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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
mlu.imutils.resize_keep_aspect(img_arr):

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

tagging tools

  • multilabel
  • pixel level

Project details


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Files for nn-utils, version 0.1.0
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Filename, size nn_utils-0.1.0-py2.py3-none-any.whl (326.8 kB) File type Wheel Python version py2.py3 Upload date Hashes View
Filename, size nn_utils-0.1.0.tar.gz (155.2 kB) File type Source Python version None Upload date Hashes View

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