Add 3x upscaling model.

README.md

@@ -34,12 +34,12 @@ import requests
 url = 'https://paperswithcode.com/media/datasets/Set5-0000002728-07a9793f_zA3bDjj.jpg'
 image = Image.open(requests.get(url, stream=True).raw)
 
-model = EdsrModel.from_pretrained('eugenesiow/edsr-base', scale=2)
+model = EdsrModel.from_pretrained('eugenesiow/edsr-base', scale=2)      # scale 2, 3 and 4 models available
 inputs = ImageLoader.load_image(image)
 preds = model(inputs)
 
-ImageLoader.save_image(preds, './scaled_2x.png')
-ImageLoader.save_compare(inputs, preds, './scaled_2x_compare.png')
+ImageLoader.save_image(preds, './scaled_2x.png')                        # save the output 2x scaled image to `./scaled_2x.png`
+ImageLoader.save_compare(inputs, preds, './scaled_2x_compare.png')      # save an output comparing the super-image with a bicubic scaling
 ```
 ## Training data
 The EDSR models for 2x, 3x and 4x image super resolution were pretrained on [DIV2K](https://data.vision.ee.ethz.ch/cvl/DIV2K/), a dataset of 800 high-quality (2K resolution) images for training, augmented to 4000 images and uses a dev set of  100 validation images (images numbered 801 to 900). 
@@ -105,20 +105,20 @@ Evaluation datasets include:
 
 The results columns below are represented below as `PSNR/SSIM`. They are compared against a Bicubic baseline.
 
-|Dataset  	|Scale  |Bicubic  	    |edsr-base  	      |
-|---	      |---	  |---	          |---	              |
-|Set5  	    |2x     |33.64/0.9292   |**38.02/0.9607**   |
-|Set5  	    |3x  	  |30.39/0.8678  	|  	|
-|Set5  	    |4x  	  |28.42/0.8101  	|**32.12/0.8947**   |
-|Set14  	  |2x     |30.22/0.8683  	|  	|
-|Set14  	  |3x     |27.53/0.7737  	|  	|
-|Set14  	  |4x     |25.99/0.7023  	|**28.60/0.7815**  	|
-|BSD100  	  |2x  	  |29.55/0.8425  	|  	|
-|BSD100  	  |3x  	  |27.20/0.7382  	|  	|
-|BSD100  	  |4x  	  |25.96/0.6672  	|**27.61/0.7363**  	|
-|Urban100  	|2x  	  |26.66/0.8408  	|  	|
-|Urban100  	|3x  	  |  	|  	|
-|Urban100  	|4x  	  |23.14/0.6573  	|**26.02/0.7832**  	|
+|Dataset  	    |Scale      |Bicubic  	        |edsr-base  	        |
+|---	        |---	    |---	            |---	                |
+|Set5  	        |2x         |33.64/0.9292       |**38.02/0.9607**       |
+|Set5  	        |3x  	    |30.39/0.8678  	    |**35.04/0.9403**  	    |
+|Set5  	        |4x  	    |28.42/0.8101  	    |**32.12/0.8947**       |
+|Set14  	    |2x         |30.22/0.8683  	    |**33.57/0.9172**  	    |
+|Set14  	    |3x         |27.53/0.7737  	    |**30.93/0.8567**  	    |
+|Set14  	    |4x         |25.99/0.7023  	    |**28.60/0.7815**  	    |
+|BSD100  	    |2x  	    |29.55/0.8425  	    |**32.21/0.8999**  	    |
+|BSD100  	    |3x  	    |27.20/0.7382  	    |**29.65/0.8204**  	    |
+|BSD100  	    |4x  	    |25.96/0.6672  	    |**27.61/0.7363**  	    |
+|Urban100  	    |2x  	    |26.66/0.8408  	    |**32.04/0.9276**  	    |
+|Urban100  	    |3x  	    |  	                |**29.23/0.8723**  	    |
+|Urban100  	    |4x  	    |23.14/0.6573  	    |**26.02/0.7832**  	    |
 
 ![Comparing Bicubic upscaling against EDSR x2 upscaling on Set5 Image 2](images/Set5_2_compare.png "Comparing Bicubic upscaling against EDSR x2 upscaling on Set5 Image 2")
 

config.json

@@ -7,5 +7,5 @@
   "n_resblocks": 16,
   "res_scale": 1,
   "rgb_range": 255,
-  "supported_scales": [2, 4]
+  "supported_scales": [2, 3, 4]
 }

pytorch_model_3x.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:27a09b477d3b9531e2a0e6747a103a8c619c0daac9f4ee704828e335bdb034cd
+size 6245313