https://github.com/juldpnt/flower-classification-transfer-learning

Classification of few flowers based on transfer learning
https://github.com/juldpnt/flower-classification-transfer-learning

classification cnn keras transfer-learning

Last synced: 23 days ago
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Classification of few flowers based on transfer learning

• Host: GitHub
• URL: https://github.com/juldpnt/flower-classification-transfer-learning
• Owner: juldpnt
• License: mit
• Created: 2023-08-22T06:36:51.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2023-08-27T19:58:31.000Z (over 1 year ago)
• Last Synced: 2024-11-19T19:07:07.305Z (3 months ago)
• Topics: classification, cnn, keras, transfer-learning
• Language: Jupyter Notebook
• Homepage:
• Size: 84.2 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • Changelog: history.npy
  • License: LICENSE

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README

        
This repository follows the tutorial of this [Gitlab](https://gitlab.com/ecostat/imaginecology/-/tree/master/projects/classifierWithKeras/) made by Gaspard Dussert & Vincent Miele  (CNRS/LBBE).

It is recommended to use a virtual environment to avoid conflicts with other projects, using venv or conda. Venv won't be explained here, but you can find more information [here](https://docs.python.org/3/library/venv.html).

If you don't have anaconda, you can either install the lightweigth version [miniconda](https://docs.conda.io/en/latest/miniconda.html) or install the full version [anaconda](https://www.anaconda.com/download). 

You can create a virtual environment with the following command with an anaconda/miniconda prompt:

```python

conda create -n myenv pip

```

Then, you can activate your virtual environment with the following command:

```python

conda activate myenv

```

You can move to the directory of the project with the following command:

```python

cd path/to/directory

```

And finally, you can install the required packages with the following command while in the right directory:

```python

pip install -r requirements.txt 

```

If you want to run the notebook, write the following command while being in the right directory, it will open a jupyter notebook in your browser:

```python

jupyter lab

```