Evaluation code for machine-generated image captions in Japanese.
Project description
JaSPICE - Japanese SPICE
Evaluation code for machine-generated image captions in Japanese.
This code also implemented a scene-graph parser for Japanese.
Instructions (using Docker)
Clone & Install
git clone git@github.com:keio-smilab23/JaSPICE.git
cd JaSPICE
pip install -e .
Build
docker build -t jaspice .
Run the docker container.
docker run -d -p 2115:2115 jaspice
Usage
from jaspice.api import JaSPICE
batch_size = 16
jaspice = JaSPICE(batch_size,server_mode=True)
_, score = jaspice.compute_score(references, candidates)
Instructions (without Docker)
Clone & Install
git clone git@github.com:keio-smilab23/JaSPICE.git
cd JaSPICE
pip install -e .
Install JUMAN, JUMAN++, KNP
- juman : v7.01
- juman++ : v1.02
- knp : v4.20
# JUMAN++
wget 'http://nlp.ist.i.kyoto-u.ac.jp/DLcounter/lime.cgi?down=http://lotus.kuee.kyoto-u.ac.jp/nl-resource/jumanpp/jumanpp-1.02.tar.xz&name=jumanpp-1.02.tar.xz'
# JUMAN
wget 'http://nlp.ist.i.kyoto-u.ac.jp/nl-resource/juman/juman-7.01.tar.bz2' -O /tmp/juman.tar.bz2
# KNP
wget 'https://nlp.ist.i.kyoto-u.ac.jp/DLcounter/lime.cgi?down=https://nlp.ist.i.kyoto-u.ac.jp/nl-resource/knp/knp-4.20.tar.bz2&name=knp-4.20.tar.bz2'
Usage
from jaspice.api import JaSPICE
batch_size = 16
jaspice = JaSPICE(batch_size,server_mode=False)
_, score = jaspice.compute_score(references, candidates)
Scene Graph Example
- 「人通りの少なくなった道路で青いズボンを着た男の子がオレンジ色のヘルメットを被りスケートボードに乗っている.」
BibTex
@InProceedings{jaspice,
title = {JaSPICE: 日本語における述語項構造に基づく画像キャプション生成モデルの自動評価尺度},
author = {和田唯我 and 兼田寛大 and 杉浦孔明},
year = {2023},
booktitle = {言語処理学会第29回年次大会}
}
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
jaspice-0.0.1.tar.gz
(16.9 kB
view details)
File details
Details for the file jaspice-0.0.1.tar.gz
.
File metadata
- Download URL: jaspice-0.0.1.tar.gz
- Upload date:
- Size: 16.9 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.2 CPython/3.8.10
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 5b39fdf864fcac66d1c8aa69e906de4a8ccd429fb353d797074b13e149207ec9 |
|
MD5 | 6b7f5b1baaa811bda6e4ae26bae72949 |
|
BLAKE2b-256 | 71ecb6fad376ada784849ad05286a668f8627d220c455d875a8bf337f5443675 |