Added more in-depth information

README.md

@@ -1,14 +1,111 @@
-# Vision Transformer for Face Recognition
-![python](https://img.shields.io/badge/python-3.9-brightgreen)
-![python](https://img.shields.io/badge/tensorflow-2.7-orange)
-![python](https://img.shields.io/badge/CUDA-11.2-blue)
-![python](https://img.shields.io/badge/cuDNN-8.1-blue)
+# Vision Transformers for Face Recognition
+![](https://img.shields.io/badge/python-3.9-brightgreen)
+![](https://img.shields.io/badge/tensorflow-2.7-orange)
+![](https://img.shields.io/badge/CUDA-11.2-blue)
+![](https://img.shields.io/badge/cuDNN-8.1-blue)
 
 This is the official implementation of the paper titled "Comprehensive Comparison of Vision Transformers and 
-Traditional Convolutional Neural Networks for Face Recognition Tasks"
+Traditional Convolutional Neural Networks for Face Recognition Tasks".
 
-The model weights and extensive results can be found in https://www.gti.ssr.upm.es/data
+The whole project, including model weights and extensive results can be found in
+https://www.gti.ssr.upm.es/data as a .zip file.
 
-````
+The structure of directories should look like:
+```
+Project
+|-> datasets
+    |-> LFW
+        |-> lfw
+    |-> UPM-GTI-Face
+    |-> VGG-Face2
+|-> saved_results
+    |-> Models
+        |-> ResNet_50
+        |-> VGG_16
+        |->  ViT_B32
+    |-> Tests
+        |-> LFW
+        |-> UPM-GTI-Face
+```
+
+
+
+
+
+## Pre-requisites
+1. Download the following datasets and move them to their respective directories:
+
+* [VGG-Face2](https://www.robots.ox.ac.uk/~vgg/data/vgg_face2/)
+* [Labeled Faces in the Wild (LFW)](http://vis-www.cs.umass.edu/lfw/#download)
+* [UPM-GTI-Face](https://www.gti.ssr.upm.es/data/upm-gti-face-dataset)
+
+```bash
+cd ~/Downloads/
+mv VGG-Face2/* ~/Project/datasets/VGG-Face2/
+mv lfw/* ~/Project/datasets/LFW/lfw/
+mv UPM-GTI-Face/* ~/Project/datasets/UPM-GTI-Face
+```
+
+2. Install the requirements
+```bash
+pip install -r requirements.txt
+```
+
+
+
+
+
+
+## Training
+The training of the three models can be achieved executing their respective files.
+The results of the training will be saved to ``/tmp`` directory.
+
+* ViT_B32
+```bash
 python vitb32_train.py
-````
+```
+
+* ResNet_50
+```bash
+python resnet50_train.py
+```
+
+* VGG_16
+```bash
+python vgg16_train.py
+```
+
+Any of the networks can be trained from scratch by commenting the following line in the respective training file:
+```python
+"""
+LOAD PRE-TRAINED MODEL WEIGHTS
+"""
+
+# Load pre-trained model weights before training
+best_weights = "./saved_results/Models/ViT_B32/checkpoint"
+vit_model.load_weights(best_weights)
+```
+
+
+
+
+
+## LFW Test
+The test can be performed by executing the corresponding file. Results will be saved to
+``/saved_results/Tests/LFW``.
+
+```bash
+python lfw_test.py
+```
+
+
+
+
+
+## UPM-GTI-Face Test
+The test can be performed by executing the corresponding file. Results will be saved to
+``/saved_results/Tests/UPM-GTI-Face``.
+
+```bash
+python upm-gti-face_test.py
+```