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remove purge_model_cache option
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804afe3980
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4a28a3179a
@ -357,9 +357,6 @@ detectors: # required
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# 0 means choose automatically
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# increase for better performance if you have a multicore NPU e.g. set to 3 on rk3588
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num_cores: 0
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# delete old models from config/model_cache/rknn_cache/ folder
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# set to false to skip, but keep in mind to manually remove unused models
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purge_model_cache: true
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model: # required
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# name of model (will be automatically downloaded) or path to your own .rknn model file
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@ -397,5 +394,5 @@ $ cat /sys/kernel/debug/rknpu/load
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:::
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- By default the rknn detector uses the yolonas_s model (`model: path: default-fp16-yolonas_s`). This model comes with the image, so no further steps than those mentioned above are necessary and no download happens.
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- The other choices are automatically downloaded and stored in the folder `config/model_cache/rknn_cache`.
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- Finally, you can also provide your own `.rknn` model. To convert a model to `.rknn` format see the `rknn-toolkit2` (requires a x86 machine). Note, that there is only post-processing for the supported models.
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- The other choices are automatically downloaded and stored in the folder `config/model_cache/rknn_cache`. After upgrading Frigate, you should remove older models to free up space.
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- Finally, you can also provide your own `.rknn` model. You should not save your own models in the `rknn_cache` folder, store them directly in the `model_cache` folder or another subfolder. To convert a model to `.rknn` format see the `rknn-toolkit2` (requires a x86 machine). Note, that there is only post-processing for the supported models.
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@ -37,14 +37,6 @@ class Rknn(DetectionApi):
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core_mask = 2**config.num_cores - 1
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soc = self.get_soc()
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if config.purge_model_cache:
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self.purge_model_cache()
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else:
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logger.warning(
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"Purging model chache is disabled. Remember to manually delete unused models from "
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+ str(model_chache_dir[1:])
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)
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model_props = self.parse_model_input(config.model.path, soc)
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from rknnlite.api import RKNNLite
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@ -60,15 +52,6 @@ class Rknn(DetectionApi):
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def __del__(self):
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self.rknn.release()
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def purge_model_cache(self):
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if os.path.isdir(model_chache_dir):
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for file in os.listdir(model_chache_dir):
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if os.path.isfile(file):
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if file.endswith("-v2.0.0-1.rknn"):
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continue
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else:
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os.remove(file)
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def get_soc(self):
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try:
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with open("/proc/device-tree/compatible") as file:
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