You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
95 lines
2.7 KiB
95 lines
2.7 KiB
# Ultralytics YOLO 🚀, GPL-3.0 license
|
|
|
|
from pathlib import Path
|
|
|
|
from ultralytics.yolo.configs import get_config
|
|
from ultralytics.yolo.utils import DEFAULT_CONFIG, ROOT, SETTINGS
|
|
from ultralytics.yolo.v8 import classify, detect, segment
|
|
|
|
CFG_DET = 'yolov8n.yaml'
|
|
CFG_SEG = 'yolov8n-seg.yaml'
|
|
CFG_CLS = 'squeezenet1_0'
|
|
CFG = get_config(DEFAULT_CONFIG)
|
|
MODEL = Path(SETTINGS['weights_dir']) / 'yolov8n'
|
|
SOURCE = ROOT / "assets"
|
|
|
|
|
|
def test_detect():
|
|
overrides = {"data": "coco8.yaml", "model": CFG_DET, "imgsz": 32, "epochs": 1, "save": False}
|
|
CFG.data = "coco8.yaml"
|
|
|
|
# Trainer
|
|
trainer = detect.DetectionTrainer(overrides=overrides)
|
|
trainer.train()
|
|
|
|
# Validator
|
|
val = detect.DetectionValidator(args=CFG)
|
|
val(model=trainer.best) # validate best.pt
|
|
|
|
# Predictor
|
|
pred = detect.DetectionPredictor(overrides={"imgsz": [64, 64]})
|
|
result = pred(source=SOURCE, model=f"{MODEL}.pt")
|
|
assert len(result), "predictor test failed"
|
|
|
|
overrides["resume"] = trainer.last
|
|
trainer = detect.DetectionTrainer(overrides=overrides)
|
|
try:
|
|
trainer.train()
|
|
except Exception as e:
|
|
print(f"Expected exception caught: {e}")
|
|
return
|
|
|
|
Exception("Resume test failed!")
|
|
|
|
|
|
def test_segment():
|
|
overrides = {"data": "coco8-seg.yaml", "model": CFG_SEG, "imgsz": 32, "epochs": 1, "save": False}
|
|
CFG.data = "coco8-seg.yaml"
|
|
CFG.v5loader = False
|
|
# YOLO(CFG_SEG).train(**overrides) # works
|
|
|
|
# trainer
|
|
trainer = segment.SegmentationTrainer(overrides=overrides)
|
|
trainer.train()
|
|
|
|
# Validator
|
|
val = segment.SegmentationValidator(args=CFG)
|
|
val(model=trainer.best) # validate best.pt
|
|
|
|
# Predictor
|
|
pred = segment.SegmentationPredictor(overrides={"imgsz": [64, 64]})
|
|
result = pred(source=SOURCE, model=f"{MODEL}-seg.pt")
|
|
assert len(result) == 2, "predictor test failed"
|
|
|
|
# Test resume
|
|
overrides["resume"] = trainer.last
|
|
trainer = segment.SegmentationTrainer(overrides=overrides)
|
|
try:
|
|
trainer.train()
|
|
except Exception as e:
|
|
print(f"Expected exception caught: {e}")
|
|
return
|
|
|
|
Exception("Resume test failed!")
|
|
|
|
|
|
def test_classify():
|
|
overrides = {"data": "mnist160", "model": "yolov8n-cls.yaml", "imgsz": 32, "epochs": 1, "batch": 64, "save": False}
|
|
CFG.data = "mnist160"
|
|
CFG.imgsz = 32
|
|
CFG.batch = 64
|
|
# YOLO(CFG_SEG).train(**overrides) # works
|
|
|
|
# Trainer
|
|
trainer = classify.ClassificationTrainer(overrides=overrides)
|
|
trainer.train()
|
|
|
|
# Validator
|
|
val = classify.ClassificationValidator(args=CFG)
|
|
val(model=trainer.best)
|
|
|
|
# Predictor
|
|
pred = classify.ClassificationPredictor(overrides={"imgsz": [64, 64]})
|
|
result = pred(source=SOURCE, model=trainer.best)
|
|
assert len(result) == 2, "predictor test failed"
|