Visual UI interface for fastai
Visual UI adds a graphical interface to fastai allowing the user to quickly load, choose parameters, train and view results without the need to dig deep into the code.
- after a training run, the model is saved in the models folder with the following name: 'architecture' + 'pretrained' + batchsize + image size eg: resnet50_pretrained_True_batch_32_image_128.pth
- updated tkinter askdirectory code: now after choosing a file the tkinter dialogue box will be destroyed - previously the box would remain open
- results tab added where you can load your saved model and plot multi_plot_losses, top_losses and Confusion_matrix
- path and image_path (for augmentations) is now within vision_ui so no need to have a seperate cell to specify path
- included link to fastai docs and forum in 'info' tab
All tabs are provided within an accordion design using ipywidgets, this allows for all aspects of choosing and viewing parameters in one line of sight
The Augmentation tab utilizes fastai parameters so you can view what different image augmentations look like and compare
View batch information
Review model data and choose suitable metrics for training
Review parameters get learning rate and train using the one cycle policy
Can experiment with various learning rates and train
- fastai
I am using the developer version:
git clone https://github.com/fastai/fastai
cd fastai
tools/run-after-git-clone
pip install -e ".[dev]"
for installation instructions visit Fastai Installation Readme
- ipywidgets
pip install ipywidgets jupyter nbextension enable --py widgetsnbextension
or
conda install -c conda-forge ipywidgets
for installation instructions visit Installation docs
- psutil
psutil (process and system utilities) is a cross-platform library for retrieving information on running processes and system utilization (CPU, memory, disks, network, sensors) in Python
pip install psutil
git clone this repository
git clone https://github.com/asvcode/Vision_UI.git
run 01_UI_Fastai.ipynb
and run display_ui(path)
Colab does not currently support ipywidgets because their output is in its own frame so prevents ipywidets from working. This is the link to issues thread Link
- Currently on works with images using the
ImageDataBunch.from_folder
option. Plans to expand to.from_csv
and.from_df