From 7fd095bc40df3af28e9b28b29a131595d333921c Mon Sep 17 00:00:00 2001 From: Alexey <AlexeyAB@users.noreply.github.com> Date: Fri, 10 Mar 2017 12:22:19 +0000 Subject: [PATCH] Update Readme.md - How to improve object detection --- README.md | 23 ++++++++++++++++++++--- 1 files changed, 20 insertions(+), 3 deletions(-) diff --git a/README.md b/README.md index 5c29830..a63c443 100644 --- a/README.md +++ b/README.md @@ -5,9 +5,13 @@ 3. [How to train (Pascal VOC Data)](#how-to-train-pascal-voc-data) 4. [How to train (to detect your custom objects)](#how-to-train-to-detect-your-custom-objects) 5. [When should I stop training](#when-should-i-stop-training) -6. [How to mark bounded boxes of objects and create annotation files](#how-to-mark-bounded-boxes-of-objects-and-create-annotation-files) +6. [How to improve object detection](#how-to-improve-object-detection) +7. [How to mark bounded boxes of objects and create annotation files](#how-to-mark-bounded-boxes-of-objects-and-create-annotation-files) -|  |  https://arxiv.org/abs/1612.08242 | +|  |  https://arxiv.org/abs/1612.08242 | +|---|---| + +|  |  https://arxiv.org/abs/1612.08242 | |---|---| @@ -264,7 +268,9 @@  - If training is stopped after 9000 iterations, to validate some of previous weights use this commands: + 2.1. At first, you should put filenames of validation images to file `data\voc.2007.test` (format as in `train.txt`) or if you haven't validation images - simply copy `data\train.txt` to `data\voc.2007.test`. + + 2.2 If training is stopped after 9000 iterations, to validate some of previous weights use this commands: * `darknet.exe detector recall data/obj.data yolo-obj.cfg backup\yolo-obj_7000.weights` * `darknet.exe detector recall data/obj.data yolo-obj.cfg backup\yolo-obj_8000.weights` @@ -289,6 +295,17 @@ |  |  | |---|---| +## How to improve object detection: + +1. Before training: + * set flag `random=1` in your `.cfg`-file - it will increase precision by training Yolo for different resolutions: [link](https://github.com/AlexeyAB/darknet/blob/47409529d0eb935fa7bafbe2b3484431117269f5/cfg/yolo-voc.cfg#L244) + +2. After training - for detection: + + * Increase network-resolution by set in your `.cfg`-file (`height=608` and `width=608`) or (`height=832` and `width=832`) or (any value multiple of 32): [link](https://github.com/AlexeyAB/darknet/blob/47409529d0eb935fa7bafbe2b3484431117269f5/cfg/yolo-voc.cfg#L4) + * you do not need to train the network again, just use `.weights`-file already trained for 416x416 resolution + * if error `Out of memory` occurs then in `.cfg`-file you should increase `subdivisions=16`, 32 or 64: [link](https://github.com/AlexeyAB/darknet/blob/47409529d0eb935fa7bafbe2b3484431117269f5/cfg/yolo-voc.cfg#L3) + ## How to mark bounded boxes of objects and create annotation files: Here you can find repository with GUI-software for marking bounded boxes of objects and generating annotation files for Yolo v2: https://github.com/AlexeyAB/Yolo_mark -- Gitblit v1.10.0