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Update pages/Data Collection.py
Browse files- pages/Data Collection.py +3 -9
pages/Data Collection.py
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@@ -1,7 +1,7 @@
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import streamlit as st
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import pandas as pd
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import numpy as np
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import matplotlib.pyplot as plt
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st.set_page_config(
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@@ -261,8 +261,6 @@ elif st.session_state.current_page == "explore_excel":
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if st.button("Go Back"):
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navigate_to("main")
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elif st.session_state.current_page == "explore_images_video":
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st.markdown("""
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<h2 style="color: #BB3385;">Introduction to Images and Videos📸🖼️</h2>
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@@ -276,7 +274,6 @@ elif st.session_state.current_page == "explore_images_video":
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An image is a two-dimensional representation of the visible light spectrum, often captured
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using devices like cameras or scanners. It can store details such as colors, shapes, and textures,
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enabling us to visually interpret and analyze information.
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Common formats include JPEG, PNG, and BMP.
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</p>
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</div>
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A video is a collection of images, often referred to as frames, displayed one after another quickly
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to show continuous movement. Each frame captures a moment in time, and when these frames are played
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sequentially, they show continuous movement.
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Videos typically have a frame rate (e.g., 30 frames
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per second or 60 frames per second), which determines how many frames are displayed per second.
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Common video formats include MP4, AVI, and MOV.
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@@ -306,9 +302,7 @@ elif st.session_state.current_page == "explore_images_video":
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Images are called **grid-like structures** because they are composed of **pixels** arranged in rows and columns,
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forming a rectangular grid. Each pixel contains information about **shape**, **color**, and **patterns**, which
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together define the image's content.
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The total number of pixels is determined by the image's height
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and width (resolution), and a higher resolution provides better clarity.
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</p>
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<p style="font-size: 16px; color: #333;">
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In images, **pixels act as features**, and the entire grid represents a single data point. This combination
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# Annotate the grid with pixel labels
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for i in range(height):
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for j in range(width):
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ax.text(j, i, f'{grid[i, j]:.2f}', ha='center', va='center', color='white', fontsize=
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# Set axis labels and title
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ax.set_title("Image as a Grid-Like Structure", fontsize=12)
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import streamlit as st
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import numpy as np
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import matplotlib.pyplot as plt
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import pandas as pd
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st.set_page_config(
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if st.button("Go Back"):
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navigate_to("main")
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elif st.session_state.current_page == "explore_images_video":
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st.markdown("""
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<h2 style="color: #BB3385;">Introduction to Images and Videos📸🖼️</h2>
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An image is a two-dimensional representation of the visible light spectrum, often captured
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using devices like cameras or scanners. It can store details such as colors, shapes, and textures,
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enabling us to visually interpret and analyze information.
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Common formats include JPEG, PNG, and BMP.
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</p>
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</div>
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A video is a collection of images, often referred to as frames, displayed one after another quickly
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to show continuous movement. Each frame captures a moment in time, and when these frames are played
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sequentially, they show continuous movement.
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Videos typically have a frame rate (e.g., 30 frames
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per second or 60 frames per second), which determines how many frames are displayed per second.
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Common video formats include MP4, AVI, and MOV.
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Images are called **grid-like structures** because they are composed of **pixels** arranged in rows and columns,
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forming a rectangular grid. Each pixel contains information about **shape**, **color**, and **patterns**, which
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together define the image's content.
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The total number of pixels is determined by the image's height and width (resolution), and a higher resolution provides better clarity.
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</p>
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<p style="font-size: 16px; color: #333;">
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In images, **pixels act as features**, and the entire grid represents a single data point. This combination
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# Annotate the grid with pixel labels
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for i in range(height):
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for j in range(width):
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ax.text(j, i, f'{grid[i, j]:.2f}', ha='center', va='center', color='white', fontsize=10)
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# Set axis labels and title
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ax.set_title("Image as a Grid-Like Structure", fontsize=12)
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