From 382100307a818c72749c3b6d898ea3d98536fd9e Mon Sep 17 00:00:00 2001 From: Glenn Jocher Date: Sat, 1 Sep 2018 18:37:40 +0200 Subject: [PATCH] updates --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index 217be811..8af276ec 100755 --- a/README.md +++ b/README.md @@ -23,7 +23,7 @@ Run `train.py` to begin training after downloading COCO data with `data/get_coco 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 (in progress to 160 epochs, will update) +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). ![Alt](https://github.com/ultralytics/yolov3/blob/master/data/coco_training_loss.png "coco training loss") ## Image Augmentation