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Support model caching
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@ -7,7 +7,7 @@ cython == 0.29.*; platform_machine == 'x86_64'
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nvidia-cuda-runtime-cu12 == 12.1.*; platform_machine == 'x86_64'
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nvidia-cuda-runtime-cu12 == 12.1.*; platform_machine == 'x86_64'
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nvidia-cuda-runtime-cu11 == 11.8.*; platform_machine == 'x86_64'
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nvidia-cuda-runtime-cu11 == 11.8.*; platform_machine == 'x86_64'
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nvidia-cublas-cu11 == 11.11.3.6; platform_machine == 'x86_64'
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nvidia-cublas-cu11 == 11.11.3.6; platform_machine == 'x86_64'
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nvidia-cudnn-cu11 == 8.5.0.*; platform_machine == 'x86_64'
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nvidia-cudnn-cu11 == 8.6.0.*; platform_machine == 'x86_64'
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nvidia-cufft-cu11==10.*; platform_machine == 'x86_64'
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nvidia-cufft-cu11==10.*; platform_machine == 'x86_64'
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onnx==1.14.0; platform_machine == 'x86_64'
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onnx==1.14.0; platform_machine == 'x86_64'
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onnxruntime-gpu==1.17.*; platform_machine == 'x86_64'
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onnxruntime-gpu==1.17.*; platform_machine == 'x86_64'
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@ -36,7 +36,28 @@ class ONNXDetector(DetectionApi):
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path = detector_config.model.path
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path = detector_config.model.path
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logger.info(f"ONNX: loading {detector_config.model.path}")
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logger.info(f"ONNX: loading {detector_config.model.path}")
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self.model = ort.InferenceSession(path, providers=ort.get_available_providers())
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providers = ort.get_available_providers()
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options = []
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for provider in providers:
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if provider == "TensorrtExecutionProvider":
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options.append(
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{
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"trt_timing_cache_enable": True,
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"trt_timing_cache_path": "/config/model_cache/onnx",
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"trt_engine_cache_enable": True,
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"trt_engine_cache_path": "/config/model_cache/onnx/trt-engines",
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}
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)
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elif provider == "OpenVINOExecutionProvider":
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options.append({"cache_dir": "/config/model_cache/onnx"})
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else:
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options.append({})
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self.model = ort.InferenceSession(
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path, providers=providers, provider_options=options
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)
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self.h = detector_config.model.height
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self.h = detector_config.model.height
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self.w = detector_config.model.width
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self.w = detector_config.model.width
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