GitHub - rerun-io/rerun: Visualize streams of multimodal data. Fast, easy to use, and simple to integrate. Built in Rust using egui.You signed in with another tab or window. Reload to refresh your session. You signed out in another tab or window. Reload to refresh your session. You switched accounts on another tab or window. Reload to refresh your session. Dismiss alert
GitHub - wmuron/motpy: Library for tracking-by-detection multi object tracking implemented in python
Optimal Peanut Butter and Banana Sandwiches | Ethan Rosenthal
I was personally useless for most of the Spring of 2020. There was a period of time, though, after the peak in coronavirus cases here in NYC and before the onslaught of police violence here in NYC that I managed to scrounge up the motivation to do something other than drink and maniacally refresh my Twitter feed. I set out to work on something completely meaningless. It was almost therapeutic to w
ゆゆ式Advent Calendar 2018のオープニングと、ゆゆ式のコマのデータ分析したやつ - マンダリンオレンジ in hatenablog
オープニング ご無沙汰してます、はてなダイアリーからはてなブログに引っ越してきた方の私です。今年もゆゆ式Advent Calendarの時期がやってまいりました。 ゆゆ式 Advent Calendar 2018 ゆゆ式 Advent Calendar 2018 - Adventar https://t.co/G2LbJaeHeG あどべんとだー！— 三上小又＠ゆゆ式 きららファンタジアやってるよ。 (@mikamikomata) 2018年11月2日 三上先生にも反応してもらえてやったー、の図 今年も常連の方から新規の方、文章っぽい方からイラスト・漫画を投稿してくれそうな方まで幅広く集っていただきました。ありがたいことです。 今年は連載10周年だったり、きらら展があったり、まさかの『ゆゆ式』単独での展覧会があったりとニュースも多い年だったので年表もやりたいとこですが、今年はちゃんとしたネ
PlaNet - Photo Geolocation with Convolutional Neural Networks
Is it possible to build a system to determine the location where a photo was taken using just its pixels? In general, the problem seems exceptionally difficult: it is trivial to construct situations where no location can be inferred. Yet images often contain informative cues such as landmarks, weather patterns, vegetation, road markings, and architectural details, which in combination may allow on
Google Cloud Vision API enters Beta, open to all to try! | Google Cloud Blog
Google Cloud Vision API enters Beta, open to all to try! Today, we're announcing the beta release of Google Cloud Vision API. Now anyone can submit their images to the Cloud Vision API to understand the contents of those images — from detecting everyday objects (for example, “sports car,” “sushi,” or “eagle”) to reading text within the image or identifying product logos. With the beta release of C
Cloud Vision APIの凄さを伝えるべくRasPi botとビデオを作った話
（この記事はGoogle Cloud Platform Advent Calendar 2015の12月3日分の記事です） Cloud Vision APIと私 Googleに入ってからまもなく5年、Google Cloud Platformのデベロッパーアドボケイト（エバンジェリストみたいな役割）の仕事に就いてから1年が経ちました。仕事の半分はアジア地域向けの開発者コミュニティ支援で、残り半分はGCPの新製品ローンチの支援をグローバル向けに行っています。 特にここ半年は、TensorFlowをはじめ、GCPの機械学習系プロダクトのローンチ支援にフォーカスしています。TensorFlowはその序章で、公開前からAlphaカスタマー向けのスライドを作ったり説明やデモしたりしていました。 そうしたGCPの新しい機械学習系サービスのひとつが、Cloud Vision APIです。これはGoogl
Awesome-deep-vision
Awesome-deep-vision : A curated list of deep learning resources for computer vision View on GitHub Awesome-deep-vision A curated list of deep learning resources for computer vision Download this project as a .zip file Download this project as a tar.gz file Awesome Deep Vision A curated list of deep learning resources for computer vision, inspired by awesome-php and awesome-computer-vision. Mainta
Time-lapse Mining from Internet Photos
Ricardo Martin-Brualla1 David Gallup2 Steven M. Seitz1,2 1University of Washington 2Google Inc. Overview We introduce an approach for synthesizing time-lapse videos of popular landmarks from large community photo collections. The approach is completely automated and leverages the vast quantity of photos available online. First, we cluster 86 million photos into landmarks and popular viewpoints
Programming Computer Vision with Python
PCV - an open source Python module for computer vision Download .zip Download data View on GitHub PCV is a pure Python library for computer vision based on the book "Programming Computer Vision with Python" by Jan Erik Solem. The final pre-production draft of the book (as of March 18, 2012) is available under a Creative Commons license. Note that this version does not have the final copy edits and
ImageNet Large Scale Visual Recognition Challenge
The ImageNet Large Scale Visual Recognition Challenge is a benchmark in object category classification and detection on hundreds of object categories and millions of images. The challenge has been run annually from 2010 to present, attracting participation from more than fifty institutions. This paper describes the creation of this benchmark dataset and the advances in object recognition that have
The Revolutionary Technique That Quietly Changed Machine Vision Forever
The Revolutionary Technique That Quietly Changed Machine Vision Forever Machines are now almost as good as humans at object recognition, and the turning point occurred in 2012, say computer scientists. In space exploration, there is the Google Lunar X Prize for placing a rover on the lunar surface. In medicine, there is the Qualcomm Tricorder X Prize for developing a Star Trek-like device for diag
ねこと画像処理 part 2 – 猫検出 (モデル配布) – Rest Term
ねこと画像処理。 (アイシャ – 池袋 ねころび) 前回のねこと画像処理 part 1 – 素材集めでは猫画像の集め方について整理しました。今回はその集めた猫画像を使って猫検出用の学習モデル(分類器)を作成したいと思います。それにはいろいろと準備が必要です。 モデル(分類器)の配布についてはこのエントリーの後半で説明します。 アノテーションデータの収集 学習モデルを作る前に猫のどの部分を検出するかを決める必要がありますが、今回は猫の顔(頭)部分の検出を行おうと思います。そのためのアノテーションデータ作成補助ツールを作成したのでそれを使ってひたすらデータを集めます。僕一人の作業だと限界があったのですが、クラウドソーシングによりネット上の顔も知らない有志達の協力のおかげであっという間にデータが集まりました。 アノテーションデータ作成補助ツールの作成にあたっては以下のサイトを参考にさせてもらいま
Illumination-Aware Age Progression
Interested in the tool? Enter your email here or follow Ira on twitter. We'll annouce as soon as the tool is out--we're working on it! Description | Results | Popular press | Bibtex | Contact Description We present an approach that takes a single photograph of a child as input and automatically produces a series of age-progressed outputs between 1 and 80 years of age, accounting for pose, expressi
My solution for the Galaxy Zoo challenge
The Galaxy Zoo challenge on Kaggle has just finished. The goal of the competition was to predict how Galaxy Zoo users (zooites) would classify images of galaxies from the Sloan Digital Sky Survey. I finished in 1st place and in this post I’m going to explain how my solution works. Introduction The problem Galaxy Zoo is a crowdsourcing project, where users are asked to describe the morphology of ga
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GitHub - amzn/computer-vision-basics-in-microsoft-excel: Computer Vision Basics in Microsoft Excel (using just formulas)
GitHub - cchen156/Learning-to-See-in-the-Dark: Learning to See in the Dark. CVPR 2018
https://illustration2vec.net/
動画の中の人が何をしているか分かるアルゴリズム、開発される
ccv 0.6 open sources near state-of-the-art image classifier under Creative Commons