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.
124 lines
4.3 KiB
124 lines
4.3 KiB
# Ultralytics YOLO 🚀, AGPL-3.0 license |
|
|
|
from pathlib import Path |
|
|
|
from ultralytics import YOLO |
|
from ultralytics.yolo.cfg import get_cfg |
|
from ultralytics.yolo.engine.exporter import Exporter |
|
from ultralytics.yolo.utils import DEFAULT_CFG, 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_cfg(DEFAULT_CFG) |
|
MODEL = Path(SETTINGS['weights_dir']) / 'yolov8n' |
|
SOURCE = ROOT / 'assets' |
|
|
|
|
|
def test_func(model=None): |
|
print('callback test passed') |
|
|
|
|
|
def test_export(): |
|
exporter = Exporter() |
|
exporter.add_callback('on_export_start', test_func) |
|
assert test_func in exporter.callbacks['on_export_start'], 'callback test failed' |
|
f = exporter(model=YOLO(CFG_DET).model) |
|
YOLO(f)(SOURCE) # exported model inference |
|
|
|
|
|
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.add_callback('on_train_start', test_func) |
|
assert test_func in trainer.callbacks['on_train_start'], 'callback test failed' |
|
trainer.train() |
|
|
|
# Validator |
|
val = detect.DetectionValidator(args=CFG) |
|
val.add_callback('on_val_start', test_func) |
|
assert test_func in val.callbacks['on_val_start'], 'callback test failed' |
|
val(model=trainer.best) # validate best.pt |
|
|
|
# Predictor |
|
pred = detect.DetectionPredictor(overrides={'imgsz': [64, 64]}) |
|
pred.add_callback('on_predict_start', test_func) |
|
assert test_func in pred.callbacks['on_predict_start'], 'callback test failed' |
|
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' |
|
# YOLO(CFG_SEG).train(**overrides) # works |
|
|
|
# trainer |
|
trainer = segment.SegmentationTrainer(overrides=overrides) |
|
trainer.add_callback('on_train_start', test_func) |
|
assert test_func in trainer.callbacks['on_train_start'], 'callback test failed' |
|
trainer.train() |
|
|
|
# Validator |
|
val = segment.SegmentationValidator(args=CFG) |
|
val.add_callback('on_val_start', test_func) |
|
assert test_func in val.callbacks['on_val_start'], 'callback test failed' |
|
val(model=trainer.best) # validate best.pt |
|
|
|
# Predictor |
|
pred = segment.SegmentationPredictor(overrides={'imgsz': [64, 64]}) |
|
pred.add_callback('on_predict_start', test_func) |
|
assert test_func in pred.callbacks['on_predict_start'], 'callback test failed' |
|
result = pred(source=SOURCE, model=f'{MODEL}-seg.pt') |
|
assert len(result), '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': 'imagenet10', 'model': 'yolov8n-cls.yaml', 'imgsz': 32, 'epochs': 1, 'save': False} |
|
CFG.data = 'imagenet10' |
|
CFG.imgsz = 32 |
|
# YOLO(CFG_SEG).train(**overrides) # works |
|
|
|
# Trainer |
|
trainer = classify.ClassificationTrainer(overrides=overrides) |
|
trainer.add_callback('on_train_start', test_func) |
|
assert test_func in trainer.callbacks['on_train_start'], 'callback test failed' |
|
trainer.train() |
|
|
|
# Validator |
|
val = classify.ClassificationValidator(args=CFG) |
|
val.add_callback('on_val_start', test_func) |
|
assert test_func in val.callbacks['on_val_start'], 'callback test failed' |
|
val(model=trainer.best) |
|
|
|
# Predictor |
|
pred = classify.ClassificationPredictor(overrides={'imgsz': [64, 64]}) |
|
pred.add_callback('on_predict_start', test_func) |
|
assert test_func in pred.callbacks['on_predict_start'], 'callback test failed' |
|
result = pred(source=SOURCE, model=trainer.best) |
|
assert len(result), 'predictor test failed'
|
|
|