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https://github.com/bensuperpc/easyai
Make your own AI easily !
https://github.com/bensuperpc/easyai
ai cuda python python3 tensorflow
Last synced: 22 days ago
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Make your own AI easily !
- Host: GitHub
- URL: https://github.com/bensuperpc/easyai
- Owner: bensuperpc
- License: mit
- Created: 2022-08-19T17:48:33.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2023-12-06T15:26:43.000Z (about 1 year ago)
- Last Synced: 2025-01-14T01:35:40.904Z (26 days ago)
- Topics: ai, cuda, python, python3, tensorflow
- Language: Python
- Homepage: https://github.com/bensuperpc
- Size: 85.9 KB
- Stars: 2
- Watchers: 3
- Forks: 1
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# EasyAI
## _Make your own AI easily ! via tensorflow 2_
[](https://github.com/bensuperpc/EasyAI/actions/workflows/base.yml)
## Description
The main goal of this project is to create an AI easily using tensorflow
## Software requirements
- [Python 3.6+](https://www.python.org/downloads/)
- [Tensorflow 2.4+](https://www.tensorflow.org/install)
- [Tensorboard 2.4+](https://www.tensorflow.org/tensorboard/get_started)
- [OpenCV 4.5+](https://pypi.org/project/opencv-python/)
- [Git](https://git-scm.com/downloads)
- [Docker](https://docs.docker.com/get-docker/)
## Hardware requirements
We recommend using a GPU with Hardware Acceleration for Tensorflow.
| Hardware | minimum | recommended |
| --- | --- | --- |
| CPU | 2 cores | 4 cores |
| RAM | 4 GB | 8 GB |
| GPU | 2 GB | 4 GB |
## Usage
Get help:
```bash
python3 EasyAI.py --help
```
Launch training:
```bash
python3 EasyAI.py
```
Launch training without GPU:
```bash
python3 EasyAI.py --no-gpu
```
Launch training, save model and set dataset path:
```bash
python EasyAI.py --data_dir ./dataset/flower_photos --save test_AI.h5
```
## Example
Train a model with flowers dataset:
```bash
python EasyAI.py --save test_AI.h5
```
Predict images (**class_name order is important**):
```bash
python EasyAI.py --load test_AI.h5 --predict ./dataset/flower_photos/roses/ --class_name daisy dandelion roses sunflowers tulips
```
## Command table
| Command | Description | Default | Example |
| --- | --- | --- | --- |
| --data_dir | Path to the data directory. | ./dataset/ | --data_dir ./dataset/ |
| --save-model | Save model to a HDF5 file. | None | --save test_AI.h5 |
| --load-model | Load model from a HDF5 file. | None | --load test_AI.h5 |
| --predict | Predict images. | None | --predict ./dataset/flower_photos/roses/ |
| --class_name | Class name. | None | --class_name daisy dandelion roses sunflowers tulips |
| --no-gpu | Disable GPU. | False | --no-gpu |
| --batch_size | Batch size. | 32 | --batch_size 32 |
| --epochs | Number of epochs. | 10 | --epochs 10 |
| --model_path | Path to the model. | None | --model_path ./model/ |
| --tensorboard | Enable tensorboard (Slow). | False | --tensorboard |
| --checkpoint | Enable checkpoint. | False | --checkpoint |
## Done features
- Working model
- Tensorboard integration
- GPU support
- Load and save model
- Data augmentation
- Argument parser
## Work in progress features
- Data set generator
- Load and save weights
## Future features
- Lite version
- Docker image
- pip package
### Open source projects used
- [tensorflow](https://github.com/tensorflow/tensorflow)
- [tensorboard](https://github.com/tensorflow/tensorboard)
- [opencv](https://github.com/opencv/opencv)
- [git](https://github.com/git/git)
- [docker](https://github.com/docker/docker)
- [actions](https://github.com/actions/virtual-environments)
## Licensing
[MIT License](LICENSE)