Update app.py

app.py

@@ -13,10 +13,10 @@ import numpy as np
 
 examples = [['sample1.png'],
             ['sample2.png'],
-            ['sample3.png'],
-            ['sample4.png'],
-            ['sample5.png'],
-            ['sample6.png']]
+            ['Sample3.png'],
+            ['Sample4.png'],
+            ['Sample5.png'],
+            ['ample6.png']]
 
 
 title = "Restormer"
@@ -24,8 +24,6 @@ description = """
 Gradio demo for <b>Restormer: Efficient Transformer for High-Resolution Image Restoration</b>, CVPR 2022--ORAL. <a href='https://arxiv.org/abs/2111.09881'>[Paper]</a><a href='https://github.com/swz30/Restormer'>[Github Code]</a>\n 
 <b> Note:</b> Since this demo uses CPU, by default it will run on the downsampled version of the input image (for speedup). But if you want to perform inference on the original input, then choose the option "Full Resolution Image" from the dropdown menu. 
 """
-##With Restormer, you can perform: (1) Image Denoising, (2) Defocus Deblurring, (3)  Motion Deblurring, and (4) Image Deraining. 
-##To use it, simply upload your own image, or click one of the examples provided below.
 
 article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2111.09881'>Restormer: Efficient Transformer for High-Resolution Image Restoration </a> | <a href='https://github.com/swz30/Restormer'>Github Repo</a></p>"