update text

app.py

@@ -4,7 +4,25 @@ import subprocess
 import streamlit as st
 import numpy as np
 from PIL import Image
+import os
 
+st.sidebar.write("# FashionCLIP Resources")
+st.sidebar.write("We have several resources related to FashionCLIP.")
+st.sidebar.write("## Documentation")
+st.sidebar.write("* 📚 [Blog Post](https://towardsdatascience.com/teaching-clip-some-fashion-3005ac3fdcc3)")
+st.sidebar.write("* 📚 [Paper](https://www.nature.com/articles/s41598-022-23052-9)")
+
+st.sidebar.write("## Code")
+st.sidebar.write("* 📚 [Repo](https://github.com/patrickjohncyh/fashion-clip)")
+st.sidebar.write("* 📚 [Colab](https://colab.research.google.com/drive/1Z1hAxBnWjF76bEi9KQ6CMBBEmI_FVDrW#scrollTo=FzUQGwS1lhGS)")
+st.sidebar.write("* 📚 [HuggingFace Weights](https://huggingface.co/patrickjohncyh/fashion-clip)")
+
+
+st.write("# FashionCLIP. A Foundation Model for Fashion.")
+st.write("This web app uses FashionCLIP to find clothing items based on a query of the item you want to find.")
+st.write("The model is going to find the most similar item to your query, given a list of 5000 items that have been released [here](https://github.com/alexeygrigorev/clothing-dataset).")
+st.write("Note that some queries might not return anything useful. This could be both due to model's limitation or to the fact that the item you are looking for is missing from the collection.")
+st.write("You can find more about FashionCLIP on the [repo](https://github.com/patrickjohncyh/fashion-clip) or on our [paper](https://www.nature.com/articles/s41598-022-23052-9)")
 @st.cache_resource
 def load_embedding_file():
     with open("embeddings_and_paths.pkl", "rb") as filino:
@@ -16,8 +34,10 @@ def load_embedding_file():
 
 fclip = FashionCLIP('fashion-clip')
 
-subprocess.run("git clone https://github.com/alexeygrigorev/clothing-dataset", shell=True)
+if not os.path.exists("clothing-dataset"):
+    subprocess.run("git clone https://github.com/alexeygrigorev/clothing-dataset", shell=True)
 
+st.write("## Simple FashionCLIP search engine")
 query = st.text_input("Enter a description of the clothing item you want to find", "a red dress")
 
 images, image_embeddings = load_embedding_file()
@@ -29,3 +49,31 @@ id_of_matched_object = np.argmax(text_embedding.dot(image_embeddings.T))
 image = Image.open(images[id_of_matched_object])
 
 st.image(image)
+
+
+st.write("If you use FashionCLIP in your work, please cite our paper:")
+st.write("""
+```
+@Article{Chia2022,
+    title="Contrastive language and vision learning of general fashion concepts",
+    author="Chia, Patrick John
+            and Attanasio, Giuseppe
+            and Bianchi, Federico
+            and Terragni, Silvia
+            and Magalh{\~a}es, Ana Rita
+            and Goncalves, Diogo
+            and Greco, Ciro
+            and Tagliabue, Jacopo",
+    journal="Scientific Reports",
+    year="2022",
+    month="Nov",
+    day="08",
+    volume="12",
+    number="1",
+    pages="18958",
+    issn="2045-2322",
+    doi="10.1038/s41598-022-23052-9",
+    url="https://doi.org/10.1038/s41598-022-23052-9"
+```
+}""")
+