Upload app.py with huggingface_hub
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app.py
CHANGED
@@ -19,7 +19,7 @@ st.set_page_config(
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layout="wide"
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)
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debug =
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#st.write("Available models:", open_clip.list_models())
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@@ -60,6 +60,7 @@ def knn_get_score(knn, k, cat, vec):
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kscores = scores[sortinds][:k]
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if debug: st.write('kscores.shape', kscores.shape)
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# Get actual sorted similiarity scores
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ksims = cos_sim_table[np.expand_dims(np.arange(sortinds.shape[0]), axis=1), sortinds]
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if debug: st.write('ksims.shape', ksims.shape)
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# Apply normalization after exponential formula
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@@ -111,8 +112,8 @@ def main():
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if debug: st.write(vec.shape)
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vec = vec.numpy()
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k = 40
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for cat in
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st.write(cat, 'rating =
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except Exception as e:
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st.error(f"Error processing image: {str(e)}")
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layout="wide"
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)
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debug = False
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#st.write("Available models:", open_clip.list_models())
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kscores = scores[sortinds][:k]
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if debug: st.write('kscores.shape', kscores.shape)
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# Get actual sorted similiarity scores
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# (line copied from clip_retrieval_knn.py even though sortinds.shape[0] == 1 here)
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ksims = cos_sim_table[np.expand_dims(np.arange(sortinds.shape[0]), axis=1), sortinds]
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if debug: st.write('ksims.shape', ksims.shape)
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# Apply normalization after exponential formula
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if debug: st.write(vec.shape)
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vec = vec.numpy()
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k = 40
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for cat in categories:
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st.write(cat, f'rating = {knn_get_score(knn, k, cat, vec):.1f}')
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except Exception as e:
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st.error(f"Error processing image: {str(e)}")
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