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OTCamera

OTCamera is a core module of the OpenTrafficCam framework to record videos over multiple days with a custom camera system based on Raspberry Pi Zero W. In the recorded videos, one can detect and track objects (road users) using OTVision or other tools and on the resulting trajectories, one can perform traffic analysis using OTAnalytics.

Check out the documentation for detailed instructions on how to assemble and use OTCamera.

We appreciate your support in the form of both code and comments. First, please have a look at the contribute section of the OpenTrafficCam documentation.

License

This software is licensed under the GPL-3.0 License.

OpenTrafficCam's Projects

.github icon .github

Special repo to hold public GitHub organization.

anonymizer icon anonymizer

An anonymizer to obfuscate faces and license plates.

cvat icon cvat

Powerful and efficient Computer Vision Annotation Tool (CVAT)

downloads icon downloads

Files to download for installing or maintaining the OpenTrafficCam tools

earthenginetogeotiff icon earthenginetogeotiff

A simple python script to download a map from Google's Earth Engine and save as a GeoTIFF file.

otanalytics icon otanalytics

Perform traffic analysis on trajectories of road users

otcamera icon otcamera

Record videos over several days with a camera system based on Raspberry Pi Zero W

otdocs icon otdocs

Documentation for all OpenTrafficCam Modules

otgroundtruther icon otgroundtruther

Create ground truth data to validate road traffic events automatically obtained with OTAnalytics.

otlabels icon otlabels

A set of labeled images of vehicles/road users from German roads

otvideoplayer icon otvideoplayer

Tkinter and OpenCV based videoplayer that can be used as standalone application and as an embedded LabelFrame of a custom window in other OpenTrafficCam applications

otvision icon otvision

Detect and track objects (road users) in videos

pytorch icon pytorch

Tensors and Dynamic neural networks in Python with strong GPU acceleration

tph-yolov5 icon tph-yolov5

Implementation of "TPH-YOLOv5: Improved YOLOv5 Based on Transformer Prediction Head for Object Detection on Drone-Captured Scenarios"

yolov5 icon yolov5

YOLOv5 in PyTorch > ONNX > CoreML > TFLite

yolov7 icon yolov7

Implementation of paper - YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors

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