Spaces:
Sleeping
Sleeping
Update app.py
Browse files
app.py
CHANGED
@@ -410,7 +410,7 @@ with tab5:
|
|
410 |
st.dataframe(reordered_df_32.style.applymap(lambda v: "background-color: lightgreen" if v == 1 else "background-color: lightcoral"))
|
411 |
st.download_button("Download Reordered CSV", reordered_df_32.to_csv(index=False), "decoded_binary_32_reordered.csv", key="download_csv_tab5_32_reordered")
|
412 |
|
413 |
-
|
414 |
st.subheader("Decoded String (Reordered 4402β3244, 4882β4455)")
|
415 |
st.write(decoded_reordered)
|
416 |
|
@@ -440,9 +440,6 @@ with tab5:
|
|
440 |
st.subheader("Binary Labels (Reordered 4402β3244, 4882β4455)")
|
441 |
st.dataframe(reordered_df_31.style.applymap(lambda v: "background-color: lightgreen" if v == 1 else "background-color: lightcoral"))
|
442 |
st.download_button("Download Reordered CSV", reordered_df_31.to_csv(index=False), "decoded_binary_31_reordered.csv", key="download_csv_tab5_31_reordered")
|
443 |
-
|
444 |
-
st.write("HI")
|
445 |
-
st.write(row.dropna().astype(int).tolist()[:31])
|
446 |
|
447 |
decoded_rows_reordered = [
|
448 |
binary_labels_to_string(row.dropna().astype(int).tolist()[:31])
|
|
|
410 |
st.dataframe(reordered_df_32.style.applymap(lambda v: "background-color: lightgreen" if v == 1 else "background-color: lightcoral"))
|
411 |
st.download_button("Download Reordered CSV", reordered_df_32.to_csv(index=False), "decoded_binary_32_reordered.csv", key="download_csv_tab5_32_reordered")
|
412 |
|
413 |
+
decoded_flat_reordered = binary_labels_to_string(reordered_df_31.values.flatten().astype(int).tolist())
|
414 |
st.subheader("Decoded String (Reordered 4402β3244, 4882β4455)")
|
415 |
st.write(decoded_reordered)
|
416 |
|
|
|
440 |
st.subheader("Binary Labels (Reordered 4402β3244, 4882β4455)")
|
441 |
st.dataframe(reordered_df_31.style.applymap(lambda v: "background-color: lightgreen" if v == 1 else "background-color: lightcoral"))
|
442 |
st.download_button("Download Reordered CSV", reordered_df_31.to_csv(index=False), "decoded_binary_31_reordered.csv", key="download_csv_tab5_31_reordered")
|
|
|
|
|
|
|
443 |
|
444 |
decoded_rows_reordered = [
|
445 |
binary_labels_to_string(row.dropna().astype(int).tolist()[:31])
|