mmtracking
mmsegmentation
| mmtracking | mmsegmentation | |
|---|---|---|
| 7 | 7 | |
| 3,382 | 7,414 | |
| 1.6% | 1.8% | |
| 1.5 | 8.2 | |
| 8 months ago | 8 days ago | |
| Python | Python | |
| Apache License 2.0 | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
mmtracking
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Tracking sets of Keypoints by Person
I suggest to try the top down approach with the https://openmmlab.com/ open source package. The openmmlab provides multiple algorithms, datasets and pretrained models for various computer vision tasks. Start with mmpose video demo that integrates detection and pose estimation. You can add later tracking with https://github.com/open-mmlab/mmtracking to track the poses in time.
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MMDeploy: Deploy All the Algorithms of OpenMMLab
MMTracking: OpenMMLab video perception toolbox and benchmark.
- [P]We have supported Quasi-Dense Similarity Learning for Multiple Object Tracking.
- [p]We have supported Quasi-Dense Similarity Learning for Multiple Object Tracking
- MMTracking have supported Quasi-Dense Similarity Learning for Multiple Object Tracking.
- MMTracking Supports Quasi-Dense Similarity Learning for Multiple Object Tracking
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Help combining custom detector (yolo) with a tracker.
Implementations exist, like https://github.com/open-mmlab/mmtracking
mmsegmentation
- [D] The MMSegmentation library from OpenMMLab appears to return the wrong results when computing basic image segmentation metrics such as the Jaccard index (IoU - intersection-over-union). It appears to compute recall (sensitivity) instead of IoU, which artificially inflates the performance metrics.
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Is there any ML model out there for room surfaces detection? (ceiling, floor, windows)
Segmentation models trained on datasets like ADE20k could probably be used for that, because it has separate classes for these things iirc. https://github.com/open-mmlab/mmsegmentation should have suitable pretrained models available.
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MMDeploy: Deploy All the Algorithms of OpenMMLab
MMSegmentation: OpenMMLab semantic segmentation toolbox and benchmark.
- Mmsegmentation - Openmmlab semantic segmentation toolbox and benchmark.
- Mmsegmentation – Openmmlab semantic segmentation toolbox and benchmark
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Semantic Segmentation models
This repo is amazing: https://github.com/open-mmlab/mmsegmentation
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What's A Simple Custom Segmentation Pipeline?
Mmsegmentation would be a good place to start for basic segmentation. They have lots of recent methods and pretained models you could fine-tune from. They also support quite a few datasets including VOC. There is a custom dataset format which looks straightforward to create.
What are some alternatives?
ByteTrack - [ECCV 2022] ByteTrack: Multi-Object Tracking by Associating Every Detection Box
Pytorch-UNet - PyTorch implementation of the U-Net for image semantic segmentation with high quality images
FastMOT - High-performance multiple object tracking based on YOLO, Deep SORT, and KLT 🚀
Swin-Transformer-Semantic-Segmentation - This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows" on Semantic Segmentation.
PaddleDetection - Object Detection toolkit based on PaddlePaddle. It supports object detection, instance segmentation, multiple object tracking and real-time multi-person keypoint detection.
segmentation_models.pytorch - Segmentation models with pretrained backbones. PyTorch.
norfair - Lightweight Python library for adding real-time multi-object tracking to any detector.
Mask_RCNN - Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow
Yolov7_StrongSORT_OSNet - Real-time multi-camera multi-object tracker using YOLOv7 and StrongSORT with OSNet
face-parsing.PyTorch - Using modified BiSeNet for face parsing in PyTorch
mmyolo - OpenMMLab YOLO series toolbox and benchmark. Implemented RTMDet, RTMDet-Rotated,YOLOv5, YOLOv6, YOLOv7, YOLOv8,YOLOX, PPYOLOE, etc.
PaddleSeg - Easy-to-use image segmentation library with awesome pre-trained model zoo, supporting wide-range of practical tasks in Semantic Segmentation, Interactive Segmentation, Panoptic Segmentation, Image Matting, 3D Segmentation, etc.