From de8ddb87fb5829e3f28df83baca797f51385b0de Mon Sep 17 00:00:00 2001 From: Daniel Bolya Date: Sat, 6 Apr 2019 18:35:28 -0700 Subject: [PATCH] Uploaded all the weights to Google Drive. --- README.md | 14 +++++++------- 1 file changed, 7 insertions(+), 7 deletions(-) diff --git a/README.md b/README.md index a2dde58b1..f763409b6 100644 --- a/README.md +++ b/README.md @@ -47,10 +47,10 @@ As of April 5th, 2019 here are our latest models along with their FPS on a Titan | Image Size | Backbone | FPS | mAP | Weights | |:----------:|:-------------:|:----:|:----:|----------------------------------------------------------------------------------------------------------------| -| 550 | Resnet50-FPN | 42.5 | 28.2 | [yolact_resnet50_54_800000.pth](http://vision5.idav.ucdavis.edu:6337/weights/yolact_resnet50_54_800000.pth ) | -| 550 | Darknet53-FPN | 40.0 | 28.7 | [yolact_darknet53_54_800000.pth](http://vision5.idav.ucdavis.edu:6337/weights/yolact_darknet53_54_800000.pth ) | -| 550 | Resnet101-FPN | 33.0 | 29.8 | [yolact_base_54_800000.pth](http://vision5.idav.ucdavis.edu:6337/weights/yolact_base_54_800000.pth ) | -| 700 | Resnet101-FPN | 23.6 | 31.2 | [yolact_im700_54_800000.pth](http://vision5.idav.ucdavis.edu:6337/weights/yolact_im700_54_800000.pth ) | +| 550 | Resnet50-FPN | 42.5 | 28.2 | [yolact_resnet50_54_800000.pth](https://drive.google.com/file/d/1yp7ZbbDwvMiFJEq4ptVKTYTI2VeRDXl0/view?usp=sharing) | +| 550 | Darknet53-FPN | 40.0 | 28.7 | [yolact_darknet53_54_800000.pth](https://drive.google.com/file/d/1dukLrTzZQEuhzitGkHaGjphlmRJOjVnP/view?usp=sharing) | +| 550 | Resnet101-FPN | 33.0 | 29.8 | [yolact_base_54_800000.pth](https://drive.google.com/file/d/1UYy3dMapbH1BnmtZU4WH1zbYgOzzHHf_/view?usp=sharing) | +| 700 | Resnet101-FPN | 23.6 | 31.2 | [yolact_im700_54_800000.pth](https://drive.google.com/file/d/1lE4Lz5p25teiXV-6HdTiOJSnS7u7GBzg/view?usp=sharing) | To evalute the model, put the corresponding weights file in the `./weights` directory and run one of the following commands. ## Quantitative Results on COCO @@ -107,9 +107,9 @@ python eval.py --help # Training - To train, grab an imagenet-pretrained model and put it in `./weights`. - * For Resnet101, download `resnet101_reducedfc.pth` from [here](http://vision5.idav.ucdavis.edu:6337/resnet101_reducedfc.pth). - * For Resnet50, download `resnet50-19c8e357.pth` from [here](http://vision5.idav.ucdavis.edu:6337/resnet50-19c8e357.pth). - * For Darknet53, download `darknet53.pth` from [here](http://vision5.idav.ucdavis.edu:6337/darknet53.pth). + * For Resnet101, download `resnet101_reducedfc.pth` from [here](https://drive.google.com/file/d/1tvqFPd4bJtakOlmn-uIA492g2qurRChj/view?usp=sharing). + * For Resnet50, download `resnet50-19c8e357.pth` from [here](https://drive.google.com/file/d/1Jy3yCdbatgXa5YYIdTCRrSV0S9V5g1rn/view?usp=sharing). + * For Darknet53, download `darknet53.pth` from [here](https://drive.google.com/file/d/17Y431j4sagFpSReuPNoFcj9h7azDTZFf/view?usp=sharing). - Run one of the training commands below. * Note that you can press ctrl+c while training and it will save an `*_interrupt.pth` file at the current iteration. * All weights are saved in the `./weights` directory by default with the file name `__.pth`.