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
-
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 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
-
lmdb, hd5
-
yolo
-
deepfashion
-
tamara berg
-
ILSRVC
-
etc
-
multilabel
-
pixel level