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Check PyTorch model status for all YOLO methods (#945)

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Signed-off-by: dependabot[bot] <support@github.com>
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Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>
Co-authored-by: Ayush Chaurasia <ayush.chaurarsia@gmail.com>
This commit is contained in:
Glenn Jocher
2023-02-13 15:08:08 +04:00
committed by GitHub
parent fd5be10c66
commit 20fe708f31
21 changed files with 180 additions and 106 deletions
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12
tests/test_cli.py
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@ -48,18 +48,18 @@ def test_val_classify():
# Predict checks -------------------------------------------------------------------------------------------------------
def test_predict_detect():
run(f"yolo predict detect model={MODEL}.pt source={ROOT / 'assets'} imgsz=32")
run(f"yolo predict detect model={MODEL}.pt source=https://ultralytics.com/images/bus.jpg imgsz=32")
run(f"yolo predict detect model={MODEL}.pt source=https://ultralytics.com/assets/decelera_landscape.mov imgsz=32")
run(f"yolo predict detect model={MODEL}.pt source=https://ultralytics.com/assets/decelera_portrait.mov imgsz=32")
run(f"yolo predict model={MODEL}.pt source={ROOT / 'assets'} imgsz=32")
run(f"yolo predict model={MODEL}.pt source=https://ultralytics.com/images/bus.jpg imgsz=32")
run(f"yolo predict model={MODEL}.pt source=https://ultralytics.com/assets/decelera_landscape_min.mov imgsz=32")
run(f"yolo predict model={MODEL}.pt source=https://ultralytics.com/assets/decelera_portrait_min.mov imgsz=32")
def test_predict_segment():
run(f"yolo predict segment model={MODEL}-seg.pt source={ROOT / 'assets'} imgsz=32")
run(f"yolo predict model={MODEL}-seg.pt source={ROOT / 'assets'} imgsz=32")
def test_predict_classify():
run(f"yolo predict classify model={MODEL}-cls.pt source={ROOT / 'assets'} imgsz=32")
run(f"yolo predict model={MODEL}-cls.pt source={ROOT / 'assets'} imgsz=32")
# Export checks --------------------------------------------------------------------------------------------------------

18
tests/test_python.py
View File

@ -18,7 +18,6 @@ SOURCE = ROOT / 'assets/bus.jpg'
def test_model_forward():
model = YOLO(CFG)
model.predict(SOURCE)
model(SOURCE)
@ -38,11 +37,10 @@ def test_model_fuse():
def test_predict_dir():
model = YOLO(MODEL)
model.predict(source=ROOT / "assets")
model(source=ROOT / "assets")
def test_predict_img():
model = YOLO(MODEL)
img = Image.open(str(SOURCE))
output = model(source=img, save=True, verbose=True) # PIL
@ -106,22 +104,26 @@ def test_export_torchscript():
print(export_formats())
model = YOLO(MODEL)
model.export(format='torchscript')
f = model.export(format='torchscript')
YOLO(f)(SOURCE) # exported model inference
def test_export_onnx():
model = YOLO(MODEL)
model.export(format='onnx')
f = model.export(format='onnx')
YOLO(f)(SOURCE) # exported model inference
def test_export_openvino():
model = YOLO(MODEL)
model.export(format='openvino')
f = model.export(format='openvino')
YOLO(f)(SOURCE) # exported model inference
def test_export_coreml():
model = YOLO(MODEL)
model.export(format='coreml')
# YOLO(f)(SOURCE) # model prediction only supported on macOS
def test_export_paddle(enabled=False):
@ -140,6 +142,7 @@ def test_workflow():
model = YOLO(MODEL)
model.train(data="coco8.yaml", epochs=1, imgsz=32)
model.val()
print(model.metrics)
model.predict(SOURCE)
model.export(format="onnx", opset=12) # export a model to ONNX format
@ -164,6 +167,3 @@ def test_predict_callback_and_setup():
print('test_callback', bs)
boxes = result.boxes # Boxes object for bbox outputs
print(boxes)
test_predict_img()