Detectron2 Install and Run on your Machine

Posted By :Saharsh Gaurav |2nd January 2020

Detectron2: Installation and Implementation on your machine

This blog is a guide to install Detectron2 and how to run it on your machine.

We assume here that Python is already installed on your machine.

Process of installing Detectron2

Step 1: Clone the following git repository on your machine.

git clone git://github.com/jagin/detectron2-pipeline.git
cd detectron2-pipeline

 Step 2: Create and activate the environment with conda.

$ conda env create -f environment.yml
$ conda activate detectron2-pipeline

Step 3: Next, we need to clone and install Detectron2 itself

git clone https://github.com/facebookresearch/detectron2.git
cd detectron2

Step 4: Build and Install detectron2

python setup.py build develop

 Step 5: Back to detectron2-pipeline directory.

cd ..
cd detectron2-pipeline

If you are using macOS x then...

MACOSX_DEPLOYMENT_TARGET=10.9 CC=clang CXX=clang++ python setup.py build develop

Now Detectron2 is installed in your python detectron2-pipeline enviroment.

How to Run Detectron2

To run detectron2 on images use...

python process_images.py -i /home/task/detectron2-pipeline/assets/images/others/ -p

For more options of process_images.py use... 

python process_images.py -h

To use other config/models of the detectron2 use...

python process_images.py -i /home/task/detectron2-pipeline/assets/images/others/couple.jpg -p --config-file configs/COCO-Keypoints/keypoint_rcnn_R_50_FPN_3x.yaml

Note: You can always supply other config/models to the process_images.py to change the identification process. All the model can be found in config directory

To process Video by using Detectron2 use...

python process_video.py -i /home/task/detectron2-pipeline/assets/videos/walk.small.mp4 -p -d -ov walk.avi

To know more options of process_video.py use...

python process_video.py -h

To process video using other config/models use...

python process_video.py -i /home/task/detectron2-pipeline/assets/videoss/traffic.small.mp4 -p -d -ov traffic.avi --config-file configs/COCO-PanopticSegmentation/panoptic_fpn_R_50_3x.yaml

Note: You can always supply other config/models to the process_video.py to change the identification process. All the model can be found in config directory

To process live video using your webcam use...

python process_video.py -i 0 -d -p

That's all in this blog about Installing and Running the "Detectron2: A state-of-the-art computer-vision Application"


About Author

Saharsh Gaurav

Saharsh is a quick & smart learner, problem-solver, and smart-working Python Developer. He has good knowledge about Python, Flask Framework, Machine Learning, Artificial Intelligence, Model Training and Prediction, REST Web API. He likes playing Chess.

Request For Proposal

Sending message..

Ready to innovate ? Let's get in touch


Notice: Undefined index: HTTP_REFERER in /var/html/www/AI/wp-content/themes/oxides-child/functions.php on line 272

Notice: Undefined index: HTTP_REFERER in /var/html/www/AI/wp-content/themes/oxides-child/functions.php on line 272

Notice: Undefined index: HTTP_REFERER in /var/html/www/AI/wp-content/themes/oxides-child/functions.php on line 272

Notice: Undefined index: HTTP_REFERER in /var/html/www/AI/wp-content/themes/oxides-child/functions.php on line 272

Chat With Us