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106 lines
2.9 KiB
106 lines
2.9 KiB
import torch
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from ultralytics import YOLO
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def test_model_init():
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model = YOLO("yolov8n.yaml")
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model.info()
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try:
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YOLO()
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except Exception:
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print("Successfully caught constructor assert!")
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raise Exception("constructor error didn't occur")
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def test_model_forward():
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model = YOLO("yolov8n.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("yolov8n.yaml")
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model.info()
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model = model.load("best.pt")
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model.info(verbose=True)
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def test_model_fuse():
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model = YOLO("yolov8n.yaml")
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model.fuse()
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model.load("best.pt")
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model.fuse()
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def test_visualize_preds():
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model = YOLO("best.pt")
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model.predict(source="ultralytics/assets")
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def test_val():
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model = YOLO("best.pt")
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model.val(data="coco128.yaml", imgsz=32)
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def test_model_resume():
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model = YOLO("yolov8n.yaml")
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model.train(epochs=1, imgsz=32, data="coco128.yaml")
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try:
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model.resume(task="detect")
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except AssertionError:
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print("Successfully caught resume assert!")
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def test_model_train_pretrained():
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model = YOLO("best.pt")
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model.train(data="coco128.yaml", epochs=1, imgsz=32)
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model = model.new("yolov8n.yaml")
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model.train(data="coco128.yaml", epochs=1, imgsz=32)
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img = torch.rand(512 * 512 * 3).view(1, 3, 512, 512)
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model(img)
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def test_exports():
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"""
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Format Argument Suffix CPU GPU
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0 PyTorch - .pt True True
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1 TorchScript torchscript .torchscript True True
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2 ONNX onnx .onnx True True
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3 OpenVINO openvino _openvino_model True False
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4 TensorRT engine .engine False True
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5 CoreML coreml .mlmodel True False
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6 TensorFlow SavedModel saved_model _saved_model True True
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7 TensorFlow GraphDef pb .pb True True
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8 TensorFlow Lite tflite .tflite True False
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9 TensorFlow Edge TPU edgetpu _edgetpu.tflite False False
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10 TensorFlow.js tfjs _web_model False False
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11 PaddlePaddle paddle _paddle_model True True
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"""
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from ultralytics import YOLO
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from ultralytics.yolo.engine.exporter import export_formats
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print(export_formats())
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model = YOLO("yolov8n.yaml")
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model.export(format='torchscript')
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model.export(format='onnx')
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model.export(format='openvino')
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model.export(format='coreml')
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model.export(format='paddle')
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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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test_model_train_pretrained()
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if __name__ == "__main__":
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test()
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