Update app.py

app.py

@@ -107,6 +107,32 @@ def process_image(img):
 image = gr.inputs.Image()
 image_out = gr.outputs.Image()
 
+markdown_part = """
+
+This space is the demo for the EDSR (Enhanced Deep Residual Networks for Single Image Super-Resolution) model. This model surpassed the performace of the current available SOTA models.
+
+Paper Link - https://arxiv.org/pdf/1707.02921
+
+Keras Example link - https://keras.io/examples/vision/edsr/
+
+
+TODO:
+
+Hack to make this work for any image size. Currently the model takes input of image size 150 x 150.
+
+We pad the input image with transparent pixels so that it is a square image, which is a multiple of 150 x 150
+
+Then we chop the image into multiple 150 x 150 sub images
+
+Upscale it and stitch it together.
+
+The output image might look a bit off, because each sub-image dosent have data about other sub-images.
+
+This approach assumes that the subimage has enough data about its surroundings
+"""
+
+gr.markdown(markdown_part)
+
 gr.Interface(
     process_image, 
     title="EDSR - Enhanced Deep Residual Networks for Single Image Super-Resolution",