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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
 The Image Mark
Image is a Mark object, used to visualize images in standard format (png, jpg etc...), in a bqplot Figure
It takes as input an ipywidgets Image widget
The ipywidgets Image
Step1:  Displaying the image inside a bqplot Figure
Step2:  Mixing with other marks
Image is a mark like any other, so they can be mixed and matched together.
Step3:  Its traits (attributes) will also respond dynamically to a change from the backend
Step4:  Pyplot
It may seem verbose to first open the image file, create an ipywidgets Image, then create the scales and so forth.
The pyplot api does all of that for you, via the imshow function.
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Python Code:
import ipywidgets as widgets
import os
image_path = os.path.abspath('../data_files/trees.jpg')
with open(image_path, 'rb') as f:
    raw_image = f.read()
ipyimage = widgets.Image(value=raw_image, format='jpg')
ipyimage
Explanation: The Image Mark
Image is a Mark object, used to visualize images in standard format (png, jpg etc...), in a bqplot Figure
It takes as input an ipywidgets Image widget
The ipywidgets Image
End of explanation
from bqplot import *
# Create the scales for the image coordinates
scales={'x': LinearScale(), 'y': LinearScale()}
# Define the bqplot Image mark
image = Image(image=ipyimage, scales=scales)
# Create the bqplot Figure to display the mark
fig = Figure(title='Trees', marks=[image], padding_x=0, padding_y=0)
fig
Explanation: Displaying the image inside a bqplot Figure
End of explanation
scales = {'x': LinearScale(min=-1, max=2), 'y': LinearScale(min=-0.5, max=2)}
image = Image(image=ipyimage, scales=scales)
lines = Lines(x=[0, 1, 1, 0, 0], y=[0, 0, 1, 1, 0], scales=scales, colors=['red'])
fig = Figure(marks=[image, lines], padding_x=0, padding_y=0, animation_duration=1000)
fig.axes = [Axis(scale=scales['x']), Axis(scale=scales['y'], orientation='vertical')]
fig
Explanation: Mixing with other marks
Image is a mark like any other, so they can be mixed and matched together.
End of explanation
# Full screen
image.x = [-1, 2]
image.y = [-.5, 2]
Explanation: Its traits (attributes) will also respond dynamically to a change from the backend
End of explanation
import bqplot.pyplot as bqp
bqp.figure()
bqp.imshow(image_path, 'filename')
bqp.show()
Explanation: Pyplot
It may seem verbose to first open the image file, create an ipywidgets Image, then create the scales and so forth.
The pyplot api does all of that for you, via the imshow function.
End of explanation
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