GitHub - activeloopai/deeplake: Database for AI. Store Vectors, Images, Texts, Videos, etc. Use with LLMs/LangChain. Store, query, version, & visualize any AI data. Stream data in real-time to PyTorch/TensorFlow. https://activeloop.aiYou 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
Pervasive Label Errors in Test Sets Destabilize Machine Learning Benchmarks
We identify label errors in the test sets of 10 of the most commonly-used computer vision, natural language, and audio datasets, and subsequently study the potential for these label errors to affect benchmark results. Errors in test sets are numerous and widespread: we estimate an average of at least 3.3% errors across the 10 datasets, where for example label errors comprise at least 6% of the Ima
pycocotools を使って COCO datasets を扱ってみる - パソコン関連もろもろ
はじめに 「pycocotools」がWindowsでもpipを使って簡単にインストールできるようになった。 touch-sp.hatenablog.com 今回はpycocotoolsを使ってCOCO datasets を扱ってみる。 COCO datasetsのダウンロード、解凍 まずはGluonCVのチュートリアルページから「val2017.zip」と「annotations_trainval2017.zip」をダウンロード。 「coco_data」というフォルダを作成しそちらの中にダウンロードしたZIPファイルを解凍する。 以下のような構造にする。 coco_data | +---annotations | captions_train2017.json | captions_val2017.json | instances_train2017.json | instances_v
GitHub - lemondan/HumanParsing-Dataset
This human parsing dataset includes the detailed pixel-wise annotations for fashion images, which is proposed in our TPAMI paper "Deep Human Parsing with Active Template Regression", and ICCV 2015 paper "Human Parsing with Contextualized Convolutional Neural Network". You can download the dataset from this link. http://pan.baidu.com/s/1qY8bToS passwd：kjgk We will mainly maintain a new LIP benchmar
DeepFashion Database
News 2022-06-01 We release the DeepFashion-MultiModal dataset with rich multi-modal annotations, including manually annotated human parsing labels, manually annotated human keypoints, manually annotated fine-grained labels and textual descriptions. 2020-05-04 Parsing mask annotations and dense pose annotations have been added to “In-shop Clothes Retrieval Benchmark”. Fine-grained attribute annotat
大規模画像データセット - n_hidekeyの日記
最近は画像認識・検索で用いられるデータセットも大規模化が進んでいます。 いくつか代表的なものや最近見つけたものをまとめてみます。 （ここでの目安は、教師つきデータは10万枚以上、教師なしデータは100万枚以上のもの） ImageNet http://www.image-net.org/ 自然言語処理の分野で有名なWordNetのオントロジーに従って、各単語（今のところ名詞のみ）に対応する画像を収集したものです。Amazon Mechanical Turk を利用し、質の高いデータセットを構築するように工夫されています。日々データは蓄積・更新されており、2012年1月現在、約1400万枚の画像データ（2万2千カテゴリ）が集まっているようです。 アノテーションは基本的に1画像1カテゴリで、一部の画像には物体の位置を示すbounding boxもついています。カテゴリによっては十分な数の画像がな
Introducing the Open Images Dataset
Posted by Ivan Krasin and Tom Duerig, Software Engineers In the last few years, advances in machine learning have enabled Computer Vision to progress rapidly, allowing for systems that can automatically caption images to apps that can create natural language replies in response to shared photos. Much of this progress can be attributed to publicly available image datasets, such as ImageNet and COCO
Caffe | Fine-tuning for style recognition
Fine-tuning CaffeNet for Style Recognition on “Flickr Style” Data Fine-tuning takes an already learned model, adapts the architecture, and resumes training from the already learned model weights. Let’s fine-tune the BAIR-distributed CaffeNet model on a different dataset, Flickr Style, to predict image style instead of object category. Explanation The Flickr-sourced images of the Style dataset are
Cross-Age Reference Coding for Age-Invariant Face Recognition and Retrieval
Cross-Age Reference Coding for Age-Invariant Face Recognition and Retrieval Abstract Recently, promising results have been shown on face recognition researches. However, face recognition and retrieval across age is still challenging. Unlike prior methods using complex models with strong parametric assumptions to model the aging process, we use a data-driven method to address this problem. We propo
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EPIC@ICCV2021: Ego4D Reveal Session
Egocentric 4D Perception (EGO4D)
CVPR 2019 Open Access Repository
Fashion IQ: A New Dataset Towards Retrieving Images by Natural Language Feedback
ModaNet: A Large-scale Street Fashion Dataset with Polygon Annotations
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