wait to merge. changes dependent on lobe-python open PR.
This commit is contained in:
Adi Azulay 2020-10-22 18:25:00 -07:00 коммит произвёл GitHub
Родитель b57c900e17
Коммит d2cda1575b
Не найден ключ, соответствующий данной подписи
Идентификатор ключа GPG: 4AEE18F83AFDEB23
1 изменённых файлов: 5 добавлений и 7 удалений

Просмотреть файл

@ -74,13 +74,11 @@ To build this project successfully, you should have some prior knowledge of:
* Hot melt tool (or other non-conductive glue -- epoxy works great but is 100% permanent)
## Setup
1. Export your Lobe ML model in a TensorFlow (TF) format.
2. On your PC, open WinSCP and connect to your Pi. Create a *Lobe* folder in your Pi's home directory and create a *model* folder in that directory. Drag the resulting Lobe TF folder contents onto the Pi. Note the file path: /home/pi/Lobe/model
1. Export your Lobe ML model in a TensorFlow Lite (TF Lite) format.
2. On your PC, open WinSCP and connect to your Pi. Create a *Lobe* folder in your Pi's home directory and create a *model* folder in that directory. Drag the resulting Lobe TF Lite folder contents onto the Pi. Note the file path: /home/pi/Lobe/model
3. On the Pi, open a terminal and download the [lobe-python library](https://github.com/lobe/lobe-python) for Python3:
```
pip3 install setuptools
pip3 install tensorflow==1.13.1
pip3 install git+https://github.com/lobe/lobe-python
```sh
pip3 install lobe
```
4. Download this repo onto the Pi (or download onto your PC and send the example python code to the Pi via WinSCP).
@ -91,7 +89,7 @@ To build this project successfully, you should have some prior knowledge of:
## Running the sample
Once you've connected the hardware to the Pi's GPIO pins, read through the example code and update any file paths as needed:
* Line 29: filepath to the Lobe TF model
* Line 29: filepath to the Lobe TF Lite model directory
* Lines 47 and 83: filepath to captured images via Pi Camera
Run the program using Python3 in the terminal window: