ultralytics 8.2.82 YOLOv10 CoreML, Edge TPU and TF.js export support (#15796)
Signed-off-by: UltralyticsAssistant <web@ultralytics.com> Co-authored-by: UltralyticsAssistant <web@ultralytics.com> Co-authored-by: Ryan Hirasaki <4690732+RyanHir@users.noreply.github.com>
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4 changed files with 31 additions and 45 deletions
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@ -97,20 +97,17 @@ def benchmark(
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assert MACOS or LINUX, "CoreML and TF.js export only supported on macOS and Linux"
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assert not IS_RASPBERRYPI, "CoreML and TF.js export not supported on Raspberry Pi"
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assert not IS_JETSON, "CoreML and TF.js export not supported on NVIDIA Jetson"
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assert not is_end2end, "End-to-end models not supported by CoreML and TF.js yet"
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if i in {3, 5}: # CoreML and OpenVINO
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assert not IS_PYTHON_3_12, "CoreML and OpenVINO not supported on Python 3.12"
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if i in {6, 7, 8}: # TF SavedModel, TF GraphDef, and TFLite
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assert not isinstance(model, YOLOWorld), "YOLOWorldv2 TensorFlow exports not supported by onnx2tf yet"
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if i in {9, 10}: # TF EdgeTPU and TF.js
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assert not isinstance(model, YOLOWorld), "YOLOWorldv2 TensorFlow exports not supported by onnx2tf yet"
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assert not is_end2end, "End-to-end models not supported by TF EdgeTPU and TF.js yet"
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if i in {11}: # Paddle
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assert not isinstance(model, YOLOWorld), "YOLOWorldv2 Paddle exports not supported yet"
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assert not is_end2end, "End-to-end models not supported by PaddlePaddle yet"
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if i in {12}: # NCNN
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assert not isinstance(model, YOLOWorld), "YOLOWorldv2 NCNN exports not supported yet"
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assert not is_end2end, "End-to-end models not supported by NCNN yet"
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if "cpu" in device.type:
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assert cpu, "inference not supported on CPU"
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if "cuda" in device.type:
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@ -130,6 +127,8 @@ def benchmark(
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assert model.task != "pose" or i != 7, "GraphDef Pose inference is not supported"
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assert i not in {9, 10}, "inference not supported" # Edge TPU and TF.js are unsupported
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assert i != 5 or platform.system() == "Darwin", "inference only supported on macOS>=10.13" # CoreML
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if i in {12}:
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assert not is_end2end, "End-to-end torch.topk operation is not supported for NCNN prediction yet"
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exported_model.predict(ASSETS / "bus.jpg", imgsz=imgsz, device=device, half=half)
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# Validate
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