ensemble-boxes

Python implementation of several methods for ensembling boxes from object detection models: Non-maximum Suppression (NMS), Soft-NMS, Non-maximum weighted (NMW), Weighted boxes fusion (WBF)

Project description

Python implementation of several methods for ensembling boxes from object detection models: Non-maximum Suppression (NMS), Soft-NMS, Non-maximum weighted (NMW), Weighted boxes fusion (WBF)More details: https://github.com/ZFTurbo/Weighted-Boxes-Fusion

Project details

Release history Release notifications | RSS feed

1.0.9

Apr 20, 2022

This version

1.0.8

Dec 6, 2021

1.0.7

Sep 16, 2021

1.0.6

Mar 23, 2021

1.0.4

Jun 16, 2020

1.0.3

Jun 16, 2020

1.0.2

Jun 6, 2020

1.0.1

Jun 3, 2020

1.0.0

Oct 30, 2019

Download files

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

Source Distribution

ensemble_boxes-1.0.8.tar.gz (8.7 kB view hashes)

Uploaded Dec 6, 2021 Source

Built Distribution

ensemble_boxes-1.0.8-py3-none-any.whl (21.3 kB view hashes)

Uploaded Dec 6, 2021 Python 3

Hashes for ensemble_boxes-1.0.8.tar.gz

Hashes for ensemble_boxes-1.0.8.tar.gz
Algorithm	Hash digest
SHA256	`e765ecb3f1349ade3079a872c3290828451088fe94aaf14e9432a895af8e5a8d`
MD5	`5ea551428173846a64534da3cf2b7b45`
BLAKE2b-256	`6efcc4a25f59e89745957a12d4eb4ee8ecdf815de4afb6fa9e7d947a7ee952b8`

Hashes for ensemble_boxes-1.0.8-py3-none-any.whl

Hashes for ensemble_boxes-1.0.8-py3-none-any.whl
Algorithm	Hash digest
SHA256	`56a70524c0046772ae3f4a92e8aa06ae590a0414810072fbd7f1c984c25b22be`
MD5	`223e1e77800aaffe943067134318570f`
BLAKE2b-256	`8e351fa365f6364de126ec2306f63600a6c2f5dcd0230de480a2cb9ea8e58010`