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| author | StevenLiuWen <liuwen@shanghaitech.edu.cn> | 2018-03-13 03:46:45 -0400 |
|---|---|---|
| committer | GitHub <noreply@github.com> | 2018-03-13 03:46:45 -0400 |
| commit | bfee5daff018b2555c0f82270bf0468917e7c5c5 (patch) | |
| tree | 58646708cf4d87c36826223c4663903453c651c5 /README.md | |
| parent | 09316d6f2c4cc22675bb66dd5bdef7c417ccbdd4 (diff) | |
Update README.md
Diffstat (limited to 'README.md')
| -rw-r--r-- | README.md | 8 |
1 files changed, 4 insertions, 4 deletions
@@ -2,7 +2,7 @@ This repo is the official open source of [Future Frame Prediction for Anomaly Detection -- A New Baseline, CVPR 2018](https://arxiv.org/pdf/1712.09867.pdf) by Wen Liu, Weixinluo, Dongze Lian and Shenghua Gao. A **demo** is shown in *https://www.youtube.com/watch?v=M--wv-Y_h0A*. It is implemented in tensorflow. Please follow the instructions to run the code. -####1. Installation (Anaconda with python3.6 installation is recommended) +#### 1. Installation (Anaconda with python3.6 installation is recommended) * Install 3rd-package dependencies of python (listed in requirements.txt) ``` numpy==1.14.1 @@ -24,7 +24,7 @@ pip install -r requirements.txt CUDA 8.0 Cudnn 6.0 ``` -####2. Download datasets +#### 2. Download datasets cd into Data folder of project and run the shell scripts (**ped1.sh, ped2.sh, avenue.sh, shanghaitech.sh**) under the Data folder. ```shell cd Data @@ -34,7 +34,7 @@ cd Data ./shanghaitech.sh ``` -####3. Testing on saved models +#### 3. Testing on saved models * Download the trained models ```shell cd models @@ -56,7 +56,7 @@ python inference.py --dataset avenue \ ``` -####4. Training from scratch (here we use ped2 and avenue datasets for examples) +#### 4. Training from scratch (here we use ped2 and avenue datasets for examples) * Set hyper-parameters The default hyper-parameters, such as $\lambda_{init}$, $\lambda_{gd}$, $\lambda_{op}$, $\lambda_{adv}$ and the learning rate of G, as well as D, are all initialized in **training_hyper_params/hyper_params.ini**. * Running script (as ped2 or avenue for instances) and cd into **Codes** folder at first. |