From b4d0cb3ac2e3cc1e2bd5b027caf33e043bb5e291 Mon Sep 17 00:00:00 2001 From: Maneesh Date: Tue, 9 Apr 2024 17:21:40 -0400 Subject: [PATCH] added license and cleaned --- README.md | 22 ++++------------------ 1 file changed, 4 insertions(+), 18 deletions(-) diff --git a/README.md b/README.md index df713a3..ca446d5 100644 --- a/README.md +++ b/README.md @@ -2,9 +2,7 @@ PyAFAR is a Python-based, open-source facial action unit detection library for use with adults and infants. For an introduction to PyAFAR and understanding the Facial Affect Coding System (FACS), visit our [website](https://affectanalysisgroup.github.io/PyAFAR/). -## Requirements - -PyAFAR comes as an executable file for Windows, Linux (Ubuntu), and Mac platforms. It can be used as an out-of-the-box software with no additional dependency requirements. +PyAFAR comes as an executable file for Windows, Linux (Ubuntu), and Mac platforms. It can be used as an out-of-the-box software with no additional proprietary dependency requirements. PyAFAR GPU capabilities work only on Linux or WSL2. @@ -17,15 +15,7 @@ PyAFAR GPU capabilities work only on Linux or WSL2. - `AU predictions`: Normalized faces are used for AU predictions (occurrence and intensity). Separate detection modules for occurrence are available for adults and infants. Intensity predictions are available for adults only. - `Output`: PyAFAR can output frame-level predictions in CSV and JSON formats to enable easy reading with most platforms used by both computational as well as domain experts. -## How to run - -A step-by-step instruction guide with screenshots on how to run PyAFAR can be found [here](./resources/readme/instructions.md). - -Ensure the executable file (.exe file in windows) and the downloaded models folder are in the same directory for the package to run. - -## Output format - -A complete description of each variable in the output can be found [here](./resources/readme/output_format.md). +See the [wiki](https://github.com/AffectAnalysisGroup/PyAFAR/wiki) for information on how to install and use PyAFAR. ## Citations @@ -67,12 +57,8 @@ PyAFAR is a result of the following publications. If you use PyAFAR in your work ## License -Copyright (c) 2024 AffectAnalysisGroup +Copyright (c) 2024 AffectAnalysisGroup. AFAR is freely available for free non-commercial use, and may be redistributed under these conditions. Interested in a commercial license? Please contact Jeffrey Cohn. -Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: - -The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. - -THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. +See complete license information [here](https://github.com/AffectAnalysisGroup/PyAFAR/blob/main/LICENSE).