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100 lines
2.6 KiB
100 lines
2.6 KiB
# Ultralytics YOLO 🚀, GPL-3.0 license |
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from pathlib import Path |
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from ultralytics import YOLO |
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from ultralytics.yolo.utils import ROOT, SETTINGS |
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MODEL = Path(SETTINGS['weights_dir']) / 'yolov8n.pt' |
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CFG = 'yolov8n.yaml' |
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SOURCE = ROOT / 'assets/bus.jpg' |
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def test_model_forward(): |
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model = YOLO(CFG) |
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model.predict(SOURCE) |
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model(SOURCE) |
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def test_model_info(): |
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model = YOLO(CFG) |
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model.info() |
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model = YOLO(MODEL) |
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model.info(verbose=True) |
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def test_model_fuse(): |
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model = YOLO(CFG) |
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model.fuse() |
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model = YOLO(MODEL) |
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model.fuse() |
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def test_predict_dir(): |
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model = YOLO(MODEL) |
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model.predict(source=ROOT / "assets") |
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def test_val(): |
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model = YOLO(MODEL) |
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model.val(data="coco128.yaml", imgsz=32) |
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def test_train_scratch(): |
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model = YOLO(CFG) |
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model.train(data="coco128.yaml", epochs=1, imgsz=32) |
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model(SOURCE) |
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def test_train_pretrained(): |
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model = YOLO(MODEL) |
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model.train(data="coco128.yaml", epochs=1, imgsz=32) |
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model(SOURCE) |
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def test_export_torchscript(): |
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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.yolo.engine.exporter import export_formats |
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print(export_formats()) |
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model = YOLO(MODEL) |
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model.export(format='torchscript') |
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def test_export_onnx(): |
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model = YOLO(MODEL) |
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model.export(format='onnx') |
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def test_export_openvino(): |
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model = YOLO(MODEL) |
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model.export(format='openvino') |
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def test_export_coreml(): |
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model = YOLO(MODEL) |
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model.export(format='coreml') |
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def test_export_paddle(): |
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model = YOLO(MODEL) |
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model.export(format='paddle') |
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def test_all_model_yamls(): |
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for m in list((ROOT / 'models').rglob('*.yaml')): |
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YOLO(m.name)
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