examples
multi-object-tracking-in-python
| examples | multi-object-tracking-in-python | |
|---|---|---|
| 1 | 2 | |
| 66 | 201 | |
| - | - | |
| 9.1 | 3.5 | |
| 3 days ago | 6 months ago | |
| Jupyter Notebook | Jupyter Notebook | |
| MIT License | 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.
examples
multi-object-tracking-in-python
What are some alternatives?
kfserving - Standardized Serverless ML Inference Platform on Kubernetes [Moved to: https://github.com/kserve/kserve]
FOXTracker - Facial Head Pose Tracker for Gaming
Traffic-Lights-Classification-CNN - Coding and testing a convolutional neural network for classifying traffic lights, with Keras and Tensorflow, using LISA dataset.
whotracks.me - Data from the largest and longest measurement of online tracking.
ee_repository_stats - Scraping, parsing, and analyzing every public Earth Engine repository
Deepstream - yolov5, yolov8, segmenations, face, pose, keypoints on deepstream
ststats - UK Specialty Training Stats
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.
Ordinal_Classifier - Introduce order in your classification within 1 line
TrackerComponentLibrary - This is a collection of Matlab functions that are useful in the development of target tracking algorithms.
quick-deploy - Optimize, convert and deploy machine learning models as fast inference API using Triton and ORT. Currently support Hugging Face transformers, PyToch, Tensorflow, SKLearn and XGBoost models.
SipMask - SipMask: Spatial Information Preservation for Fast Image and Video Instance Segmentation (ECCV2020)