This repository is the official release of the code for the following paper "FuseNet: Incorporating Depth into Semantic Segmentation via Fusion-based CNN Architecture" which is published at the 13th Asian Conference on Computer Vision (ACCV 2016).
Latte is a convolutional neural network (CNN) inference engine written in C++ and uses AVX to vectorize operations. The engine runs on Windows 10, Linux and macOS Sierra.
The objective of this project is to detect the presence of a face mask on human faces on live streaming video as well as on images and alert the authority to take action on those who'r not wearing mask.
File "extract_embeddings.py", line 31, in
embedder = cv2.dnn.readNetFromTorch(args["embedding_model"])
cv2.error: OpenCV(4.5.3) C:\Users\runneradmin\AppData\Local\Temp\pip-req-build-q3d_8t8e\opencv\modules\dnn\src\torch\THDiskFile.cpp:496: error: (-2:Unspecified error) cannot open <openface_nn4.small2.v1.t7> in mode r in function 'TH::THDiskFile_new'
demo: https://github.com/openvinotoolkit/open_model_zoo/tree/master/demos/mri_reconstruction_demo
example: openvinotoolkit/open_model_zoo#2178