UNINEXT
norfair
| UNINEXT | norfair | |
|---|---|---|
| 2 | 4 | |
| 1,443 | 2,290 | |
| - | 0.8% | |
| 5.5 | 7.0 | |
| 10 months ago | 22 days ago | |
| Python | Python | |
| MIT License | BSD 3-clause "New" or "Revised" License |
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UNINEXT
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[R] Universal Instance Perception as Object Discovery and Retrieval (Video Demo)
Hi, we have uploaded the complete paper (https://github.com/MasterBin-IIAU/UNINEXT/blob/master/assets/UNINEXT_Paper.pdf) to our repo. You can find more details in the paper :) About the first question, the input videos are NOT segmented aforehand and all target masks are predicted by our UNINEXT model. For SOT and VOS, we use target annotations (box or mask) from the first frame as the prompts. This helps UNINEXT to segment corresponding targets in the following frames.
norfair
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Seeking Efficient Video Object Tracking and or Video Segmentation Software for Research
If you're familiar with Python you can try using Norfair. It's a lightweight Python library for adding real-time multi-object tracking to any detector. There are lots of examples for you to try, they mostly differ on the object detector.
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Help combining custom detector (yolo) with a tracker.
Yyou can use norfair: https://github.com/tryolabs/norfair
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Empresa uruguaya que SI recomendarías
Tryolabs
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Tracker on top of YOLO algorithm?
Depending on your task normal SORT would work as well (No retraining required, just some Kallman filter and some other techniques). The library https://github.com/tryolabs/norfair has implemented SORT and can be extended with DeepSORT if you want.
What are some alternatives?
VolleyVision - Applying Deep Learning Approaches to Volleyball Data
multi-object-tracker - Multi-object trackers in Python
ailia-models - The collection of pre-trained, state-of-the-art AI models for ailia SDK
yolov4-deepsort - Object tracking implemented with YOLOv4, DeepSort, and TensorFlow.
py-motmetrics - :bar_chart: Benchmark multiple object trackers (MOT) in Python
zero-shot-object-tracking - Object tracking implemented with the Roboflow Inference API, DeepSort, and OpenAI CLIP.
TagMaps - Spatio-Temporal Tag and Photo Location Clustering for generating Tag Maps
mmtracking - OpenMMLab Video Perception Toolbox. It supports Video Object Detection (VID), Multiple Object Tracking (MOT), Single Object Tracking (SOT), Video Instance Segmentation (VIS) with a unified framework.
unimatch - [TPAMI'23] Unifying Flow, Stereo and Depth Estimation
kalmanpy - Implementation of Kalman Filter in Python
VNext - Next-generation Video instance recognition framework on top of Detectron2 which supports InstMove (CVPR 2023), SeqFormer(ECCV Oral), and IDOL(ECCV Oral))
Deep-SORT-YOLOv4 - People detection and optional tracking with Tensorflow backend.