breast-cancer-toolkit 1.0.0

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BCT

Machine learning toolkit designed to support data scientists in breast cancer detection, classification and analysis.

Installation

Install the package with:

pip install breast-cancer-toolkit

Usage as CLI

Convert the format

parallel bct convert {} {.}.tiff ::: *.dcm

Usage as library

Models

Remove background with instance segmentation

Model	Training data	Resolution	# of samples seen	IoU	Accuracy

Data sources

Source	Argument	Type	Notes
image	'image.jpg'	str or Path	Single image file. Format supported: jgp, png, dcm, tiff
URL	'https://ultralytics.com/images/bus.jpg'	str	URL to an image.
screenshot	'screen'	str	Capture a screenshot.
PIL	Image.open('im.jpg')	PIL.Image	HWC format with RGB channels.
OpenCV	cv2.imread('im.jpg')	np.ndarray	HWC format with BGR channels uint8 (0-255).
numpy	np.zeros((640,1280,3))	np.ndarray	HWC format with BGR channels uint8 (0-255).
torch	torch.zeros(16,3,320,640)	torch.Tensor	BCHW format with RGB channels float32 (0.0-1.0).
CSV, json, xlsx	'sources.csv'	str or Path	CSV file containing paths to images, videos, or directories.
video	'video.mp4'	str or Path	Video file in formats like MP4, AVI, etc.
directory	'path/'	str or Path	Path to a directory containing images or videos.
glob	'path/*.jpg'	str	Glob pattern to match multiple files. Use the * character as a wildcard.
YouTube	'https://youtu.be/LNwODJXcvt4'	str	URL to a YouTube video.
stream	'rtsp://example.com/media.mp4'	str	URL for streaming protocols such as RTSP, RTMP, TCP, or an IP address.
multi-stream	'list.streams'	str or Path	*.streams text file with one stream URL per row, i.e. 8 streams will run at batch-size 8.

Note

This project has been set up using PyScaffold 4.5 and the dsproject extension 0.0.post1.dev166+g2aaddf7.d20240514.