feat: fix metric

api.py

@@ -15,7 +15,7 @@ def load_annoy_index(
 ) -> Tuple[annoy.AnnoyIndex, dict]:
     """Load annoy index and associated mapping file"""
 
-    annoy_index = annoy.AnnoyIndex(f=EMBEDDING_DIMENSION, metric='euclidean')
+    annoy_index = annoy.AnnoyIndex(f=EMBEDDING_DIMENSION, metric='angular')
     annoy_index.load(index_file)
 
     with open(ANNOY_MAPPING_FILE) as f:

app.py

@@ -36,7 +36,7 @@ def find_matching_images(input_img, n_matches: int = 10):
         if url != "":
           images.append(url)
 
-          score = round(100 - scores[i], 1)
+          score = round((1 - scores[i]) * 100, 1)
 
           HTML += f"""<div class="card mb-3">
                 <div class="row g-0">
@@ -46,7 +46,7 @@ def find_matching_images(input_img, n_matches: int = 10):
                     <div class="col-md-8">
                         <div class="card-body">
                             <h5 class="card-title">{mapping["name"]}</h5>
-                            <p class="card-text">Similarity: {score} %</p>
+                            <p class="card-text">Rank: {i+1}, Similarity: {score} %</p>
                             <p class="card-text">
                                 <a target="_blank" href="https://kunshujo2022.dl.itc.u-tokyo.ac.jp/item/{mapping["nconst"]}">View at 「電子展示『捃拾帖』（拡張版）」</a>
                             </p>
@@ -67,6 +67,7 @@ iface = gr.Interface(
     article=get_article_text(),
     inputs=[
         gr.inputs.Image(shape=None, label="Your image"),
+        gr.inputs.Slider(minimum=1, maximum=30, step=1, default=10, label="Number of matches"),
     ],
     # outputs=gr.Gallery(label="類似する貼り込み資料").style(height="100px"),
     outputs=gr.HTML(label="類似する貼り込み資料"),

models/index.ann

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:93813702bd173d85d7fdeeb743964360e4624facec2b8719db9ad1abf79b7bae
-size 973864800
+oid sha256:3340614656c9ecbd54d6d04340c595f5e911474d92e6fed3147cb5d6870055ef
+size 1009403344

src/build.py

@@ -95,7 +95,7 @@ N_TREES = 1000
 
 from annoy import AnnoyIndex
 
-annoy_index = AnnoyIndex(features.shape[1], metric='euclidean')
+annoy_index = AnnoyIndex(features.shape[1], metric='angular')
 
 for i in range(len(features)):