first test

app.py

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+from fashion_clip.fashion_clip import FashionCLIP
+import pickle
+import subprocess
+import streamlit as st
+import numpy as np
+from PIL import Image
+
+@st.cache_resource
+def load_embedding_file():
+    with open("embeddings_and_paths.pkl", "rb") as filino:
+        data = pickle.load(filino)
+
+        images = data["images_path"]
+        embeddings = data["embeddings"]
+    return images, embeddings
+
+fclip = FashionCLIP('fashion-clip')
+
+subprocess.run("git clone https://github.com/alexeygrigorev/clothing-dataset", shell=True)
+
+query = st.text_input("Enter a description of the clothing item you want to find", "a red dress")
+
+images, image_embeddings = load_embedding_file()
+
+text_embedding = fclip.encode_text([query], 32)[0]
+
+id_of_matched_object = np.argmax(text_embedding.dot(image_embeddings.T))
+
+image = Image.open(images[id_of_matched_object])
+
+st.image(image)

embeddings_and_paths.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:540ff45010ac98c5fe88a7f3891c1bb78fc88c93deb40c0e88c773c8925b04b9
+size 12174196

requirements.txt

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+torch
+transformers
+pandas==1.4.1
+numpy
+Pillow
+streamlit==1.21.0
+st_clickable_images
+plotly
+datetime
+fashion-clip