From d696753538fd378ce8fc1f90d359fa2fc44d3e5e Mon Sep 17 00:00:00 2001
From: Nataniel Ruiz <nruiz9@gatech.edu>
Date: 星期三, 29 十一月 2017 13:56:50 +0800
Subject: [PATCH] Update README.md

---
 README.md |    4 ++--
 1 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/README.md b/README.md
index f2c8e22..42bf9e8 100644
--- a/README.md
+++ b/README.md
@@ -8,11 +8,11 @@
 
 To use please install [PyTorch](http://pytorch.org/) and [OpenCV](https://opencv.org/) (for video) - I believe that's all you need apart from usual libraries such as numpy. You need a GPU to run Hopenet (for now).
 
-To test on a video using dlib face detections (center of face will be jumpy):
+To test on a video using dlib face detections (center of head will be jumpy):
 ```bash
 python code/test_on_video_dlib.py --snapshot PATH_OF_SNAPSHOT --face_model PATH_OF_DLIB_MODEL --video PATH_OF_VIDEO --output_string STRING_TO_APPEND_TO_OUTPUT --n_frames N_OF_FRAMES_TO_PROCESS --fps FPS_OF_SOURCE_VIDEO
 ```
-To test on a video using your own face detections (we recommend using [dockerface](https://github.com/natanielruiz/dockerface)):
+To test on a video using your own face detections (we recommend using [dockerface](https://github.com/natanielruiz/dockerface), center of head will be very smooth):
 ```bash
 python code/test_on_video_dockerface.py --snapshot PATH_OF_SNAPSHOT --video PATH_OF_VIDEO --bboxes FACE_BOUNDING_BOX_ANNOTATIONS --output_string STRING_TO_APPEND_TO_OUTPUT --n_frames N_OF_FRAMES_TO_PROCESS --fps FPS_OF_SOURCE_VIDEO
 ```

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