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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 | |
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) | |