8913, 0.80487, 0.8776, 0.53242, 0.031375, 0.020934, 0, 0.0046788, 0.0046788, 0.0046788
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45, 0.02003, 0.016276, 0, 0.89132, 0.80413, 0.878, 0.53282, 0.031365, 0.020963, 0, 0.004555, 0.004555, 0.004555
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46, 0.019874, 0.016299, 0, 0.88557, 0.81015, 0.8783, 0.53268, 0.03137, 0.020986, 0, 0.0044313, 0.0044313, 0.0044313
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47, 0.01969, 0.016077, 0, 0.88787, 0.8097, 0.87899, 0.53284, 0.03139, 0.021027, 0, 0.0043075, 0.0043075, 0.0043075
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48, 0.019512, 0.01584, 0, 0.89094, 0.80554, 0.87841, 0.53325, 0.031389, 0.021069, 0, 0.0041837, 0.0041837, 0.0041837
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49, 0.019293, 0.015728, 0, 0.88709, 0.80849, 0.87744, 0.53346, 0.031429, 0.021154, 0, 0.00406, 0.00406, 0.00406
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50, 0.019171, 0.015679, 0, 0.88995, 0.80719, 0.87729, 0.53325, 0.031456, 0.021215, 0, 0.0039362, 0.0039362, 0.0039362
|
||||
51, 0.019024, 0.015475, 0, 0.89143, 0.80661, 0.87714, 0.53327, 0.031476, 0.021269, 0, 0.0038125, 0.0038125, 0.0038125
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||||
52, 0.018813, 0.015559, 0, 0.88925, 0.80781, 0.87713, 0.53341, 0.031494, 0.02133, 0, 0.0036888, 0.0036888, 0.0036888
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||||
53, 0.018791, 0.01535, 0, 0.88636, 0.80941, 0.87642, 0.53308, 0.031497, 0.021387, 0, 0.003565, 0.003565, 0.003565
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||||
54, 0.018395, 0.015212, 0, 0.88604, 0.80875, 0.8765, 0.53323, 0.031505, 0.021436, 0, 0.0034413, 0.0034413, 0.0034413
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55, 0.01827, 0.015173, 0, 0.88587, 0.80929, 0.8763, 0.53306, 0.031523, 0.021478, 0, 0.0033175, 0.0033175, 0.0033175
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||||
56, 0.018246, 0.01505, 0, 0.88589, 0.81012, 0.8765, 0.53302, 0.031537, 0.021523, 0, 0.0031938, 0.0031938, 0.0031938
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||||
57, 0.018001, 0.014984, 0, 0.88608, 0.80871, 0.87654, 0.5334, 0.031544, 0.021566, 0, 0.00307, 0.00307, 0.00307
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||||
58, 0.018037, 0.014958, 0, 0.88544, 0.81036, 0.87661, 0.53368, 0.031552, 0.021599, 0, 0.0029462, 0.0029462, 0.0029462
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||||
59, 0.017653, 0.014732, 0, 0.88683, 0.80966, 0.87681, 0.53396, 0.031549, 0.021615, 0, 0.0028225, 0.0028225, 0.0028225
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||||
60, 0.017459, 0.014548, 0, 0.88572, 0.81099, 0.87699, 0.53399, 0.031545, 0.021636, 0, 0.0026987, 0.0026987, 0.0026987
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||||
61, 0.017415, 0.014624, 0, 0.88578, 0.81053, 0.87694, 0.53403, 0.031543, 0.02166, 0, 0.002575, 0.002575, 0.002575
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||||
62, 0.017236, 0.014451, 0, 0.88657, 0.80978, 0.87747, 0.53419, 0.031548, 0.021698, 0, 0.0024513, 0.0024513, 0.0024513
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||||
63, 0.017191, 0.014502, 0, 0.88732, 0.80892, 0.87762, 0.53438, 0.031552, 0.021729, 0, 0.0023275, 0.0023275, 0.0023275
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||||
64, 0.016974, 0.014294, 0, 0.88805, 0.80847, 0.87764, 0.53452, 0.031555, 0.021756, 0, 0.0022038, 0.0022038, 0.0022038
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||||
65, 0.016788, 0.013915, 0, 0.88913, 0.80807, 0.87792, 0.53485, 0.031548, 0.021785, 0, 0.00208, 0.00208, 0.00208
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||||
66, 0.016679, 0.01386, 0, 0.88905, 0.80803, 0.87765, 0.53479, 0.031551, 0.021811, 0, 0.0019563, 0.0019563, 0.0019563
|
||||
67, 0.016605, 0.013816, 0, 0.88992, 0.80731, 0.87777, 0.53476, 0.031557, 0.021847, 0, 0.0018325, 0.0018325, 0.0018325
|
||||
68, 0.016214, 0.013727, 0, 0.88843, 0.80795, 0.87763, 0.53457, 0.031563, 0.021884, 0, 0.0017087, 0.0017087, 0.0017087
|
||||
69, 0.016106, 0.013615, 0, 0.88919, 0.80735, 0.87764, 0.5346, 0.031561, 0.021921, 0, 0.001585, 0.001585, 0.001585
|
||||
70, 0.015987, 0.013433, 0, 0.88973, 0.80715, 0.87771, 0.53469, 0.031556, 0.021959, 0, 0.0014612, 0.0014612, 0.0014612
|
||||
71, 0.015746, 0.013259, 0, 0.8901, 0.80669, 0.8774, 0.53483, 0.031556, 0.022001, 0, 0.0013375, 0.0013375, 0.0013375
|
||||
72, 0.015789, 0.013187, 0, 0.89103, 0.80638, 0.87737, 0.53488, 0.031557, 0.022042, 0, 0.0012138, 0.0012138, 0.0012138
|
||||
73, 0.015496, 0.01303, 0, 0.89132, 0.80539, 0.87721, 0.53508, 0.031558, 0.022081, 0, 0.00109, 0.00109, 0.00109
|
||||
74, 0.015368, 0.013018, 0, 0.89201, 0.80499, 0.8773, 0.53511, 0.03156, 0.022124, 0, 0.00096625, 0.00096625, 0.00096625
|
||||
75, 0.015092, 0.012764, 0, 0.89222, 0.80474, 0.8773, 0.53525, 0.031563, 0.022172, 0, 0.0008425, 0.0008425, 0.0008425
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||||
76, 0.01509, 0.012924, 0, 0.89226, 0.80413, 0.87739, 0.53531, 0.031568, 0.022219, 0, 0.00071875, 0.00071875, 0.00071875
|
||||
77, 0.014831, 0.012636, 0, 0.89273, 0.80397, 0.87737, 0.53538, 0.03157, 0.022265, 0, 0.000595, 0.000595, 0.000595
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||||
78, 0.014895, 0.012536, 0, 0.89438, 0.80224, 0.87733, 0.53539, 0.031574, 0.022315, 0, 0.00047125, 0.00047125, 0.00047125
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||||
79, 0.014628, 0.012369, 0, 0.89464, 0.80228, 0.87723, 0.53528, 0.031579, 0.022367, 0, 0.0003475, 0.0003475, 0.0003475
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||||
epoch, train/box_loss, train/obj_loss, train/cls_loss, metrics/precision, metrics/recall, metrics/mAP_0.5,metrics/mAP_0.5:0.95, val/box_loss, val/obj_loss, val/cls_loss, x/lr0, x/lr1, x/lr2
|
||||
0, 0.068575, 0.039993, 0, 0.70102, 0.58071, 0.60196, 0.2519, 0.048167, 0.021189, 0, 0.070096, 0.0033226, 0.0033226
|
||||
1, 0.048822, 0.031577, 0, 0.83348, 0.67616, 0.75758, 0.3812, 0.038854, 0.019978, 0, 0.040014, 0.0065736, 0.0065736
|
||||
2, 0.041754, 0.02902, 0, 0.77593, 0.62288, 0.69313, 0.32412, 0.041876, 0.02355, 0, 0.0098492, 0.009742, 0.009742
|
||||
3, 0.037026, 0.02777, 0, 0.83418, 0.71955, 0.80302, 0.42477, 0.035953, 0.01995, 0, 0.0096288, 0.0096288, 0.0096288
|
||||
4, 0.034654, 0.02614, 0, 0.85591, 0.7205, 0.81403, 0.45105, 0.034349, 0.019149, 0, 0.0096288, 0.0096288, 0.0096288
|
||||
5, 0.033087, 0.02533, 0, 0.84811, 0.7377, 0.81351, 0.45187, 0.03501, 0.019692, 0, 0.009505, 0.009505, 0.009505
|
||||
6, 0.031878, 0.024502, 0, 0.84654, 0.76661, 0.83513, 0.46097, 0.035043, 0.018774, 0, 0.0093813, 0.0093813, 0.0093813
|
||||
7, 0.03092, 0.023962, 0, 0.85534, 0.75749, 0.83288, 0.46915, 0.034133, 0.019144, 0, 0.0092575, 0.0092575, 0.0092575
|
||||
8, 0.03049, 0.02335, 0, 0.85638, 0.77501, 0.84568, 0.48421, 0.033064, 0.01893, 0, 0.0091337, 0.0091337, 0.0091337
|
||||
9, 0.029464, 0.022836, 0, 0.87385, 0.75689, 0.83902, 0.47473, 0.033736, 0.019446, 0, 0.00901, 0.00901, 0.00901
|
||||
10, 0.028927, 0.022414, 0, 0.87058, 0.76291, 0.83836, 0.46732, 0.03437, 0.019651, 0, 0.0088863, 0.0088863, 0.0088863
|
||||
11, 0.028566, 0.022261, 0, 0.86504, 0.77011, 0.84318, 0.47604, 0.033465, 0.019213, 0, 0.0087625, 0.0087625, 0.0087625
|
||||
12, 0.027956, 0.021923, 0, 0.85476, 0.77168, 0.84491, 0.48466, 0.032688, 0.01882, 0, 0.0086388, 0.0086388, 0.0086388
|
||||
13, 0.02772, 0.02173, 0, 0.86119, 0.79026, 0.85609, 0.4882, 0.033376, 0.019337, 0, 0.008515, 0.008515, 0.008515
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||||
14, 0.027131, 0.021128, 0, 0.87567, 0.78199, 0.85549, 0.49365, 0.03306, 0.01928, 0, 0.0083913, 0.0083913, 0.0083913
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||||
15, 0.026691, 0.021199, 0, 0.87045, 0.78705, 0.85453, 0.48935, 0.032743, 0.019439, 0, 0.0082675, 0.0082675, 0.0082675
|
||||
16, 0.026246, 0.020844, 0, 0.86617, 0.79394, 0.85683, 0.50459, 0.032289, 0.019477, 0, 0.0081437, 0.0081437, 0.0081437
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||||
17, 0.026001, 0.020515, 0, 0.87474, 0.79456, 0.8614, 0.50697, 0.032548, 0.019612, 0, 0.00802, 0.00802, 0.00802
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||||
18, 0.025843, 0.020263, 0, 0.87164, 0.78985, 0.85977, 0.49572, 0.03286, 0.019747, 0, 0.0078963, 0.0078963, 0.0078963
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||||
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||||
20, 0.02506, 0.019861, 0, 0.87474, 0.79407, 0.86474, 0.51026, 0.032239, 0.019819, 0, 0.0076488, 0.0076488, 0.0076488
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24, 0.023864, 0.019081, 0, 0.88117, 0.79456, 0.86429, 0.51661, 0.031982, 0.02004, 0, 0.0071538, 0.0071538, 0.0071538
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25, 0.023603, 0.018897, 0, 0.88311, 0.80146, 0.8721, 0.52056, 0.031827, 0.019855, 0, 0.00703, 0.00703, 0.00703
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||||
26, 0.023432, 0.018633, 0, 0.88739, 0.80151, 0.87221, 0.52409, 0.031854, 0.02001, 0, 0.0069063, 0.0069063, 0.0069063
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27, 0.023217, 0.018547, 0, 0.87712, 0.80711, 0.87094, 0.51917, 0.03161, 0.020015, 0, 0.0067825, 0.0067825, 0.0067825
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28, 0.022933, 0.018421, 0, 0.8834, 0.80401, 0.87038, 0.52186, 0.031668, 0.020249, 0, 0.0066587, 0.0066587, 0.0066587
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29, 0.022767, 0.018128, 0, 0.88202, 0.80417, 0.87323, 0.52412, 0.031704, 0.020196, 0, 0.006535, 0.006535, 0.006535
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31, 0.022335, 0.01796, 0, 0.88668, 0.80744, 0.87393, 0.52537, 0.03154, 0.020176, 0, 0.0062875, 0.0062875, 0.0062875
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32, 0.022157, 0.017577, 0, 0.87766, 0.81433, 0.87665, 0.52844, 0.031462, 0.020093, 0, 0.0061637, 0.0061637, 0.0061637
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||||
33, 0.022158, 0.017984, 0, 0.88273, 0.81092, 0.87597, 0.5282, 0.031602, 0.020117, 0, 0.00604, 0.00604, 0.00604
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34, 0.021801, 0.017571, 0, 0.88569, 0.81222, 0.87736, 0.5294, 0.031389, 0.020136, 0, 0.0059163, 0.0059163, 0.0059163
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35, 0.021742, 0.017489, 0, 0.88152, 0.81317, 0.87553, 0.52937, 0.031372, 0.020244, 0, 0.0057925, 0.0057925, 0.0057925
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36, 0.02136, 0.017304, 0, 0.88046, 0.81354, 0.87724, 0.53145, 0.031391, 0.020415, 0, 0.0056688, 0.0056688, 0.0056688
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37, 0.02128, 0.017268, 0, 0.88673, 0.80465, 0.87544, 0.53091, 0.031355, 0.020477, 0, 0.005545, 0.005545, 0.005545
|
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38, 0.021174, 0.017063, 0, 0.88437, 0.81057, 0.87682, 0.5323, 0.031347, 0.020434, 0, 0.0054212, 0.0054212, 0.0054212
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39, 0.020998, 0.017043, 0, 0.88227, 0.81226, 0.87718, 0.53318, 0.03129, 0.020569, 0, 0.0052975, 0.0052975, 0.0052975
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40, 0.020624, 0.016898, 0, 0.88607, 0.8081, 0.87692, 0.53286, 0.031339, 0.020679, 0, 0.0051737, 0.0051737, 0.0051737
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41, 0.020378, 0.016884, 0, 0.88768, 0.80611, 0.87717, 0.53119, 0.031375, 0.020792, 0, 0.00505, 0.00505, 0.00505
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42, 0.020381, 0.016592, 0, 0.89306, 0.80343, 0.8783, 0.53234, 0.031363, 0.02084, 0, 0.0049263, 0.0049263, 0.0049263
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45, 0.02003, 0.016276, 0, 0.89132, 0.80413, 0.878, 0.53282, 0.031365, 0.020963, 0, 0.004555, 0.004555, 0.004555
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46, 0.019874, 0.016299, 0, 0.88557, 0.81015, 0.8783, 0.53268, 0.03137, 0.020986, 0, 0.0044313, 0.0044313, 0.0044313
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47, 0.01969, 0.016077, 0, 0.88787, 0.8097, 0.87899, 0.53284, 0.03139, 0.021027, 0, 0.0043075, 0.0043075, 0.0043075
|
||||
48, 0.019512, 0.01584, 0, 0.89094, 0.80554, 0.87841, 0.53325, 0.031389, 0.021069, 0, 0.0041837, 0.0041837, 0.0041837
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||||
49, 0.019293, 0.015728, 0, 0.88709, 0.80849, 0.87744, 0.53346, 0.031429, 0.021154, 0, 0.00406, 0.00406, 0.00406
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||||
50, 0.019171, 0.015679, 0, 0.88995, 0.80719, 0.87729, 0.53325, 0.031456, 0.021215, 0, 0.0039362, 0.0039362, 0.0039362
|
||||
51, 0.019024, 0.015475, 0, 0.89143, 0.80661, 0.87714, 0.53327, 0.031476, 0.021269, 0, 0.0038125, 0.0038125, 0.0038125
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||||
52, 0.018813, 0.015559, 0, 0.88925, 0.80781, 0.87713, 0.53341, 0.031494, 0.02133, 0, 0.0036888, 0.0036888, 0.0036888
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53, 0.018791, 0.01535, 0, 0.88636, 0.80941, 0.87642, 0.53308, 0.031497, 0.021387, 0, 0.003565, 0.003565, 0.003565
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54, 0.018395, 0.015212, 0, 0.88604, 0.80875, 0.8765, 0.53323, 0.031505, 0.021436, 0, 0.0034413, 0.0034413, 0.0034413
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55, 0.01827, 0.015173, 0, 0.88587, 0.80929, 0.8763, 0.53306, 0.031523, 0.021478, 0, 0.0033175, 0.0033175, 0.0033175
|
||||
56, 0.018246, 0.01505, 0, 0.88589, 0.81012, 0.8765, 0.53302, 0.031537, 0.021523, 0, 0.0031938, 0.0031938, 0.0031938
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57, 0.018001, 0.014984, 0, 0.88608, 0.80871, 0.87654, 0.5334, 0.031544, 0.021566, 0, 0.00307, 0.00307, 0.00307
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58, 0.018037, 0.014958, 0, 0.88544, 0.81036, 0.87661, 0.53368, 0.031552, 0.021599, 0, 0.0029462, 0.0029462, 0.0029462
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59, 0.017653, 0.014732, 0, 0.88683, 0.80966, 0.87681, 0.53396, 0.031549, 0.021615, 0, 0.0028225, 0.0028225, 0.0028225
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60, 0.017459, 0.014548, 0, 0.88572, 0.81099, 0.87699, 0.53399, 0.031545, 0.021636, 0, 0.0026987, 0.0026987, 0.0026987
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61, 0.017415, 0.014624, 0, 0.88578, 0.81053, 0.87694, 0.53403, 0.031543, 0.02166, 0, 0.002575, 0.002575, 0.002575
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62, 0.017236, 0.014451, 0, 0.88657, 0.80978, 0.87747, 0.53419, 0.031548, 0.021698, 0, 0.0024513, 0.0024513, 0.0024513
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63, 0.017191, 0.014502, 0, 0.88732, 0.80892, 0.87762, 0.53438, 0.031552, 0.021729, 0, 0.0023275, 0.0023275, 0.0023275
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64, 0.016974, 0.014294, 0, 0.88805, 0.80847, 0.87764, 0.53452, 0.031555, 0.021756, 0, 0.0022038, 0.0022038, 0.0022038
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||||
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|
||||
|
|
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Before Width: | Height: | Size: 619 KiB After Width: | Height: | Size: 619 KiB |
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Before Width: | Height: | Size: 518 KiB After Width: | Height: | Size: 518 KiB |
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Before Width: | Height: | Size: 532 KiB After Width: | Height: | Size: 532 KiB |
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Before Width: | Height: | Size: 642 KiB After Width: | Height: | Size: 642 KiB |
|
Before Width: | Height: | Size: 655 KiB After Width: | Height: | Size: 655 KiB |
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Before Width: | Height: | Size: 530 KiB After Width: | Height: | Size: 530 KiB |
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Before Width: | Height: | Size: 572 KiB After Width: | Height: | Size: 572 KiB |
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Reference in New Issue