ultralytics 8.0.20 CLI yolo simplifications, DDP and ONNX fixes (#608)

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Sid Prabhakaran <s2siddhu@gmail.com>
This commit is contained in:
Glenn Jocher
2023-01-25 21:21:39 +01:00
committed by GitHub
parent 59d4335664
commit 15b3b0365a
17 changed files with 242 additions and 139 deletions

View File

@ -1,5 +1,5 @@
# Ultralytics YOLO 🚀, GPL-3.0 license
import sys
from copy import copy
import torch
@ -194,15 +194,18 @@ class Loss:
return loss.sum() * batch_size, loss.detach() # loss(box, cls, dfl)
def train(cfg=DEFAULT_CFG):
cfg.model = cfg.model or "yolov8n.pt"
cfg.data = cfg.data or "coco128.yaml" # or yolo.ClassificationDataset("mnist")
cfg.device = cfg.device if cfg.device is not None else ''
# trainer = DetectionTrainer(cfg)
# trainer.train()
from ultralytics import YOLO
model = YOLO(cfg.model)
model.train(**vars(cfg))
def train(cfg=DEFAULT_CFG, use_python=False):
model = cfg.model or "yolov8n.pt"
data = cfg.data or "coco128.yaml" # or yolo.ClassificationDataset("mnist")
device = cfg.device if cfg.device is not None else ''
args = dict(model=model, data=data, device=device, verbose=True)
if use_python:
from ultralytics import YOLO
YOLO(model).train(**args)
else:
trainer = DetectionTrainer(args)
trainer.train()
if __name__ == "__main__":