<jupyter_start><jupyter_text>List of times for the RCNN model taken from notebook in drive<jupyter_code>time=[9.52395872149658, 10.456350672159658, 11.456350672159658, 9.856350672159659, 8.96350892159123, 9.36350672159658, 8.99638065615965, 10.8350672159658, 9.36350672564658, 9.6350672158958, 11.194804668426514, 12.010172128677368]
import matplotlib.pyplot as plt
 
images=[1,2,3,4,5,6,7,8,9,10,11,12]

# Plot the bar graph
plot = plt.bar(images,time)

 
# Add labels and title
plt.title("Tensorflow_RCNN time")
plt.xlabel("Images")
plt.ylabel("Time(sec)")
plt.xticks(images)
 
# Display the graph on the screen
plt.show
import numpy as np
import matplotlib.pyplot as plt

data = [[9.52395872149658, 10.456350672159658, 11.456350672159658, 9.856350672159659, 8.96350892159123, 9.36350672159658, 8.99638065615965, 10.8350672159658, 9.36350672564658, 9.6350672158958, 11.194804668426514, 12.010172128677368],
  [1.626952886581421, 1.441927194595337, 1.3616983890533447, 1.4592626094818115, 1.448399543762207, 1.3365764617919922, 1.3466055393218994, 1.3622472286224365, 1.3761065006256104, 1.3657498359680176, 1.359654426574707, 1.3619511127471924]]
X = np.arange(12)
plt.bar(X + 0.0, data[0], color = 'b', width = 0.5)
plt.bar(X + 0.5, data[1], color = 'g', width = 0.5)

plt.xlabel("Images")
plt.ylabel("Time(sec)")
plt.title("Bar graph comparison")

plt.xticks([0,1,2,3,4,5,6,7,8,9,10,11])



plt.show()

import matplotlib.pyplot as plt 

# plotting the points  
plt.plot(images, ti, color='green', linestyle='dashed', linewidth = 3, 
         marker='o', markerfacecolor='blue', markersize=12) 
plt.plot(images, time, color='red', linestyle='dashed', linewidth = 3, 
         marker='o', markerfacecolor='yellow', markersize=12) 
  
# setting x and y axis range 
plt.ylim(0,13) 
plt.xlim(1,12) 

  
# naming the x axis 
plt.xlabel('images') 
# naming the y axis 
plt.ylabel('Time(sec)') 
plt.xticks(images)

# giving a title to my graph 
plt.title('Line plot comparison') 
  
# function to show the plot 
plt.show()<jupyter_output><empty_output>
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