This project is use ChatGPT create a Inception and EfficientNet's code.
In this method we train a convolutional neural network with 6 classes which contain Bus, Cars, Motorcycles, Pickup, Truck and Van in Malaysia. The model it use Inception v1 and EfficientNet b3.
Setup environment
pip install requirements.txt
To run the code for training, one can use the following command:
python train.py --modelname inception
To test the model one can use the following command:
python test.py --modelname inception
The Model Architecture of Inception and Efficientnet will be in
efficient.py and inception.py
All the information of function will be in utils.py
EarlyStopping class will be stored in pytorchtools.py
All preprocessing used jupyter lab to perform:
all the processing will be store in these file which include image augmentation, convert to h5 file, and train test split.
- Augmentation
image_augmentation.ipynb - Web Scraping
scrap_from_website.ipynb - Train, validation, test splitting
train_test_split.ipynb - Convert into h5 file for machine learning
convert2h5.ipynb
The result contain Inception and Efficient classification report, training and validation 's loss and accuracy, confusion matrix and the checkpoint file of the trained model.
Loss and Accuracy
Classification Report of Inception
Loss and Accuracy
Classification Report of Inception
