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Useful machine-learning related stuff.

Project description

Typical usage often looks like this:

#!/usr/bin/env python
import ml_utils as mlu

Some functions for supporting machine learning, generally and caffe-specific. Currently just a dump, ideally will clean up and add, examples etc

caffe - python layers for

  • image read (file or lmdb) - single / multi label, pixel level labels

  • on-the-fly augmentation

  • support for pixel-level segmentation (read mask as label, etc)

  • controlling and reporting acc/loss of solver with solver.step

image processing

  • image augmentation - including bounding boxes and pixel level

  • acccuracy/precision/recall reporting for single label, multilabel , bounding box, and pixel level

  • utilities e.g. read from anywhere (url/db/local file/img array)

  • grabcut

read/write various file formats

  • lmdb, hd5

  • yolo

  • deepfashion

  • tamara berg


  • etc

tagging tools

  • multilabel

  • pixel level

Project details

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