From 4e638b47de6a8a39e4b5998f0457c97c1f819285 Mon Sep 17 00:00:00 2001 From: milesial Date: Thu, 19 Aug 2021 00:30:35 +0200 Subject: [PATCH] Update README Former-commit-id: 20d8d2b9446970ac74deeb7c36a65ae9e8819a29 --- README.md | 9 +++++---- 1 file changed, 5 insertions(+), 4 deletions(-) diff --git a/README.md b/README.md index 9835ffd..b8c0987 100644 --- a/README.md +++ b/README.md @@ -46,8 +46,9 @@ python train.py --amp ``` ## Description -This model was trained from scratch with 5000 images (no data augmentation) and scored a [dice coefficient](https://en.wikipedia.org/wiki/S%C3%B8rensen%E2%80%93Dice_coefficient) of 0.988423 on over 100k test images. This score could be improved with more training, data augmentation, fine-tuning, CRF post-processing, and applying more weights on the edges of the masks. +This model was trained from scratch with 5k images and scored a [Dice coefficient](https://en.wikipedia.org/wiki/S%C3%B8rensen%E2%80%93Dice_coefficient) of 0.988423 on over 100k test images. +It can be easily used for multiclass segmentation, portrait segmentation, medical segmentation, ... ## Usage @@ -56,7 +57,7 @@ This model was trained from scratch with 5000 images (no data augmentation) and ### Docker A docker image containing the code and the dependencies is available on [DockerHub](https://hub.docker.com/repository/docker/milesial/unet). -You can **download and jump in the container** with ([docker >=19.03](https://docs.docker.com/get-docker/)): +You can download and jump in the container with ([docker >=19.03](https://docs.docker.com/get-docker/)): ```console docker run -it --rm --gpus all milesial/unet @@ -88,7 +89,7 @@ optional arguments: By default, the `scale` is 0.5, so if you wish to obtain better results (but use more memory), set it to 1. -Automatic mixed precision is also available with the `--amp` flag. [Mixed precision](https://arxiv.org/abs/1710.03740) allows the model to use less memory and to be faster on recent GPUs by using FP16 arithmetic. +Automatic mixed precision is also available with the `--amp` flag. [Mixed precision](https://arxiv.org/abs/1710.03740) allows the model to use less memory and to be faster on recent GPUs by using FP16 arithmetic. Enabling AMP is recommended. ### Prediction @@ -155,7 +156,7 @@ bash scripts/download_data.sh The input images and target masks should be in the `data/imgs` and `data/masks` folders respectively. For Carvana, images are RGB and masks are black and white. -You can also use your own dataset as long as you make sure it is loaded properly in `utils/data_loading.py`. +You can use your own dataset as long as you make sure it is loaded properly in `utils/data_loading.py`. ---