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This is the second version of the Google Landmarks dataset (GLDv2), which contains images annotated with labels representing human-made and natural landmarks. The dataset can be used for landmark recognition and retrieval experiments.
6 lis 2024 · Landmark Detection detects popular natural and human-made structures within an image. Note: The Vision API now supports offline asynchronous batch image annotation for all features.
6 sie 2024 · The MediaPipe Pose Landmarker task lets you detect landmarks of human bodies in an image or video. You can use this task to identify key body locations, analyze posture, and categorize movements. This task uses machine learning (ML) models that work with single images or video.
1 mar 2018 · The recognition track challenge is to build models that recognize the correct landmark in a dataset of challenging test images, while the retrieval track challenges participants to retrieve images containing the same landmark.
Perform landmark detection on a local file. Explore further. For detailed documentation that includes this code sample, see the following: Detect landmarks. Code sample. Before trying this...
We introduce the Google Landmarks Dataset v2 (GLDv2), a new benchmark for large-scale, fine-grained instance recognition and image retrieval in the domain of human-made and natural landmarks. GLDv2 is the largest such dataset to date by a large margin, including over 5M images and 200k distinct instance labels.
3 maj 2019 · In support of this goal, this year we are releasing Google-Landmarks-v2, a completely new, even larger landmark recognition dataset that includes over 5 million images (2x that of the first release) of more than 200 thousand different landmarks (an increase of 7x).
