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https://github.com/blakeblackshear/frigate.git
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update rknn
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parent
f4b41c592a
commit
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@ -18,8 +18,7 @@ RUN --mount=type=bind,from=rk-wheels,source=/rk-wheels,target=/deps/rk-wheels \
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WORKDIR /opt/frigate/
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WORKDIR /opt/frigate/
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COPY --from=rootfs / /
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COPY --from=rootfs / /
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ADD https://github.com/MarcA711/rknpu2/releases/download/v1.5.2/librknnrt_rk356x.so /usr/lib/
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ADD https://github.com/MarcA711/rknn-toolkit2/releases/download/v2.0.0/librknnrt.so /usr/lib/
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ADD https://github.com/MarcA711/rknpu2/releases/download/v1.5.2/librknnrt_rk3588.so /usr/lib/
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# TODO removed models, other models support may need to be added back in
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# TODO removed models, other models support may need to be added back in
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@ -1,2 +1 @@
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hide-warnings == 0.17
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rknn-toolkit-lite2 @ https://github.com/MarcA711/rknn-toolkit2/releases/download/v2.0.0/rknn_toolkit_lite2-2.0.0b0-cp39-cp39-linux_aarch64.whl
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rknn-toolkit-lite2 @ https://github.com/MarcA711/rknn-toolkit2/releases/download/v1.5.2/rknn_toolkit_lite2-1.5.2-cp39-cp39-linux_aarch64.whl
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@ -32,6 +32,7 @@ class Rknn(DetectionApi):
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type_key = DETECTOR_KEY
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type_key = DETECTOR_KEY
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def __init__(self, config: RknnDetectorConfig):
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def __init__(self, config: RknnDetectorConfig):
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super().__init__(config)
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self.height = config.model.height
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self.height = config.model.height
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self.width = config.model.width
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self.width = config.model.width
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core_mask = 2**config.num_cores - 1
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core_mask = 2**config.num_cores - 1
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@ -108,6 +109,8 @@ class Rknn(DetectionApi):
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f"Model {model_path} is unsupported. Provide your own model or choose one of the following: {supported_models_str}"
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f"Model {model_path} is unsupported. Provide your own model or choose one of the following: {supported_models_str}"
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)
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)
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return model_props
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def download_model(self, filename):
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def download_model(self, filename):
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if not os.path.isdir(model_chache_dir):
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if not os.path.isdir(model_chache_dir):
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os.mkdir(model_chache_dir)
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os.mkdir(model_chache_dir)
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@ -133,13 +136,10 @@ class Rknn(DetectionApi):
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'Make sure to set the model input_tensor to "nhwc" in your config.yml.'
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'Make sure to set the model input_tensor to "nhwc" in your config.yml.'
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)
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)
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def post_process(self, output):
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pass
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def detect_raw(self, tensor_input):
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def detect_raw(self, tensor_input):
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output = self.rknn.inference(
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output = self.rknn.inference(
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[
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[
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tensor_input,
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tensor_input,
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]
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]
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)
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)
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return self.postprocess(output[0])
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return self.post_process(output)
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