diff --git a/README.txt b/README.txt
index 8a8d243..53841f7 100644
--- a/README.txt
+++ b/README.txt
@@ -1,19 +1,34 @@
-Made by Vita_Aeterna and Google researches. 
+!!!!  Made by Vita_Aeterna and Google researches.  !!!!
+©Used DataSet "https://www.microsoft.com/en-us/download/details.aspx?id=54765"
 
-Simple tensorflow Neural Network with Sigmoid and with Binary_Crossentropy, learning with and about accuracy and loss.
+
+
+
+Simple tensorflow Neural Network with Sigmoid and Binary_Crossentropy, learning with and about accuracy and loss.
 All of the Pictures are converted to (50,50) sized Pictures and also GrayScaled (To improve the learning process of the Neural Network).
-At first i tested multiple Versions of The Neural Network, The one with the best Accuracy and smallest Loss is used to predict the Animals.
+At first i tested multiple Versions(different Dense layers, Conv layers and Layer size) of The Neural Network, The one with the best Accuracy and smallest Loss is used to predict the Animals.
 I noticed that if u give an invalid picture like a Man or a Woman the Neural Network will always give the Ouput 0!
 
 
 
 
+
 As Input a Picture of a Dog or a Cat is given (Need to change Name of your Picture in "EndProduct" script, default Name is "dog.jpg")
 Note that the Picture has to be in png or jpg Format. 
+Path of Cat and Dog Pictures (DataSet) in "ImageUsing" need to be changed too! (DATA_DIR)
 
 As Output, 0 or 1 is given. 
+0=Dog;
+1=Cat;
 
-!0=Dog; 1=Cat!
-
-
-
+All packages (pip) used in this Project:
+  tensorflow / tensorflow-gpu
+  pickle
+  numpy
+  random 
+  os
+  matplotlib
+  tqdm
+  cv2
+  time
+