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Update pages/Data Collection.py
Browse files- pages/Data Collection.py +14 -6
pages/Data Collection.py
CHANGED
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@@ -1853,13 +1853,20 @@ elif st.session_state.current_page == "image_transformations":
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transformed_images.append(transformed_image)
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return transformed_images
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-
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# Streamlit App
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st.title("Dynamic Affine Transformation Tool")
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st.write("Select a transformation type to proceed and learn how it works before uploading an image.")
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#
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if transformation == "Rotation":
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st.info("Rotation rotates the image around a fixed point. Angles are applied in steps of 10 degrees.")
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elif transformation == "Scaling":
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@@ -1870,8 +1877,8 @@ elif st.session_state.current_page == "image_transformations":
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st.info("Shearing skews the image along the x-axis or y-axis, creating a slanted effect.")
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elif transformation == "Cropping":
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st.info("Cropping trims the image edges step by step to focus on a smaller region.")
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uploaded_file = st.file_uploader("Step 2: Now, upload an image", type=["jpg", "jpeg", "png"])
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if uploaded_file:
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@@ -1907,7 +1914,8 @@ elif st.session_state.current_page == "image_transformations":
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file_name=f"{transformation}_transformed_images.zip",
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mime="application/zip"
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)
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col1, col2 = st.columns(2)
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with col1:
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transformed_images.append(transformed_image)
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return transformed_images
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+
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# Streamlit App
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st.title("Dynamic Affine Transformation Tool")
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st.write("Select a transformation type to proceed and learn how it works before uploading an image.")
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# Transformation Options
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transformation = st.selectbox(
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"Step 1: Select a transformation type:",
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["Select a Transformation", "Rotation", "Scaling", "Translation", "Shearing", "Cropping"]
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)
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# Ensure the user selects a valid transformation
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if transformation != "Select a Transformation":
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# Provide guidance based on the selected transformation
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if transformation == "Rotation":
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st.info("Rotation rotates the image around a fixed point. Angles are applied in steps of 10 degrees.")
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elif transformation == "Scaling":
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st.info("Shearing skews the image along the x-axis or y-axis, creating a slanted effect.")
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elif transformation == "Cropping":
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st.info("Cropping trims the image edges step by step to focus on a smaller region.")
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# Image Uploader (Only appears after selection)
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uploaded_file = st.file_uploader("Step 2: Now, upload an image", type=["jpg", "jpeg", "png"])
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if uploaded_file:
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file_name=f"{transformation}_transformed_images.zip",
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mime="application/zip"
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)
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else:
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st.warning("Please select a valid transformation type to proceed.")
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col1, col2 = st.columns(2)
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with col1:
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