[openpilot] is open source software built to improve upon the existing driver assistance in most new cars on the road today.
I started a TensorFlow notebook [TF_ImageScaleUp] to experiment with AI to deblur images.
[Whisper] is a general-purpose speech recognition model. It is trained on a large dataset of diverse audio and is also a multi-task model that can perform multilingual speech recognition as well as speech translation and language identification.
I commented out the following from requirements.txt:
Run the terminal commands from the Conda terminal:
conda install pytorch==1.12.0 torchvision==0.13.0 torchaudio==0.12.0 cudatoolkit=11.3 -c pytorch
py -m pip install –upgrade pip
pip install -r requirements.txt
pip install customtkinter diffusers transformers ftfy
[TensorFlow Datasets] (TFDS) provides a collection of ready-to-use datasets for use with TensorFlow, Jax, and other Machine Learning frameworks. It handles downloading and preparing the data deterministically and constructing a tf.data.Dataset (or np.array).
The [TensorFlow Datasets Catalog] has numerous datasets available through the API.
[ImageNet] is an image database organized according to the WordNet hierarchy (currently only the nouns), in which each node of the hierarchy is depicted by hundreds and thousands of images. The project has been instrumental in advancing computer vision and deep learning research. The data is available for free to researchers for non-commercial use.
[TensorFlow Hub] is a repository of trained machine learning models ready for fine-tuning and deployable anywhere. Reuse trained models like BERT and Faster R-CNN with just a few lines of code.
The [tfhub.dev] portal lets you search and discover hundreds of trained, ready-to-deploy machine learning models in one place.