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Update app.py
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app.py
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@@ -6,8 +6,6 @@ from streamlit_cropper import st_cropper
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# Simple app: convert user input into ASCII codes and binary labels
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# (functions string_to_binary_labels, clean_image, image_to_binary_labels_rgb, binary_labels_to_rgb_image stay unchanged)
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def string_to_binary_labels(s: str) -> list[int]:
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bits: list[int] = []
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for char in s:
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@@ -61,6 +59,14 @@ def binary_labels_to_rgb_image(binary_labels: list[int], width: int = None, heig
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img = Image.fromarray(array, mode='RGB')
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return img
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# Load thresholds from file
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thresholds = pd.read_csv("Column_Thresholds.csv", index_col=0).squeeze()
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@@ -178,7 +184,6 @@ with tab3:
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st.subheader("Binary Labels")
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st.dataframe(styled_binary_df)
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st.download_button(
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label="Download Binary Labels Table as CSV",
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data=binary_df.to_csv(index=False),
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@@ -186,4 +191,4 @@ with tab3:
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mime="text/csv"
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)
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# Future: integrate DNA editor mapping for each mutation site here
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# Simple app: convert user input into ASCII codes and binary labels
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def string_to_binary_labels(s: str) -> list[int]:
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bits: list[int] = []
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for char in s:
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img = Image.fromarray(array, mode='RGB')
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return img
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# Predefined headers for the 32 mutation sites
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mutation_site_headers = [
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3244, 3297, 3350, 3399, 3455, 3509, 3562, 3614,
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3665, 3720, 3773, 3824, 3879, 3933, 3985, 4039,
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4089, 4145, 4190, 4245, 4298, 4349, 4402, 4455,
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4510, 4561, 4615, 4668, 4720, 4773, 4828, 4882
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]
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# Load thresholds from file
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thresholds = pd.read_csv("Column_Thresholds.csv", index_col=0).squeeze()
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st.subheader("Binary Labels")
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st.dataframe(styled_binary_df)
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st.download_button(
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label="Download Binary Labels Table as CSV",
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data=binary_df.to_csv(index=False),
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mime="text/csv"
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)
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# Future: integrate DNA editor mapping for each mutation site here
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