| 更新: | 2018-08-20 |
|---|---|
| 作者: | @voluntas |
| バージョン: | 18.8.3 |
| URL: | https://voluntas.github.io/ |
Yutaro Ikeda ikedaosushi
ksasao
/ detect_marker.py
Last active
December 10, 2023 02:38
ZOZOSUITのマーカーのIDを読み取るコードです。公開されている画像を元に独自に解析しているので、公式ではこのように処理しているかどうかは不明です。仕様等については https://twitter.com/ksasao/status/990779583682170881 のスレッドも参照してください。全身を読み取るコード https://twitter.com/ksasao/status/989842844243279872 ライセンスは Apache License 2.0 です。
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| import numpy as np | |
| import random | |
| import math | |
| import cv2 | |
| from PIL import Image | |
| import sys | |
| def detect_markers(im): | |
| markers = [] | |
| # 輪郭線抽出のための二値化 |
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| # -*- coding: utf-8 -*- | |
| """ | |
| Created on Mon Sep 23 23:16:44 2017 | |
| @author: Marios Michailidis | |
| This is an example that performs stacking to improve mean squared error | |
| This examples uses 2 bases learners (a linear regression and a random forest) | |
| and linear regression (again) as a meta learner to achieve the best score. | |
| The initial train data are split in 2 halves to commence the stacking. |
| 更新: | 2017-09-26 |
|---|---|
| 作者: | @voluntas |
| 作者サイト: | http://voluntas.github.io/ |
| バージョン: | 1.2.1 |
| セッション日時: | 2017-09-24 14:20 - 15:00 |
| セッション場所: | 5号館3F |