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import streamlit as st | |
import numpy as np | |
from PIL import Image | |
from utils import load_model | |
def app(model_name): | |
model, processor = load_model(f"koclip/{model_name}") | |
st.title("Zero-shot Image Classification") | |
st.markdown( | |
""" | |
Some text goes in here. | |
""" | |
) | |
query = st.file_uploader("Choose an image...", type=["jpg", "jpeg", "png"]) | |
if st.button("์ง๋ฌธ (Query)"): | |
if query is None: | |
st.error("Please upload an image query.") | |
else: | |
image = Image.open(query) | |
inputs = processor(text=[""], images=image, return_tensors="jax", padding=True) | |
# vec = np.asarray(model.get_image_features(**inputs)) | |
# ids, dists = index.knnQuery(vec, k=10) | |
# result_files = map(lambda id: files[id], ids) | |
# result_imgs, result_captions = [], [] | |
# for file, dist in zip(result_files, dists): | |
# result_imgs.append(plt.imread(os.path.join(images_directory, file))) | |
# result_captions.append("{:s} (์ ์ฌ๋: {:.3f})".format(file, 1.0 - dist)) | |