Skip to content

add py3 brance #18

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Open
Redoblue wants to merge 1 commit into
base: develop
Choose a base branch
from
Open

add py3 brance #18

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
2 changes: 1 addition & 1 deletion README.md
View file
Open in desktop
Original file line number Diff line number Diff line change
@@ -1,6 +1,6 @@
# Selective Search Implementation for Python

This is a simple Selective Search Implementation for Python
This is a specially modified version of Selective Search Implementation for Python3.

## Install

Expand Down
2 changes: 1 addition & 1 deletion selectivesearch/__init__.py
View file
Open in desktop
Original file line number Diff line number Diff line change
@@ -1 +1 @@
from selectivesearch import selective_search # NOQA
from .selectivesearch import selective_search
4 changes: 2 additions & 2 deletions selectivesearch/selectivesearch.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -203,7 +203,7 @@ def intersect(a, b):
return True
return False

R = regions.items()
R = list(regions.items())
neighbours = []
for cur, a in enumerate(R[:-1]):
for b in R[cur + 1:]:
Expand Down Expand Up @@ -282,7 +282,7 @@ def selective_search(
while S != {}:

# get highest similarity
i, j = sorted(S.items(), cmp=lambda a, b: cmp(a[1], b[1]))[-1][0]
i, j = sorted(S.items(), key=lambda x: x[1])[-1][0]

# merge corresponding regions
t = max(R.keys()) + 1.0
Expand Down