From ae9fb2abbd8e2b7e079b56bf1cf39754d7c091ac Mon Sep 17 00:00:00 2001
From: Nadeen Udantha <udanthan@gmail.com>
Date: Fri, 18 May 2018 08:49:19 +0000
Subject: [PATCH] ojbects -> objects
---
README.md | 4 ++--
1 files changed, 2 insertions(+), 2 deletions(-)
diff --git a/README.md b/README.md
index 0dc6230..352edf5 100644
--- a/README.md
+++ b/README.md
@@ -99,7 +99,7 @@
* 186 MB Yolo9000 - image: `darknet.exe detector test cfg/combine9k.data yolo9000.cfg yolo9000.weights`
* Remeber to put data/9k.tree and data/coco9k.map under the same folder of your app if you use the cpp api to build an app
* To process a list of images `data/train.txt` and save results of detection to `result.txt` use:
- `darknet.exe detector test data/voc.data yolo-voc.cfg yolo-voc.weights -dont_show < data/train.txt > result.txt`
+ `darknet.exe detector test data/voc.data yolo-voc.cfg yolo-voc.weights -dont_show -ext_output < data/train.txt > result.txt`
You can comment this line so that each image does not require pressing the button ESC: https://github.com/AlexeyAB/darknet/blob/6ccb41808caf753feea58ca9df79d6367dedc434/src/detector.c#L509
##### For using network video-camera mjpeg-stream with any Android smartphone:
@@ -349,7 +349,7 @@
2. Once training is stopped, you should take some of last `.weights`-files from `darknet\build\darknet\x64\backup` and choose the best of them:
-For example, you stopped training after 9000 iterations, but the best result can give one of previous weights (7000, 8000, 9000). It can happen due to overfitting. **Overfitting** - is case when you can detect objects on images from training-dataset, but can't detect ojbects on any others images. You should get weights from **Early Stopping Point**:
+For example, you stopped training after 9000 iterations, but the best result can give one of previous weights (7000, 8000, 9000). It can happen due to overfitting. **Overfitting** - is case when you can detect objects on images from training-dataset, but can't detect objects on any others images. You should get weights from **Early Stopping Point**:
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