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pose
README.MD
get_model.sh
run_pose.py
sample.jpg
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README.MD

Code for running OpenPose code for human pose estimation using deep learning in OpenCV.

First step is download the pretrained models:

On Ubuntu/Mac, run this command to download the models.

sh get_models.sh

Now, we can just run these models using the commands below. There are three pretrained models available each trained on a different dataset. In the blog, we have only shown MPI but you can run the other two as well.

To Run MPI pretrained model on an image sample.jpg: python3 run_pose.py --input sample.jpg --proto pose/mpi/pose_deploy_linevec_faster_4_stages.prototxt --model pose/mpi/pose_iter_160000.caffemodel --dataset MPI

To Run Body_25 pretrained model on an image sample.jpg: python3 run_pose.py --input sample.jpg --proto pose/body_25/body_25_deploy.prototxt --model pose/body_25/pose_iter_584000.caffemodel

To Run COCO pretrained model on an image sample.jpg: python3 run_pose.py --input sample.jpg --proto pose/coco/deploy_coco.prototxt --model pose/coco/pose_iter_440000.caffemodel --dataset COCO

The output results are shown in a new image result_sample.jpg saved on your hard disk.

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