synthetic-dataset-object-detection VS SynthDet

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

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synthetic-dataset-object-detection SynthDet
1 3
20 350
- 0.9%
2.6 2.9
over 2 years ago 10 months ago
Jupyter Notebook C#
- Apache License 2.0
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.

SynthDet

Posts with mentions or reviews of SynthDet. We have used some of these posts to build our list of alternatives and similar projects.

What are some alternatives?

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

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

AI-basketball-analysis - :basketball::robot::basketball: AI web app and API to analyze basketball shots and shooting pose.

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

Deep-Learning-Push-Up-Counter - Deep Learning approach to count the number of repetitions in a video of push ups or pull ups.

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

yolov3-tf2 - YoloV3 Implemented in Tensorflow 2.0

sports - Cool experiments at the intersection of Computer Vision and Sports ⚽🏃

machine-learning-for-trading - Code for Machine Learning for Algorithmic Trading, 2nd edition.

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.

Real-time-Object-Detection-for-Autonomous-Driving-using-Deep-Learning - My Computer Vision project from my Computer Vision Course (Fall 2020) at Goethe University Frankfurt, Germany. Performance comparison between state-of-the-art Object Detection algorithms YOLO and Faster R-CNN based on the Berkeley DeepDrive (BDD100K) Dataset.

make-sense - Free to use online tool for labelling photos. https://makesense.ai

Mask-RCNN-Implementation - Mask RCNN Implementation on Custom Data(Labelme)