Skip to main content

Microbe segmentation in dense colonies

Project description

MiSiC

Microbe segmentation in dense colonies.

Installation

Requires version python version 3.6/7

pip install misic

Usage

use package

from misic.misic import *
from skimage.io import imsave,imread
from skimage.transform import resize,rescale

filename = 'awesome_image.tif'

# read image using your favorite package
im = imread(filename)

# Parameters that need to be changed
## Ideally, use a single image to fine tune two parameters : mean_width and noise_variance (optional)

#input the approximate mean width of microbe under consideration
mean_width = 8

# compute scaling factor
scale = (10/mean_width)

# Initialize MiSiC
mseg = MiSiC()

# preprocess using inbuit function or if you are feeling lucky use your own preprocessing
im = rescale(im,scale,preserve_range = True)

# add local noise
img = add_noise(im,sensitivity = 0.13,invert = True)

# segment
yp = mseg.segment(img,invert = True)
yp = resize(yp,[sr,sc,-1])

# watershed based post processing
yp = postprocess_ws(img,yp)

# save 8-bit segmented image and use it as you like
imsave('segmented.tif', yp.astype(np.uint8))
''''

### In case of gpu error, one might need to disabple gpu before importing MiSiC [ os.environ["CUDA_VISIBLE_DEVICES"]="-1" ]

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

misic-1.1.1.tar.gz (17.1 kB view details)

Uploaded Source

Built Distribution

misic-1.1.1-py3-none-any.whl (7.3 MB view details)

Uploaded Python 3

File details

Details for the file misic-1.1.1.tar.gz.

File metadata

  • Download URL: misic-1.1.1.tar.gz
  • Upload date:
  • Size: 17.1 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.1 importlib_metadata/4.0.0 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.60.0 CPython/3.9.4

File hashes

Hashes for misic-1.1.1.tar.gz
Algorithm Hash digest
SHA256 19d3ceb5da22a7fbf067fc08fed31645bed7a7dd4932eaddbe5072c690a038b8
MD5 283659510bc177fbc41cfc25f78c42da
BLAKE2b-256 3212319acbcd7fa0cbf629c409435b578d0cdacb02d303eff18165f1a4aeb034

See more details on using hashes here.

File details

Details for the file misic-1.1.1-py3-none-any.whl.

File metadata

  • Download URL: misic-1.1.1-py3-none-any.whl
  • Upload date:
  • Size: 7.3 MB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.1 importlib_metadata/4.0.0 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.60.0 CPython/3.9.4

File hashes

Hashes for misic-1.1.1-py3-none-any.whl
Algorithm Hash digest
SHA256 2b6f3b964771ed85ae947d1120801db2bb3d310721ad5367d2a220ab026718e3
MD5 58b3c4f5692761d56744df6fb7ca4fb5
BLAKE2b-256 6496b1b49196c81db9ccf4f6665d9cc0d03a74ce3d2930c975ab3029d3de412e

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page