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Pre-processingīackground Matting needs a segmentation mask for the subject. This was the model used for numerical evaluation on Adobe dataset. Note: syn-comp-adobe-trainset model was trained on the training set of the Adobe dataset. Please download the pre-trained models from Google Drive and place Models/ folder inside Background-Matting/. This data was collected with a hand-held camera. Use sample_data/ folder for testing and prepare your own data based on that. (c) Target background to insert the subject (place in data/background).(b) Image of the background without the subject (use _back.png extension).(a) Image with the subject (use _img.png extension).To perform Background Matting based green-screening, you need to capture:
#Green screen background images free download code
Run the inference code on sample images Data
#Green screen background images free download install
If our code fails due to different versions, then you need to install specific CUDA, PyTorch and Tensorflow versions. If you already have a working environment with PyTorch and Tensorflow, only install dependencies with pip install -r requirements.txt. Note: The code is likely to work on other PyTorch and Tensorflow versions compatible with your system CUDA. (Output will be of same resolution and aspect-ratio as input)Ĭonda install pytorch=1.1.0 torchvision cudatoolkit=10.0 -c pytorch Incorporating 'uncropping' operation in test_background-matting_image.py.
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Ira Kemelmacher-Shlizerman, University of WashingtonĪcknowledgement: Andrey Ryabtsev, University of Washington License.Brian Curless, University of Washington.Vivek Jayaram, University of Washington.Soumyadip Sengupta, University of Washington.You can now use this with Zoom! Much better quality! We tried this on a Linux machine with a GPU. We recently released a brand new background matting project: better quality and REAL-TIME performance (30fps at 4K and 60fps at FHD)! Paper (Arxiv) Blog Post Background Matting v2.0 Go to Project page for additional details and results. This paper will be presented in IEEE CVPR 2020. Background Matting: The World is Your Green Screenīy Soumyadip Sengupta, Vivek Jayaram, Brian Curless, Steve Seitz, and Ira Kemelmacher-Shlizerman