okay so i decided to put the differences in a jupyter notebook for you to execute and see the difference,Please Note: **add_layout_image** is used to add images to the layout of the figure, allowing for precise control over the positioning and layering of the image. **add_image** (not used here) would be used to add images directly to the figure, but it is less flexible in terms of positioning and layering compared to **add_layout_image**.

import matplotlib.pyplot as plt
import numpy as np

# Create a sequence of numbers from 0 to 9
x = np.arange(10)

# Set up a new figure and plotting area
fig = plt.figure()
ax = plt.subplot(111)

# Draw multiple lines on the same graph
# Each line will be a different multiple of x
for i in range(5):
    ax.plot(x, i * x, label='$y = %ix$' % i)

# Add a legend outside the main plot area
ax.legend(bbox_to_anchor=(1.1, 1.05))

# Display the graph
plt.show()

#pip install plotly

import plotly.graph_objects as go

# Start creating an interactive figure
fig = go.Figure()

# Add the first image to the figure
# This places a semi-transparent placeholder image on the graph
fig.add_layout_image(
    dict(
        source="https://via.placeholder.com/150",
        xref="x",
        yref="y",
        x=5,
        y=5,
        sizex=2,
        sizey=2,
        sizing="stretch",
        opacity=0.5,
        layer="below"
    )
)

 # Add a second image to the figure 
    # Positioned differently from the first image
    fig.add_layout_image(
        dict(
            source="https://via.placeholder.com/150",
            xref="x",
            yref="y",
            x=7,
            y=7,
            sizex=2,
            sizey=2,
            sizing="stretch",
            opacity=0.5,
            layer="below"
        )
    )
    
    # Set up the graph's viewing area
    fig.update_layout(
        xaxis=dict(range=[0, 10]),
        yaxis=dict(range=[0, 10])
    )
    
    # Show the interactive figure
    fig.show()