YoloFace50k-landmark106 Test results Reference&Framework instructions&How to Train https://github.com/AlexeyAB/darknet You must use a pre-trained model to train your own data set. You can make a pre-trained model based on the weights of COCO training in this project to initialize the networ...
Face detection: yoloface-50k Landmark: landmark106 https://github.com/AlexeyAB/darknet You must use a pre-trained model to train your own data set. You can make a pre-trained model based on the weights of COCO training in this project to initialize the network parameters ...
yoloface-50k 56x56 0.27ms 0.31ms 0.5 ms 0.001BFlops 46kb For the close-range face detection model in a specific scene, the recommended detection distance is 1.5m YoloFace-50k Test results(thresh 0.7) YoloFace50k-landmark106(Ultra lightweight 106 point face-landmark model) NetworkResolution...
YoloFace50k-landmark106(Ultra lightweight 106 point face-landmark model) NetworkResolutionInference time (NCNN/Kirin 990)Inference time (MNN arm82/Kirin 990)Weight size landmark106 112x112 0.6ms 0.5ms 1.4MB Face detection: yoloface-50k Landmark: landmark106 YoloFace50k-landmark106 Test resu...
YoloFace50k-landmark106 Test results Reference&Framework instructions&How to Train https://github.com/AlexeyAB/darknet You must use a pre-trained model to train your own data set. You can make a pre-trained model based on the weights of COCO training in this project to initialize the networ...
YoloFace50k-landmark106(Ultra lightweight 106 point face-landmark model) Face detection: yoloface-50k Landmark: landmark106 Reference&Framework instructions&How to Train https://github.com/AlexeyAB/darknet You must use a pre-trained model to train your own data set. You can make a pre-trai...
YoloFace50k-landmark106(Ultra lightweight 106 point face-landmark model) YoloFace50k-landmark106 Test results Reference&Framework instructions&How to Train About model selection NCNN conversion tutorial NCNN C++ Sample NCNN Android Sample DarkNet2Caffe tutorial ...