From 19d23b63ee0c95cc0c4803a404cbf8edd0b915e9 Mon Sep 17 00:00:00 2001 From: Glenn Jocher Date: Sat, 1 Sep 2018 18:47:24 +0200 Subject: [PATCH] updates --- README.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index 04348198..150fe00a 100755 --- a/README.md +++ b/README.md @@ -19,9 +19,9 @@ Python 3.6 or later with the following `pip3 install -U -r requirements.txt` pac # Training -***Start Training:*** Run `train.py` to begin training after downloading COCO data with `data/get_coco_dataset.sh` and specifying COCO path on line 37 (local) or line 39 (cloud). +**Start Training:** Run `train.py` to begin training after downloading COCO data with `data/get_coco_dataset.sh` and specifying COCO path on line 37 (local) or line 39 (cloud). -***Resume Training:*** Run `train.py -resume 1` to resume training from the most recently saved checkpoint `checkpoints/latest.pt`. +**Resume Training:** Run `train.py -resume 1` to resume training from the most recently saved checkpoint `checkpoints/latest.pt`. Each epoch trains on 120,000 images from the train and validate COCO sets, and tests on 5000 images from the COCO validate set. An Nvidia GTX 1080 Ti will process ~10 epochs/day with full augmentation, or ~15 epochs/day without input image augmentation. Loss plots for the bounding boxes, objectness and class confidence should appear similar to results shown here (results in progress to 160 epochs, will update).