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A self contained example demonstrating how to use MediaPipe Object Detection with Max's jweb

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lysdexic-audio/jweb-object-detection

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jweb-object-detection

A self contained example demonstrating how to use MediaPipe Object Detection with Max's jweb connected to either a live webcamera stream or using still images.

Max example patcher screenshot

Features

This demo uses a model trained on the COCO dataset. It can identify 80 different classes of object in an image.

person bicycle car motorcycle
airplane bus train truck
boat traffic light fire hydrant stop sign
parking meter bench bird cat
dog horse sheep cow
elephant bear zebra giraffe
backpack umbrella handbag tie
suitcase frisbee skis snowboard
sports ball kite baseball bat baseball glove
skateboard surfboard tennis racket bottle
wine glass cup fork knife
spoon bowl banana apple
sandwich orange broccoli carrot
hot dog pizza donut cake
chair couch potted plant bed
dining table toilet tv laptop
mouse remote keyboard cell phone
microwave oven toaster sink
refrigerator book clock vase
scissors teddy bear hair drier toothbrush

Notes

Still images seem to work best when objects are not too far from the camera.

Resources

This example is inspired by an example by Rob Ramirez, which is in turn inspired by MediaPipe in JavaScript.

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A self contained example demonstrating how to use MediaPipe Object Detection with Max's jweb

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