YOLO

YOLO implementation from scratch for detection of rudimentary shapes

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MultiClass

Localization and classification of objects of two different shapes (Circles / Rectangle)

Detection output using trained model

Class prediction coloring - Blue : Rectangular Red : Circular

Video links : Video1 Video2

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Combined

Localization of 2 objects

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Circles

Localization of single circular object

Blocks

Localization of single rectangular object

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Notes

• For the prediction task, a probability map has not be used (as used in original paper). Instead class probabilities are predicted for every bounding box
• For multiple object detection, a 1x2 grid has been used with a single bounding box associated with each grid cell
• To simplify the learning task, input images were created in a manner that ensured that each cell always had a object in it
• Ensembling.ipynb : Code to ensemble multiple trained YOLO models. Ensemble model shown to outperform individual models
• VideoCreater.ipynb : Code for patching together multiple predicted output images