From f92b20580a21663c5db9eb8608f8cabd7adbeb10 Mon Sep 17 00:00:00 2001
From: AlexeyAB <alexeyab84@gmail.com>
Date: Mon, 13 Aug 2018 22:51:31 +0000
Subject: [PATCH] Some fixes for AVX support on CPU
---
README.md | 2 +-
1 files changed, 1 insertions(+), 1 deletions(-)
diff --git a/README.md b/README.md
index 262a253..c3b7a84 100644
--- a/README.md
+++ b/README.md
@@ -428,7 +428,7 @@
* desirable that your training dataset include images with non-labeled objects that you do not want to detect - negative samples without bounded box (empty `.txt` files) - use as many images of negative samples as there are images with objects
- * for training with a large number of objects in each image, add the parameter `max=200` or higher value in the last layer [region] in your cfg-file
+ * for training with a large number of objects in each image, add the parameter `max=200` or higher value in the last `[yolo]`-layer or `[region]`-layer in your cfg-file (the global maximum number of objects that can be detected by YoloV3 is `0,0615234375*(width*height)` where are width and height are parameters from `[net]` section in cfg-file)
* for training for small objects - set `layers = -1, 11` instead of https://github.com/AlexeyAB/darknet/blob/6390a5a2ab61a0bdf6f1a9a6b4a739c16b36e0d7/cfg/yolov3.cfg#L720
and set `stride=4` instead of https://github.com/AlexeyAB/darknet/blob/6390a5a2ab61a0bdf6f1a9a6b4a739c16b36e0d7/cfg/yolov3.cfg#L717
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