From 6c1cd4f3a245edf1e5afd7bdf64b2143ea269078 Mon Sep 17 00:00:00 2001 From: Glenn Jocher Date: Tue, 11 Dec 2018 20:18:05 +0100 Subject: [PATCH 1/2] Update README.md --- README.md | 8 +++----- 1 file changed, 3 insertions(+), 5 deletions(-) diff --git a/README.md b/README.md index e8f25e7e..026b1f1a 100755 --- a/README.md +++ b/README.md @@ -52,13 +52,11 @@ Run `detect.py --weights` to apply trained weights to an image, such as `zidane. ![Alt](https://github.com/ultralytics/yolov3/blob/master/data/zidane_result.jpg "inference example") -# Testing +# Validation mAP -Run `test.py` to validate the official YOLOv3 weights `checkpoints/yolov3.weights` against the 5000 validation images. You should obtain a mAP of .581 using this repo (https://github.com/ultralytics/yolov3), compared to .579 as reported in darknet (https://arxiv.org/abs/1804.02767). +Run `test.py` to validate the official YOLOv3 weights `weights/yolov3.weights` against the 5000 validation images. You should obtain a .584 mAP at `--img-size 416`, or .586 at `--img-size 608` using this repo, compared to .579 at 608 x 608 reported in darknet (https://arxiv.org/abs/1804.02767). -Run `test.py --weights weights/latest.pt` to validate against the latest training - -oint. +Run `test.py --weights weights/latest.pt` to validate against the latest training results. Default training settings produce a 0.522 mAP at epoch 62. We are currently exploring how to improve this. # Contact From cb21b7592085ee76185d3dcad10e62563e79c8af Mon Sep 17 00:00:00 2001 From: Glenn Jocher Date: Tue, 11 Dec 2018 20:23:27 +0100 Subject: [PATCH 2/2] Update README.md --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index 026b1f1a..3ed0a87b 100755 --- a/README.md +++ b/README.md @@ -45,7 +45,7 @@ HS**V** Intensity | +/- 50% # Inference -Run `detect.py --weights` to apply trained weights to an image, such as `zidane.jpg` from the `data/samples` folder, shown here. Download official YOLOv3 weights: +Run `detect.py` to apply trained weights to an image, such as `zidane.jpg` from the `data/samples` folder, shown here. Download official YOLOv3 weights: - PyTorch format: https://storage.googleapis.com/ultralytics/yolov3.pt - Darknet format: https://pjreddie.com/media/files/yolov3.weights