py-motmetrics
UNINEXT
py-motmetrics | UNINEXT | |
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1 | 2 | |
1,326 | 1,443 | |
- | - | |
4.4 | 5.5 | |
17 days ago | 10 months ago | |
Python | Python | |
MIT License | MIT License |
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py-motmetrics
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HOW to find MOTA and MOTP for MOT evaluation metrics?
I think this repo is a great starting point for your question: https://github.com/cheind/py-motmetrics
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.
What are some alternatives?
multi-object-tracker - Multi-object trackers in Python
VolleyVision - Applying Deep Learning Approaches to Volleyball Data
ailia-models - The collection of pre-trained, state-of-the-art AI models for ailia SDK
Yolo_mark - GUI for marking bounded boxes of objects in images for training neural network Yolo v3 and v2
norfair - Lightweight Python library for adding real-time multi-object tracking to any detector.
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
yolov4-deepsort - Object tracking implemented with YOLOv4, DeepSort, and TensorFlow.
unimatch - [TPAMI'23] Unifying Flow, Stereo and Depth Estimation
classy-sort-yolov5 - Ready-to-use realtime multi-object tracker that works for any object category. YOLOv5 + SORT implementation.
VNext - Next-generation Video instance recognition framework on top of Detectron2 which supports InstMove (CVPR 2023), SeqFormer(ECCV Oral), and IDOL(ECCV Oral))