Ayush Chaurasia c6985da9de
New YOLOv8 Results() class for prediction outputs ()
Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
Co-authored-by: Laughing-q <1185102784@qq.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>
Co-authored-by: Laughing <61612323+Laughing-q@users.noreply.github.com>
Co-authored-by: Viet Nhat Thai <60825385+vietnhatthai@users.noreply.github.com>
Co-authored-by: Paula Derrenger <107626595+pderrenger@users.noreply.github.com>
2023-01-17 14:32:34 +01:00

71 lines
2.0 KiB
Python

# Ultralytics YOLO 🚀, GPL-3.0 license
import subprocess
from pathlib import Path
from ultralytics.yolo.utils import ROOT, SETTINGS
MODEL = Path(SETTINGS['weights_dir']) / 'yolov8n'
CFG = 'yolov8n'
def run(cmd):
# Run a subprocess command with check=True
subprocess.run(cmd.split(), check=True)
def test_checks():
run('yolo mode=checks')
# Train checks ---------------------------------------------------------------------------------------------------------
def test_train_det():
run(f'yolo mode=train task=detect model={CFG}.yaml data=coco8.yaml imgsz=32 epochs=1')
def test_train_seg():
run(f'yolo mode=train task=segment model={CFG}-seg.yaml data=coco8-seg.yaml imgsz=32 epochs=1')
def test_train_cls():
run(f'yolo mode=train task=classify model={CFG}-cls.yaml data=mnist160 imgsz=32 epochs=1')
# Val checks -----------------------------------------------------------------------------------------------------------
def test_val_detect():
run(f'yolo mode=val task=detect model={MODEL}.pt data=coco8.yaml imgsz=32 epochs=1')
def test_val_segment():
run(f'yolo mode=val task=segment model={MODEL}-seg.pt data=coco8-seg.yaml imgsz=32 epochs=1')
def test_val_classify():
pass
# Predict checks -------------------------------------------------------------------------------------------------------
def test_predict_detect():
run(f"yolo mode=predict task=detect model={MODEL}.pt source={ROOT / 'assets'}")
def test_predict_segment():
run(f"yolo mode=predict task=segment model={MODEL}-seg.pt source={ROOT / 'assets'}")
def test_predict_classify():
pass
# Export checks --------------------------------------------------------------------------------------------------------
def test_export_detect_torchscript():
run(f'yolo mode=export model={MODEL}.pt format=torchscript')
def test_export_segment_torchscript():
run(f'yolo mode=export model={MODEL}-seg.pt format=torchscript')
def test_export_classify_torchscript():
run(f'yolo mode=export model={MODEL}-cls.pt format=torchscript')