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134 lines
3.6 KiB
134 lines
3.6 KiB
# Ultralytics YOLO 🚀, GPL-3.0 license
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from pathlib import Path
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import cv2
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import torch
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from PIL import Image
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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_predict_img():
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model = YOLO(MODEL)
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img = Image.open(str(SOURCE))
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output = model(source=img, save=True, verbose=True) # PIL
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assert len(output) == 1, "predict test failed"
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img = cv2.imread(str(SOURCE))
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output = model(source=img, save=True, save_txt=True) # ndarray
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assert len(output) == 1, "predict test failed"
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output = model(source=[img, img], save=True, save_txt=True) # batch
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assert len(output) == 2, "predict test failed"
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output = model(source=[img, img], save=True, stream=True) # stream
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assert len(list(output)) == 2, "predict test failed"
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tens = torch.zeros(320, 640, 3)
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output = model(tens.numpy())
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assert len(output) == 1, "predict test failed"
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def test_val():
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model = YOLO(MODEL)
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model.val(data="coco8.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="coco8.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="coco8.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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def test_workflow():
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model = YOLO(MODEL)
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model.train(data="coco8.yaml", epochs=1, imgsz=32)
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model.val()
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model.predict(SOURCE)
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model.export(format="onnx", opset=12) # export a model to ONNX format
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if __name__ == "__main__":
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test_predict_img()
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