Provides a PIL based capture interface to multi-part tiffs, allowing them to be used more easily with OpenCV. This allows you to use OpenCV’s image and video processing capabilities with tiff stacks, a video form frequently encountered in scientific video as it is lossless and supports custom metadata.
Examples
A minimal example looks like this:
import tiffcapture as tc import matplotlib.pyplot as plt tiff = tc.opentiff(filename) plt.imshow(tiff.read()[1]) plt.show() tiff.release()
More real world usage looks like this:
import tiffcapture as tc
import cv2
tiff = tc.opentiff(filename) #open img
_, first_img = tiff.retrieve()
cv2.namedWindow('video')
for img in tiff:
tempimg = cv2.absdiff(first_img, img) # bkgnd sub
_, tempimg = cv2.threshold(tempimg, 5, 255,
cv2.THRESH_BINARY) # convert to binary
cv2.imshow('video', tempimg)
cv2.waitKey(80)
cv2.destroyWindow('video')
Metadata
Release files for TiffCapture 0.1.6
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| TiffCapture-0.1.6.tar.gz | 3.9 kB | Details |
Release files / TiffCapture-0.1.6.tar.gz
| Download URL | TiffCapture-0.1.6.tar.gz |
|---|---|
| Size | 3.9 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
d7a33097536bff6ffedb1715b6a44ca78e0df5fae8535e24ddd7e918bf948425
|
|
BLAKE2b-256 checksum How to use checksums |
1bcc0ab217237c2d195a61e42635421bd8a8c83927526b950066ac4853a79f10
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |