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
1 maintainer
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