The Founder’s Guide:

Open the YoloV3-Tf2 Directory:

cd yolov3-tf2

Set the Pyenv Version Environment Variable:

PYENV_VERSION=3.6.8

Create the Virtual Environment:

Python 3.5:
python -m venv venv35
Python 3.6: <----------
python -m venv venv36
Python 3.7:
python -m venv venv37
Python 3.8:
python -m venv venv38

Activate the Virtual Environment:

Python 3.5:
source venv35/bin/activate
Python 3.6: <----------
source venv36/bin/activate
Python 3.7:
source venv37/bin/activate
Python 3.8:
source venv38/bin/activate

Upgrade Pip:

python -m pip install --upgrade pip

Install the Requirements:

python -m pip install --requirement requirements-gpu.txt

Download the Weights:

wget https://pjreddie.com/media/files/yolov3.weights -O data/yolov3.weights

Convert the Weights:

python convert.py --weights ./data/yolov3.weights --output ./checkpoints/yolov3.tf

Use the Repository:

venv36/bin/python detect.py --image ./data/meme.jpg

Install the IPython Kernel:

python -m pip install ipykernel

Install the Virtual Environment:

Python 3.5:
sudo venv35/bin/python -m ipykernel install --name "yolov3-tf2" --display-name "yolov3-tf2"
Python 3.6: <----------
sudo venv36/bin/python -m ipykernel install --name "yolov3-tf2" --display-name "yolov3-tf2"
Python 3.7:
sudo venv37/bin/python -m ipykernel install --name "yolov3-tf2" --display-name "yolov3-tf2"
Python 3.8:
sudo venv38/bin/python -m ipykernel install --name "yolov3-tf2" --display-name "yolov3-tf2"

Open the YoloV3-Tf2 Directory:

Use the Virtual Environment:

Run the Code Cell:

Run the Code Cell:

Deactivate the Virtual Environment:

deactivate

Unset the Pyenv Version Environment Variable:

PYENV_VERSION=""

List the Installed Virtual Environments:

jupyter kernelspec list

Uninstall the Virtual Environment:

sudo ~/.pyenv/shims/jupyter kernelspec uninstall yolov3-tf2

Next Steps:

Linux:
01. Install and Manage Multiple Python Versions
02. Install the NVIDIA CUDA Driver, Toolkit, cuDNN, and TensorRT
03. Install the Jupyter Notebook Server
04. Install Virtual Environments in Jupyter Notebook
05. Install the Python Environment for AI and Machine Learning
WSL2:
01. Install Windows Subsystem for Linux 2
02. Install and Manage Multiple Python Versions
03. Install the NVIDIA CUDA Driver, Toolkit, cuDNN, and TensorRT
04. Install the Jupyter Notebook Server
05. Install Virtual Environments in Jupyter Notebook
06. Install the Python Environment for AI and Machine Learning
07. Install Ubuntu Desktop With a Graphical User Interface (Bonus)
Windows 10:
01. Install and Manage Multiple Python Versions
02. Install the NVIDIA CUDA Driver, Toolkit, cuDNN, and TensorRT
03. Install the Jupyter Notebook Server
04. Install Virtual Environments in Jupyter Notebook
05. Install the Python Environment for AI and Machine Learning
Mac:
01. Install and Manage Multiple Python Versions
02. Install the Jupyter Notebook Server
03. Install Virtual Environments in Jupyter Notebook
04. Install the Python Environment for AI and Machine Learning

From: Non-Technical | To: Technical | Writes: To Make It Easier For Everyone | Topics: #Setup #Basics #AI #MachineLearning #DeepLearning #Repositories

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