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"fork" from yolov5 with the possibility of running inferences on RGBD(C) images, work in progress. This repo is not a fork of the original repo bcs i already have 1 fork with a PR pending, this is still messy code and a work in progress

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jere357/yolov5-RGBD

i talk about this more on my website

work in progress - adapting the yolov5 v6.0 to work for multi channel inputs :) I am interested in experimenting with a novel approach to object detection. (I have been unsuccesful in finding related work regarding this theme). Rather than relying solely on RGB images, I aim to enhance the input data by adding extra channel features. By doing so, I hope to create a more nuanced and detailed representation of the images, which can potentially lead to exciting advances in computer vision research. (I may be wrong idk)

sketch

#TODO: write a better readme.md

#TODO: augmentations

#TODO: automatic mixed precision

#TODO: let's say your first layer has 32 filters and you want 22 on the RGB channels and 10 filters on the Depth channel or some stuff like that

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"fork" from yolov5 with the possibility of running inferences on RGBD(C) images, work in progress. This repo is not a fork of the original repo bcs i already have 1 fork with a PR pending, this is still messy code and a work in progress

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