update README

trash_recognition/trash_classification/README.md

@@ -6,7 +6,7 @@ This module is a part of a [Traffic-Sign Recognition and Classification](https:/
 
 ## Module Overview
 In this module I built and trained a neural network to classify different traffic signs using PyTorch.<br>
-In this project, I used the ([Garbage Classification Dataset](https://www.kaggle.com/asdasdasasdas/garbage-classification)).
+In this project, I used the [Garbage Classification Dataset](https://www.kaggle.com/asdasdasasdas/garbage-classification).
 
 
 ## User Guide
@@ -32,30 +32,30 @@ Run the classification program:
     ```
     python code/classification.py --image <image-name>
     ```
-    Where `<image-name>` is the name of the image (including image type).
+    Where `<image-name>` is the name of the image (including image type).<br>
     The trained model will be saved in the root directory as `/model`.
 
 3. To to use an existing model and test it on a specific image, copy the image to the root directory and run the following command from the root directory:
     ```
     python code/classification.py --image <image-name> --model <model-name>
     ```
-    Where `<model-name>` is the name of the model.
+    Where `<model-name>` is the name of the trained model.<br>
 
 
 The program output when running it on the example image:
 
 The loss plot:
-[Loss Graph](https://github.com/YaelBenShalom/Traffic-Sign-Recognition-and-Classification/tree/master/trash_recognition/trash_classification/images/Losses (100 Epochs).png)
+[Loss Graph](https://github.com/YaelBenShalom/Traffic-Sign-Recognition-and-Classification/blob/master/trash_recognition/trash_classification/images/Losses%20(100%20Epochs).png)
 
 The accuracy plot:
-[Accuracy Graph](https://github.com/YaelBenShalom/Traffic-Sign-Recognition-and-Classification/tree/master/trash_recognition/trash_classification/images/Accuracy (100 Epochs).png)
+[Accuracy Graph](https://github.com/YaelBenShalom/Traffic-Sign-Recognition-and-Classification/blob/master/trash_recognition/trash_classification/images/Accuracy%20(100%20Epochs).png)
 
 The output image (with the correct prediction):
-[Accuracy Graph](https://github.com/YaelBenShalom/Traffic-Sign-Recognition-and-Classification/tree/master/trash_recognition/trash_classification/images/Image_Classification.png)
+[Accuracy Graph](https://github.com/YaelBenShalom/Traffic-Sign-Recognition-and-Classification/blob/master/trash_recognition/trash_classification/images/Image_Classification.png)
 
 
 ## Dataset
 
 The Garbage Classification Dataset contains 6 classifications: cardboard (393), glass (491), metal (400), paper(584), plastic (472), and trash(127).
 
-The dataset can be found on [Garbage Classification](https://www.kaggle.com/asdasdasasdas/garbage-classification), or downloaded directly through [here](https://www.kaggle.com/asdasdasasdas/garbage-classification/download).
+The dataset can be found on the [Garbage Classification](https://www.kaggle.com/asdasdasasdas/garbage-classification) page on Kaggle, or downloaded directly through [here](https://www.kaggle.com/asdasdasasdas/garbage-classification/download).