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app.py

@@ -50,13 +50,16 @@ def process_image(image, preprocess):
 
 def knn_get_score(knn, k, cat, vec):
     allvecs = knn[f'{cat}_vecs']
+    st.write('allvecs.shape', allvecs.shape)
     scores = knn[f'{cat}_scores']
+    st.write('scores.shape', scores.shape)
     # Compute cosine similiarity of vec against allvecs
     # (both are already normalized)
     cos_sim_table = vec @ allvecs.T
     st.write('cos_sim_table.shape', cos_sim_table.shape)
     # Get sorted array indices by similiarity in descending order
     sortinds = np.flip(np.argsort(cos_sim_table))
+    st.write('sortinds.shape', sortinds.shape)
     # Get corresponding scores for the sorted vectors
     kscores = scores[sortinds][:k]
     st.write('kscores.shape', kscores.shape)