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import torch
from ultralytics import YOLO
def test_model_init():
model = YOLO.new("yolov8n.yaml")
model.info()
try:
YOLO()
except Exception:
print("Successfully caught constructor assert!")
raise Exception("constructor error didn't occur")
def test_model_forward():
model = YOLO.new("yolov8n.yaml")
img = torch.rand(512 * 512 * 3).view(1, 3, 512, 512)
model.forward(img)
model(img)
def test_model_info():
model = YOLO.new("yolov8n.yaml")
model.info()
model = model.load("best.pt")
model.info(verbose=True)
def test_model_fuse():
model = YOLO.new("yolov8n.yaml")
model.fuse()
model.load("best.pt")
model.fuse()
def test_visualize_preds():
model = YOLO.load("best.pt")
model.predict(source="ultralytics/assets")
def test_val():
model = YOLO.load("best.pt")
model.val(data="coco128.yaml", imgsz=32)
def test_model_resume():
model = YOLO.new("yolov8n.yaml")
model.train(epochs=1, imgsz=32, data="coco128.yaml")
try:
model.resume(task="detect")
except AssertionError:
print("Successfully caught resume assert!")
def test_model_train_pretrained():
model = YOLO.load("best.pt")
model.train(data="coco128.yaml", epochs=1, imgsz=32)
model = model.new("yolov8n.yaml")
model.train(data="coco128.yaml", epochs=1, imgsz=32)
img = torch.rand(512 * 512 * 3).view(1, 3, 512, 512)
model(img)
def test():
test_model_forward()
test_model_info()
test_model_fuse()
test_visualize_preds()
test_val()
test_model_resume()
test_model_train_pretrained()
if __name__ == "__main__":
test()