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chestxray

Source code for Youtube tutorial series on chest X-ray auto diagnosis

https://www.youtube.com/watch?v=rXtQQ35nLh8&list=PLTFxFDI1rrl6ImvUor9HHU2FKLZZw7ghU

Name		Name	Last commit message	Last commit date
Latest commit History 25 Commits
Advanced faster fast.ai training on Google Colab		Advanced faster fast.ai training on Google Colab
Bacterial or viral pneumonia Building a 3-class model with fast.ai and Google EfficientNet		Bacterial or viral pneumonia Building a 3-class model with fast.ai and Google EfficientNet
Building Docker images in an optimized way		Building Docker images in an optimized way
Building a proper Docker image for fast.ai		Building a proper Docker image for fast.ai
Building a simple Android (and iOS) client with Expo		Building a simple Android (and iOS) client with Expo
Building a simple iOS client with React Native and WebStorm		Building a simple iOS client with React Native and WebStorm
Building our own Docker image for Anaconda		Building our own Docker image for Anaconda
Calculating pixel mean and standard deviation with Dask		Calculating pixel mean and standard deviation with Dask
Classifying chest X-ray images with fast.ai		Classifying chest X-ray images with fast.ai
Classifying chest X-ray images with fastai2		Classifying chest X-ray images with fastai2
Common Docker commands and where to use them		Common Docker commands and where to use them
Converting DICOM files to JPEG images with Dask		Converting DICOM files to JPEG images with Dask
Converting our fast.ai model to Tensorflow		Converting our fast.ai model to Tensorflow
Cross validation with Scikit-Learn		Cross validation with Scikit-Learn
Drawing an EfficientNet with Fastdot		Drawing an EfficientNet with Fastdot
Editing an Onnx Model with ProtoBuf		Editing an Onnx Model with ProtoBuf
Explaining fast.ai predictions with GradCAM		Explaining fast.ai predictions with GradCAM
Filtering images with Pandas		Filtering images with Pandas
Fixing an ugly detail in our Onnx visualization		Fixing an ugly detail in our Onnx visualization
Gradient accumulation large batch size on a small GPU		Gradient accumulation large batch size on a small GPU
How to improve fast.ai model accuracy (1) train longer		How to improve fast.ai model accuracy (1) train longer
How to improve fast.ai model accuracy (2) use a bigger gun		How to improve fast.ai model accuracy (2) use a bigger gun
How to use multiple GPUs (1) simultaneous cross validation		How to use multiple GPUs (1) simultaneous cross validation
How to use multiple GPUs (2) data parallelized model		How to use multiple GPUs (2) data parallelized model
How to use multiple GPUs (3) distributed data parallelism		How to use multiple GPUs (3) distributed data parallelism
How to use multiple GPUs (4) DDP in Jupyter Notebook with iPyParallel		How to use multiple GPUs (4) DDP in Jupyter Notebook with iPyParallel
Inside fast.ai image preprocessing		Inside fast.ai image preprocessing
Jupyter autocomplete with fastai's delegate decorator		Jupyter autocomplete with fastai's delegate decorator
Low-memory training of a ResNet101 with gradient checkpointing		Low-memory training of a ResNet101 with gradient checkpointing
Plotting X-ray images with Google Turbo color map and Matplotlib		Plotting X-ray images with Google Turbo color map and Matplotlib
Plotting learning rate curve in a terminal with Sixel		Plotting learning rate curve in a terminal with Sixel
Progressive training from 128x128 to 512x512		Progressive training from 128x128 to 512x512
RSNA Kaggle pneumonia detection challenge first attempt		RSNA Kaggle pneumonia detection challenge first attempt
RSNA Kaggle pneumonia detection challenge second attempt		RSNA Kaggle pneumonia detection challenge second attempt
Running an Onnx model with Microsoft OnnxRuntime		Running an Onnx model with Microsoft OnnxRuntime
Running fast.ai in Windows Subsystem for Linux (WSL) with Nvidia GPU and CUDA 11		Running fast.ai in Windows Subsystem for Linux (WSL) with Nvidia GPU and CUDA 11
Scraping Dicom metadata with fastai2		Scraping Dicom metadata with fastai2
Sending an email after training finishes with KnockKnock		Sending an email after training finishes with KnockKnock
Setting up fast.ai on an HPC with Slurm		Setting up fast.ai on an HPC with Slurm
Setting up fast.ai with Docker		Setting up fast.ai with Docker
Single-Image style transfer with Lucent		Single-Image style transfer with Lucent
Stress testing an AI web app with JMeter and Docker		Stress testing an AI web app with JMeter and Docker
Style transfer with fastai2		Style transfer with fastai2
Train our own ResNet50 on ImageNet		Train our own ResNet50 on ImageNet
Training a fast.ai model on Google Colab		Training a fast.ai model on Google Colab
UNet exercise colorizing X-ray images		UNet exercise colorizing X-ray images
Understanding XResNet50 by drawing it with FastDot		Understanding XResNet50 by drawing it with FastDot
Using TensorBoard with fastai2		Using TensorBoard with fastai2
Using fast.ai on Windows		Using fast.ai on Windows
Using our own pretrained model in fast.ai		Using our own pretrained model in fast.ai
Visualizing a fast.ai model with Onnx and Netron		Visualizing a fast.ai model with Onnx and Netron
X-ray image segmentation with fast.ai UNet		X-ray image segmentation with fast.ai UNet
X-ray image super-resolution first run		X-ray image super-resolution first run
X-ray image super-resolution second run with GAN		X-ray image super-resolution second run with GAN
.gitignore		.gitignore
LICENSE		LICENSE
README.md		README.md

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yindavidyang/chestxray

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