Update README.md

README.md

@@ -9,36 +9,41 @@ size_categories:
 # DF2K_BHI SISR Dataset
 
 This is a filtered version of the DF2K dataset, specifically aimed for single image super-resolution model training.  
-It is a result, or is one of the testing sets, for [my huggingface community blog post on my BHI-Filtering method](https://huggingface.co/blog/Phips/bhi-filtering).
-
-[TODO CHECK IF THIS IS IC>=0.4 or IC>= 0.5; it is 6'620 tiles currently]
+It is a result, or is one of the testing sets, for [my huggingface community blog post on my BHI-Filtering method](https://huggingface.co/blog/Phips/bhi-filtering).  
 
 ## Dataset Details
 
-This is based on the DF2K dataset, which consists of X images.
+This is based on the DF2K dataset, which consists of X images.  
 
-These images then have been tiled into X 512x512px tiles for faster sisr I/O training speed.
+These images then have been tiled into 21'387 512x512px tiles for faster sisr I/O training speed.  
 
-The BHI filtering has been applied with the following default threshold values:
+The BHI filtering has been applied with the following default threshold values:  
 
 Blockiness < 30  
 HyperIQA >= 0.2  
 IC9600 >= 0.4  
 
-Which results in this DF2K_BHI dataset with X 512x512 training tiles.
+Which results in this DF2K_BHI dataset with 12'639 512x512 training tiles.  
 
 ## Visualization
 
-Here is a visual example of the first few tiles that are in the dataset:
+Here is a visual example of the first few tiles that are in the dataset:  
 
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/634e9aa407e669188d3912f9/KL2FnhtUBSCeAdjh4ZnoZ.png)  
 
-[TODO PUT AN IMAGE HERE THAT SHOWS SOME TILES OF THE DATASET]
 
 ## Training
 
-Here is the training validation metrics on the DIV2K validation dataset, using the plksr_tiny architecture option, in comparison to the tiled full DF2K dataset:
+As can be seen in the following training validation tensorboard graphs (DIV2K validation dataset), this BHI-filtered version of the DF2K dataset is able to achieve higher or similiar metric scores while seeing a reduction of -40.9% in training tiles quantity.   
+
+Here is the training validation metrics on the DIV2K validation dataset, using the plksr_tiny architecture option, in comparison to the tiled full DF2K dataset:  
+
+Tiled DF2K dataset (here called X): 21'387 tiles  
+DF2K_BHI dataset: 12'639 tiles  
+
+
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/634e9aa407e669188d3912f9/z_wh3koK9bpkRKjoWm4LH.png)
 
-Tiled DF2K dataset (here called X): X tiles
-DF2K_BHI dataset: X tiles
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/634e9aa407e669188d3912f9/6RkW2uILyHTNhWrPLJqGx.png)
 
-[TODO PUT IMAGES HERE OF TENSORBOARD METRICS OF ONLY TILED DF2K AND DF2K_BHI]
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/634e9aa407e669188d3912f9/Ff9RlvfZ-89jDvsDhzQNB.png)