Mask_RCNN

This account was spamming Python repositories with the same type of low value obvious backdoor spam.[1] Full list of attempted pull requests (all deleted seemingly by GitHub): 1 https://www.github.com/KurtBestor/Hitomi-Downloader/pull/7638 2 https://www.github.com/home-assistant/core/pull/130423 3 https://www.github.com/celery/celery/pull/9407 4 https://www.github.com/chriskiehl/Gooey/pull/921 5 https://www.github.com/crewAIInc/crewAI/pull/1582 6 https://www.github.com/cumulo-autumn/StreamDiffusion/pull/177 7 https://www.github.com/AUTOMATIC1111/stable-diffusion-webui/pull/16646 8 https://www.github.com/Aider-AI/aider/pull/2343 9 https://www.github.com/aboul3la/Sublist3r/pull/383 10 https://www.github.com/plotly/dash/pull/3073 11 https://www.github.com/soimort/you-get/pull/3034 12 https://www.github.com/streamlink/

The study: https://www.nature.com/articles/s41559-024-02525-2 Sampaio et al., Multidimensional social influence drives leadership and composition-dependent success in octopus–fish hunting groups I was curious about the the 3D reconstruction of the scenes. > We manually tracked individuals in the videos using the software Computer Vision Annotation Tool. We annotated three frames per second, which yielded a time resolution of 0.33 s for animal movement. > We then used another software developed to incorporate the previously tracked animals in each camera in the ‘colmap’ habitat models and camera paths, ‘multiviewtracks’ or ‘mvt’ [29] > [29] Francisco, F. A., Nührenberg, P. & Jordan, A. High-resolution, non-invasive animal tracking and reconstruction of local environment in aquatic ecosystems Seems it was specifically developed to track fis

The most widely used algorithms for classical feature detection today are "whatever opencv implements" In terms of tech that's advancing at the moment? ML techniques. https://co-tracker.github.io/ if you want to track individual points, https://github.com/matterport/Mask_RCNN and its descendents if you want to detect, say, the cover of a book.

Another popular implementation of MRCNN in Kerala+Tensorflow is found here: https://github.com/matterport/Mask_RCNN. Selective search is implemented in Fast-RCNN. Faster-RCNN improves upon that and uses a Region Proposal Me to propose RoI that may contain objects which speed up training and inference time.