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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)) | |