This is a complete detectron2 tutorial for setting up detectron2, running it on images and videos. Detectron2 is FacebookAI's framework for object detection, instance segmentation, and keypoints detection written in PyTorch. Detectron2 makes it convenient to run pre-trained models or train the models from scratch. In this Detectron2 tutorial, pre-trained Instance Segmentation, Object detection, keypoints detection, panoptic segmentation, and LVIS segmentation models are covered.
In detectron2, MaskRCNN is used for semantic segmentation while Faster RCNN is used for object detection. You do not need to download any pre-trained model. The detectron2 takes care of it automatically.
* Code is available for our Patreon Supporters*
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► Time Stamps:
Introduction: (0:00)
Setup Detectron2: (0:25)
Object Detection: (2:45)
Instance Segmentation: (6:55)
Keypoints Detection: (8:49)
LVIS Segmentation: (9:29)
Panoptic Segmentation: (11:02)
Detectron2 on Videos: (12:41)
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► Commands:
git clone github.com/facebookresearch/d...
pip install -e .
conda install pytorch torchvision torchaudio cudatoolkit=11.0 -c pytorch
pip install opencv-python
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► Links:
github.com/facebookresearch/d...
github.com/facebookresearch/d...
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