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Hailo: Fixed some typography errors
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@@ -9,7 +9,7 @@ An example for a system that uses it is
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Depending on the system and the type of access various things may have to be setup.
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For Ubuntu systems like the [Raspberry Pi](/wiki/linux/raspberry_pi.md) these are often named
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`hailort-pcie-driver` and `hailort`.
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When using the [Python prorgamming language](/wiki/programming_language/python.md) refer to the
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When using the [Python programming language](/wiki/programming_language/python.md) refer to the
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[Hailo section](/wiki/programming_language/python.md#hailo).
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## Usage
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@@ -26,11 +26,11 @@ This section assumes the neural network is using
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To convert TensorFlow models first the Hailo 8 Software Suite needs to be downloaded.
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This can be done from the [official website](https://hailo.ai/developer-zone/software-downloads/)
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altough an account is needed for it.
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although, an account is needed for it.
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After downloading, extracting and then navigating into the folder a heavily customized
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[Docker](/wiki/docker.md) container can be started by running the following command.
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However it is recommended to slightly modify this file.
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However, it is recommended to slightly modify this file.
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Add a volume that contains the TensorFlow model, that is to be converted, to the environment
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variable `DOCKER_ARGS` which is set in the file `hailo_ai_sw_suite_docker_run.sh`.
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@@ -45,7 +45,7 @@ At the current time only models using `float32` or `float16` are supported.
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Mixed precision models are not supported as well.
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For this to work run the following commands inside the Docker container.
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The first command takes the path to the tensorflow model (`<path-to-tf-model>`) and will output a
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The first command takes the path to the TensorFlow model (`<path-to-tf-model>`) and will output a
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`.har` model.
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The second command is optional but recommended and takes the path to this `.har` model
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(`<path-to-har-model`) and returns an optimized `.har` model.
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@@ -68,7 +68,7 @@ the input format.
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hailo optimize --calib-set-path <data-set> <path-to-har-model>
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```
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Note that the user in the Docker container usually uses anothr UID and GID.
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Note that the user in the Docker container usually uses another UID and GID.
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To make the volume and files accessible inside the container the IDs of the files in the volume
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should be changed accordingly - for example as shown in the following example.
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`<volume-path>` is the path that points to the volume
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@@ -79,7 +79,7 @@ and `<gid>` the GID of the Docker user - which can be found using `id -g` (for e
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chown -R <uid>:<gid> <volume-path>
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```
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After the models have been converted it can be reversed using the systems user UID and GID.
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After the models have been converted it can be reversed using the user UID and GID of the system.
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The converted models can than be run using the Python programming language as described in the
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[Python article](/wiki/programming_language/python.md#hailo).
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