ignore datasets

.idea/misc.xml

@@ -1,4 +1,7 @@
 <?xml version="1.0" encoding="UTF-8"?>
 <project version="4">
+  <component name="Black">
+    <option name="sdkName" value="Python 3.10.12 WSL (Ubuntu-22.04): (/home/awin/python/venvs/model/bin/python)" />
+  </component>
   <component name="ProjectRootManager" version="2" project-jdk-name="Python 3.13 (models)" project-jdk-type="Python SDK" />
 </project>

yolov11/runs/detect/train/args.yaml

@@ -0,0 +1,106 @@
+task: detect
+mode: train
+model: yolo12n.pt
+data: coco8.yaml
+epochs: 10
+time: null
+patience: 100
+batch: 16
+imgsz: 640
+save: true
+save_period: -1
+cache: false
+device: null
+workers: 8
+project: null
+name: train
+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
+save_hybrid: 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
+copy_paste: 0.0
+copy_paste_mode: flip
+auto_augment: randaugment
+erasing: 0.4
+crop_fraction: 1.0
+cfg: null
+tracker: botsort.yaml
+save_dir: runs/detect/train

yolov11/runs/detect/train2/args.yaml

@@ -0,0 +1,106 @@
+task: detect
+mode: train
+model: yolo12n.pt
+data: coco8.yaml
+epochs: 10
+time: null
+patience: 100
+batch: 16
+imgsz: 640
+save: true
+save_period: -1
+cache: false
+device: null
+workers: 8
+project: null
+name: train2
+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
+save_hybrid: 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
+copy_paste: 0.0
+copy_paste_mode: flip
+auto_augment: randaugment
+erasing: 0.4
+crop_fraction: 1.0
+cfg: null
+tracker: botsort.yaml
+save_dir: runs/detect/train2

yolov11/runs/detect/train2/results.csv

@@ -0,0 +1,11 @@
+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
+1,6.86948,0.70939,1.05707,1.14039,0.02628,0.21667,0.08764,0.05376,2.11971,4.98083,2.04794,0,0,0
+2,11.0357,0.67899,1.18625,1.09058,0.05949,0.3,0.12129,0.05636,2.05773,4.70166,2.00079,1.07219e-06,1.07219e-06,1.07219e-06
+3,14.7562,0.90865,1.26633,1.20842,0.06927,0.56667,0.13907,0.06017,1.97415,4.37446,1.95573,1.90876e-06,1.90876e-06,1.90876e-06
+4,18.1024,0.74725,0.99608,1.08456,0.06112,0.56667,0.24832,0.08509,1.9214,4.18075,1.89617,2.50971e-06,2.50971e-06,2.50971e-06
+5,21.4479,0.70276,1.00317,1.09192,0.14125,0.36109,0.2597,0.18404,1.90686,3.91017,1.86089,2.87504e-06,2.87504e-06,2.87504e-06
+6,24.8385,0.79145,0.81997,1.07367,0.54119,0.24116,0.26546,0.18547,1.92964,3.65661,1.84599,3.00475e-06,3.00475e-06,3.00475e-06
+7,28.4703,0.89764,1.04108,1.21462,0.52741,0.32658,0.27542,0.18197,1.83827,3.44983,1.72672,2.89884e-06,2.89884e-06,2.89884e-06
+8,31.9447,0.94011,0.94038,1.21287,0.54095,0.34005,0.29672,0.20452,1.78655,3.25106,1.70385,2.55731e-06,2.55731e-06,2.55731e-06
+9,35.7747,0.83725,0.83766,1.22182,0.55701,0.35369,0.31601,0.22002,1.69535,3.09446,1.59676,1.98016e-06,1.98016e-06,1.98016e-06
+10,40.787,0.81827,0.87845,1.09094,0.56054,0.36667,0.32583,0.24564,1.63002,2.96068,1.54419,1.16739e-06,1.16739e-06,1.16739e-06

yolov11/yolov12初始化.py

@@ -4,7 +4,7 @@ from ultralytics import YOLO
 model = YOLO("yolo12n.pt")
 
 # Train the model on the COCO8 example dataset for 100 epochs
-results = model.train(data="coco8.yaml", epochs=100, imgsz=640)
+results = model.train(data="coco8.yaml", epochs=10, imgsz=640)
 print(results)
 
 # Evaluate the model's performance on the validation set