【深度学习】YOLOv8训练过程，YOLOv8实战教程，目标检测任务SOTA，关键点回归_deterministic training

可用资源

https://github.com/ultralytics/ultralytics

官方教程：https://docs.ultralytics.com/modes/train/

资源安装

更建议下载代码后使用 下面指令安装，这样可以更改源码，如果不需要更改源码就直接pip install ultralytics也是可以的。

pip install -e .
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这样安装后，可以直接修改yolov8源码，并且可以立即生效。此图是命令解释：

安装成功后：

pip list可以看到安装的包：

模型训练（检测）

可以重新创建一个新的工程去使用安装好的ultralytics包，这样修改源码可以在別的工程。

下载一个demo数据集：https://ultralytics.com/assets/coco128.zip

最终文件：

train_coco.py，我给的绝对路径：

from ultralytics import YOLO

import os
os.environ["CUDA_VISIBLE_DEVICES"] = "2"

model = YOLO('yolov8n.yaml').load('yolov8n.pt')  # build from YAML and transfer weights

# Train the model
model.train(data='/ssd/xiedong/workplace/yolov8_script/coco128.yaml', epochs=100, imgsz=640)

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coco128.yaml，这个文件在yolov8的源码中是有的，拉出来改一下，改为绝对路径。

# Train/val/test sets as 1) dir: path/to/imgs, 2) file: path/to/imgs.txt, or 3) list: [path/to/imgs1, path/to/imgs2, ..]
path: /ssd/xiedong/workplace/yolov8_script/coco128  # dataset root dir
train: images/train2017  # train images (relative to 'path') 128 images
val: images/train2017  # val images (relative to 'path') 128 images
test:  # test images (optional)

# Classes
names:
  0: person
  1: bicycle
  2: car
  3: motorcycle
  4: airplane
  5: bus
  6: train
  7: truck
  8: boat
  9: traffic light
  10: fire hydrant
  11: stop sign
  12: parking meter
  13: bench
  14: bird
  15: cat
  16: dog
  17: horse
  18: sheep
  19: cow
  20: elephant
  21: bear
  22: zebra
  23: giraffe
  24: backpack
  25: umbrella
  26: handbag
  27: tie
  28: suitcase
  29: frisbee
  30: skis
  31: snowboard
  32: sports ball
  33: kite
  34: baseball bat
  35: baseball glove
  36: skateboard
  37: surfboard
  38: tennis racket
  39: bottle
  40: wine glass
  41: cup
  42: fork
  43: knife
  44: spoon
  45: bowl
  46: banana
  47: apple
  48: sandwich
  49: orange
  50: broccoli
  51: carrot
  52: hot dog
  53: pizza
  54: donut
  55: cake
  56: chair
  57: couch
  58: potted plant
  59: bed
  60: dining table
  61: toilet
  62: tv
  63: laptop
  64: mouse
  65: remote
  66: keyboard
  67: cell phone
  68: microwave
  69: oven
  70: toaster
  71: sink
  72: refrigerator
  73: book
  74: clock
  75: vase
  76: scissors
  77: teddy bear
  78: hair drier
  79: toothbrush


# Download script/URL (optional)
download: https://ultralytics.com/assets/coco128.zip

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即可看到成功训练起来的情况：

Transferred 355/355 items from pretrained weights
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