Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
---|---|---|---|---|---|---|---|---|---|---|
Mmdetection | 26,886 | 1 | 31 | 3 months ago | 52 | October 12, 2023 | 1,381 | apache-2.0 | Python | |
OpenMMLab Detection Toolbox and Benchmark | ||||||||||
Mask_rcnn | 23,745 | 5 months ago | 5 | March 05, 2019 | 1,993 | other | Python | |||
Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow | ||||||||||
Spark | 1,355 | 3 months ago | 13 | mit | Python | |||||
[ICLR'23 Spotlight🔥] The first successful BERT/MAE-style pretraining on any convolutional network; Pytorch impl. of "Designing BERT for Convolutional Networks: Sparse and Hierarchical Masked Modeling" | ||||||||||
Pixellib | 828 | 1 | 2 years ago | 22 | October 11, 2021 | 71 | mit | Python | ||
Visit PixelLib's official documentation https://pixellib.readthedocs.io/en/latest/ | ||||||||||
Entity | 596 | 5 months ago | 28 | other | Jupyter Notebook | |||||
EntitySeg Toolbox: Towards Open-World and High-Quality Image Segmentation | ||||||||||
Detectorch | 567 | 6 years ago | 10 | other | Jupyter Notebook | |||||
Detectorch - detectron for PyTorch | ||||||||||
Centermask | 449 | 4 years ago | 12 | other | Python | |||||
CenterMask : Real-Time Anchor-Free Instance Segmentation, in CVPR 2020 | ||||||||||
Tfwss | 205 | 6 years ago | 2 | mit | Jupyter Notebook | |||||
Weakly Supervised Segmentation with Tensorflow. Implements instance segmentation as described in Simple Does It: Weakly Supervised Instance and Semantic Segmentation, by Khoreva et al. (CVPR 2017). | ||||||||||
Siamese Mask Rcnn | 202 | 4 years ago | 3 | other | Jupyter Notebook | |||||
Siamese Mask R-CNN model for one-shot instance segmentation | ||||||||||
Tfvos | 150 | 5 years ago | mit | Jupyter Notebook | ||||||
Semi-Supervised Video Object Segmentation (VOS) with Tensorflow. Includes implementation of *MaskRNN: Instance Level Video Object Segmentation (NIPS 2017)* as part of the NIPS Paper Implementation Challenge. |