ml support code in python
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
Release files for nn-utils 0.1.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| nn_utils-0.1.0.tar.gz | 155.2 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| nn_utils-0.1.0-py2.py3-none-any.whl | Python 3, Python 2 | none | any | Details |
Total release size: 481.9 kB
Release files / nn_utils-0.1.0.tar.gz
| Download URL | nn_utils-0.1.0.tar.gz |
|---|---|
| Size | 155.2 kB |
| Tags | Source |
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Release files / nn_utils-0.1.0-py2.py3-none-any.whl
| Download URL | nn_utils-0.1.0-py2.py3-none-any.whl |
|---|---|
| Size | 326.8 kB |
| Tags | Python 2 Python 3 |
|
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