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63 lines
1.2 KiB
Python
63 lines
1.2 KiB
Python
import torch
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from ultralytics.yolo import YOLO
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def test_model_forward():
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model = YOLO()
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model.new("yolov5n-seg.yaml")
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img = torch.rand(512 * 512 * 3).view(1, 3, 512, 512)
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model.forward(img)
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model(img)
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def test_model_info():
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model = YOLO()
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model.new("yolov5n.yaml")
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model.info()
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model.load("balloon-detect.pt")
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model.info(verbose=True)
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def test_model_fuse():
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model = YOLO()
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model.new("yolov5n.yaml")
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model.fuse()
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model.load("balloon-detect.pt")
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model.fuse()
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def test_visualize_preds():
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model = YOLO()
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model.load("balloon-segment.pt")
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model.predict(source="ultralytics/assets")
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def test_val():
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model = YOLO()
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model.load("balloon-segment.pt")
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model.val(data="coco128-seg.yaml", img_size=32)
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def test_model_resume():
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model = YOLO()
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model.new("yolov5n-seg.yaml")
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model.train(epochs=1, img_size=32, data="coco128-seg.yaml")
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try:
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model.resume(task="segment")
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except AssertionError:
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print("Successfully caught resume assert!")
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def test():
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test_model_forward()
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test_model_info()
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test_model_fuse()
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test_visualize_preds()
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test_val()
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test_model_resume()
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if __name__ == "__main__":
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test()
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