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1from evaluate.filter.noiser_vllm import QueryNoiser
2
3filter = QueryNoiser('model_path')
4
5# vidoseek Test data gt_page: 03c7d62afbcc088cad1c810c09a71df29a29c968_4.jpg
6query = "Apply for Nordic Swan Ecolabel license, what is recommended as a web browser according to the Nordic Ecolabelling Portal instructions?"
7image_list = [
8 "data/03c7d62afbcc088cad1c810c09a71df29a29c968_6.jpg",
9 "data/03c7d62afbcc088cad1c810c09a71df29a29c968_5.jpg",
10 "data/03c7d62afbcc088cad1c810c09a71df29a29c968_1.jpg",
11 "data/03c7d62afbcc088cad1c810c09a71df29a29c968_8.jpg",
12 "data/03c7d62afbcc088cad1c810c09a71df29a29c968_4.jpg"
13]
14
15think_content, predicted_order = filter.find_noise(query, image_list)
16
17print(f"Query: {query}")
18print(f"noise index: {predicted_order}")
19print(f"relevant index: {[i for i in range(len(image_list)) if i not in predicted_order]}")