[CF]提交文件

data/labels/train/6.txt

@@ -1 +0,0 @@
-0 0.4882044560943644 0.4646133682830928 0.17169069462647438 0.40235910878112674

data/labels/train/7.txt

@@ -1 +0,0 @@
-0 0.48361730013106086 0.496723460026212 0.2568807339449536 0.4325032765399734

data/labels/train/8.txt

@@ -1 +0,0 @@
-0 0.6159895150720839 0.5498034076015726 0.16251638269986907 0.41546526867627775

data/labels/val/6.txt

@@ -1 +0,0 @@
-0 0.4882044560943644 0.4646133682830928 0.17169069462647438 0.40235910878112674

data/labels/val/7.txt

@@ -1 +0,0 @@
-0 0.48361730013106086 0.496723460026212 0.2568807339449536 0.4325032765399734

data/labels/val/8.txt

@@ -1 +0,0 @@
-0 0.6159895150720839 0.5498034076015726 0.16251638269986907 0.41546526867627775

runs/detect/train7/args.yaml

@@ -0,0 +1,105 @@
+task: detect
+mode: train
+model: C:\workspace\le-yolo\runs\detect\train6\weights\best.pt
+data: data.yaml
+epochs: 200
+time: null
+patience: 100
+batch: 2
+imgsz: 640
+save: true
+save_period: -1
+cache: false
+device: cpu
+workers: 8
+project: null
+name: train7
+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
+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
+cutmix: 0.0
+copy_paste: 0.0
+copy_paste_mode: flip
+auto_augment: randaugment
+erasing: 0.4
+cfg: null
+tracker: botsort.yaml
+save_dir: C:\workspace\le-yolo\runs\detect\train7

runs/detect/train7/results.csv

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runs/detect/train8/args.yaml

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runs/detect/train8/results.csv

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runs/detect/train9/args.yaml

@@ -0,0 +1,105 @@
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+save_dir: C:\workspace\le-yolo\runs\detect\train9

runs/detect/train9/results.csv

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src/data.yaml

@@ -2,4 +2,4 @@ path: C:\workspace\le-yolo\data
 train: images/train
 val: images/val
 nc: 1
-names: [ 'A' ]
+names: [ 'person' ]

src/test.py

@@ -1,3 +1,3 @@
 from ultralytics import YOLO
-model = YOLO(r"C:\workspace\le-yolo\runs\detect\train6\weights\best.pt")
+model = YOLO(r"C:\workspace\le-yolo\runs\detect\train9\weights\best.pt")
 results = model.predict("../res/2.mp4", show=True, save=True)

src/train.py

@@ -1,4 +1,4 @@
 from ultralytics import YOLO
 model = YOLO("yolov8n.pt")
-model.train(data="data.yaml", epochs=500,  batch=3, device='cpu')
+model.train(data="data.yaml", epochs=100,  batch=3, device='cpu')
 print('训练完成')