add app description

app.py

@@ -155,6 +155,40 @@ def pred_fn(image, fake=False):
 
 examples = [str(image_root / f'negative{i:03d}.jpg') for i in range(3)]
 
+description = """
+Is it possible to identify and track individual marine mammals based on 
+community photos, taken by tourist whale-watchers on their cameras or 
+smartphones?
+
+Researchers use [photographic identification](https://whalescientists.com/photo-id/) 
+(photo-ID) of individual whales since 
+decades to study their migration, population, and behavior. While this is a 
+tedious and costly process, it is tempting to leverage the huge amount of 
+image data collected by the whale-watching community and private encounters around 
+the globe. Organizations like [flukebook](www.flukebook.org) or 
+[Happywhale](www.happywhale.com) develop AI models for automated identification at
+scale. To push the state-of-the-art, Happywhale hosted two competitions on kaggle, 
+the 2018 [Humpback Whale Identification](https://www.kaggle.com/c/humpback-whale-identification) 
+and the 2022 [Happywhale](https://www.kaggle.com/competitions/happy-whale-and-dolphin) 
+competition, which included 28 marine whale and dolphin species.
+
+Top solutions used a two-step process of cropping the raw image using an 
+image detector like [YOLOv5](https://pytorch.org/hub/ultralytics_yolov5) 
+and presenting high-resolution crops to an identifier trained with an 
+ArcFace-based loss function. The detector had to be fine-tuned on the 
+competition images with auto- or manually generated labels.
+
+Below you can test my solution (down-cut version) on your own images. 
+The detector is an ensemble of five YOLOv5 models, the identifier ensembles three
+models with EfficientNet-B7, EfficientNetV2-XL, and ConvNext-base backbone.
+"""  # appears between title and input/output
+
+article = """
+"""  # appears below input/output
+
 demo = gr.Interface(fn=pred_fn, inputs="image", outputs=["image", "text"],
-                    examples=examples)
+                    examples=examples,
+                    title='Happywhale: Individual Identification for Maritime Animals',
+                    description=description,
+                    article=None,)
 demo.launch()