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import streamlit as st
import pandas as pd
import numpy as np
# Custom CSS for styling
custom_css = """
<style>
html, body, [data-testid="stAppViewContainer"] {
background-image: linear-gradient(
rgba(0, 0, 0, 0.6),
rgba(0, 0, 0, 0.6)
),
url("https://www.istockphoto.com/photo/tech-or-space-background-abstract-3d-illustration-gm1367865109-437999705?utm_source=pixabay&utm_medium=affiliate&utm_campaign=SRP_photo_sponsored&utm_content=https%3A%2F%2Fpixabay.com%2Fphotos%2Fsearch%2Fbackground%2520datascience%2F&utm_term=background+datascience.jpg");
background-size: cover;
background-position: center;
background-repeat: no-repeat;
background-attachment: fixed;
color: white; /* Ensures all text is readable */
}
h2, h3 {
color: #FFD700; /* Gold color for headings */
}
p {
color: #FFFFFF; /* White text for paragraphs */
}
</style>
"""
# Inject the CSS into the app
st.markdown(custom_css, unsafe_allow_html=True)
st.markdown("<h2 style='text-align: left; color: Black;'>What is Video</h2>", unsafe_allow_html=True)
st.markdown(
"<p style='font-size: 16px; color: White; font-style: italic;'>"
"A video is a series of images (frames) shown in quick succession to create the perception of motion. Each frame is a static image, and the frame rate (e.g., 24, 30, or 60 frames per second) specifies the number of frames displayed per second."
"</p>",
unsafe_allow_html=True
)
# Features of an videos using opencv
st.markdown("<h2 style='text-align: left; color: Black;'>Featrures of video using opencv</h2>", unsafe_allow_html=True)
st.markdown(
"<p style='font-size: 16px; color: White; font-style: italic;'>"
"OpenCV (Open Source Computer Vision Library) is a powerful tool for video processing. Using OpenCV, Python can perform a variety of operations on video files and streams."
"</p>",
unsafe_allow_html=True
)
st.markdown("<h2 style='text-align: left; color: Black;'>Common Methods Video Processing with OpenCV:</h2>", unsafe_allow_html=True)
st.markdown(
"<p style='font-size: 16px; color: White; font-style: italic;'>"
"Reading Videos: cv2.VideoCapture: Opens and reads video files or streams."
"Writing Videos: cv2.VideoWriter: Saves video frames into a file."
"Displaying Video: Use cv2.imshow to display video frames as they are read."
"Apply real-time frame manipulation, such as applying filters or transformations."
"Convert video frames to grayscale: cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)"
"</p>",
unsafe_allow_html=True
)
st.markdown("<h2 style='text-align: left; color: Black;'>Accessing WebCam with OpenCV:</h2>", unsafe_allow_html=True)
st.markdown(
"<p style='font-size: 16px; color: White; font-style: italic;'>"
"Accessing a webcam in Python is simple and efficient using OpenCV. The library provides the cv2.VideoCapture() function, which allows you to capture live video feed from your webcam."
"</p>",
unsafe_allow_html=True
)
st.markdown("<h2 style='text-align: left; color: Black;'>Steps to Access Webcam:</h2>", unsafe_allow_html=True)
st.markdown(
"<p style='font-size: 16px; color: White; font-style: italic;'>"
"Import OpenCV: Ensure OpenCV is installed (pip install opencv-python) and import it."
"Initialize Webcam: Use cv2.VideoCapture(0) to access the default webcam (replace 0 with the device index for other cameras)."
"Read Frames: Use read() method to grab individual frames from the webcam feed."
"Display Frames: Use cv2.imshow() to view the frames in a window."
"Close Webcam: Release the webcam and close all OpenCV windows using cv2.VideoCapture.release() and cv2.destroyAllWindows()."
"</p>",
unsafe_allow_html=True
)
# Adding the link to the code without showing the complete URL
st.markdown(
"<h2 style='text-align: left; color: Black;'>Link to Full Code:</h2>", unsafe_allow_html=True
)
st.markdown(
"<p style='font-size: 16px; color: White;'>"
"You can view the full code for video processing using OpenCV on [this GitHub link](https://github.com/Sathwik4119/IMAGE/blob/main/video_using.cv2.ipynb)."
"</p>",
unsafe_allow_html=True
)
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