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====== TFLite Edge2 Demo - 8 ======
We can run TFLite models by converting them into RKNN format and running them on the onboard NPU.

===== Get Source code =====

Clone the examples [[gh>sravansenthiln1/rknn_tflite]].

```shell
$ git clone https://github.com/sravansenthiln1/rknn_tflite
$ cd rknn_tflite
```
===== RKNN Conversion =====
You can convert TFLite models to run the NPU using the ''convert.py'' conversion script from the source.

**Requires:** Ubuntu 22.04/20.04/18.04 x86 Host computer.

After you have cloned the source code:

==== Get the necessary system packages ====
```shell
$ sudo apt-get install git python3 python3-dev python3-pip
$ sudo apt-get install libxslt1-dev zlib1g-dev libglib2.0 libsm6 libgl1-mesa-glx libprotobuf-dev gcc cmake
```

==== Clone the conversion tools ====
```shell
$ git clone https://github.com/rockchip-linux/rknn-toolkit2
$ cd rknn-toolkit2
$ git checkout b25dadacc24b88eb7dfcaa47c9c525ecca89b319
```

<WRAP info>
At this point of time, you can also create a virtual environment to store all the packages you need.
This will keep your system packages clean and not disturb their package versions.
for this you need to install [[https://conda.io/projects/conda/en/stable/user-guide/install/linux.html | Conda]]
```shell
$ conda create -n npu-env
$ conda activate npu-env
```

whenever you need to convert the models, you need to activate this env.
</WRAP>
==== Find the appropriate python version ====
```shell
$ python3 --version
```
and run the command accordingly
| python version | command |
| 3.11 | ''version=cp311'' |
| 3.10 | ''version=cp310'' |
| 3.9 | ''version=cp39'' |
| 3.8 | ''version=cp38'' |
| 3.7 | ''version=cp37'' |
| 3.6 | ''version=cp36'' |

==== Install the requirements ====
```shell
$ pip3 install -r rknn-toolkit2/packages/requirements_$version-*.txt
```

==== Install the appropriate toolkit wheel ====
```shell
$ pip3 install rknn-toolkit2/packages/rknn_toolkit2-*-$version-$version-linux_x86_64.whl
$ cd ../
```

==== Try using the conversion tool ====
```shell
$ python3 convert.py
```

eg. to convert a file such as detect_model.tflite, run
```shell
$ python3 convert.py detect_model
```
in the same directory, a file called detect_model.rknn will have been created.

===== RKNN Deployment =====
To run it on your board, you need to install appropriate RKNN API wheel

After cloning the source code:

==== Install pip ====
```shell
$ sudo apt-get install python3-pip
```

==== Install necessary python packages ====
```shell
$ pip3 install numpy pillow opencv-python librosa sounddevice
```

==== clone the toolkit ====
```shell
$ git clone https://github.com/rockchip-linux/rknn-toolkit2
$ cd rknn-toolkit2
$ git checkout b25dadacc24b88eb7dfcaa47c9c525ecca89b319
```

==== Find the system python version ====
```shell
$ python3 --version
```
and run the command accordingly
| python version | command |
| 3.11 | ''version=cp311'' |
| 3.10 | ''version=cp310'' |
| 3.9 | ''version=cp39'' |
| 3.8 | ''version=cp38'' |
| 3.7 | ''version=cp37'' |
| 3.6 | ''version=cp36'' |

==== Install the appropriate toolkit wheel ====
```shell
$ pip3 install rknn_toolkit_lite2/packages/rknn_toolkit_lite2-*-$version-$version-linux_aarch64.whl
```

==== Copy the runtime library ====
```shell
$ sudo cp rknpu2/runtime/Linux/librknn_api/aarch64/librknnrt.so /usr/lib/
$ cd ../
```


===== Run Examples =====
Taking the Mobilenet v1 as example.

==== Enter the example directory ====
```shell
$ cd mobilenet_v1
```

==== Run the example ====
```shell
$ python3 run_npu_inference.py
```
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