synthetic-dataset-object-detection VS sports

Compare synthetic-dataset-object-detection vs sports and see what are their differences.

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synthetic-dataset-object-detection sports
1 2
20 438
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2.6 5.9
over 2 years ago 5 months ago
Jupyter Notebook Jupyter Notebook
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The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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.

synthetic-dataset-object-detection

Posts with mentions or reviews of synthetic-dataset-object-detection. We have used some of these posts to build our list of alternatives and similar projects.

sports

Posts with mentions or reviews of sports. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-02-21.

What are some alternatives?

When comparing synthetic-dataset-object-detection and sports you can also consider the following projects:

TrainYourOwnYOLO - Train a state-of-the-art yolov3 object detector from scratch!

uav-detection - Drone / Unmanned Aerial Vehicle (UAV) Detection is a very safety critical project. It takes in Infrared (IR) video streams and detects drones in it with high accuracy.

computervision-recipes - Best Practices, code samples, and documentation for Computer Vision.

fasterrcnn-pytorch-training-pipeline - PyTorch Faster R-CNN Object Detection on Custom Dataset

SynthDet - SynthDet - An end-to-end object detection pipeline using synthetic data

MMM-MyScoreboard - Module for MagicMirror to display today's scores for your favourite teams across multiple sports.

auto_annotate - Labeling is boring. Use this tool to speed up your next object detection project!

supervision - We write your reusable computer vision tools. 💜

notebooks - Examples and tutorials on using SOTA computer vision models and techniques. Learn everything from old-school ResNet, through YOLO and object-detection transformers like DETR, to the latest models like Grounding DINO and SAM.