image_processing.py

import cv2

# Load the cascade classifier for face detection
face_cascade = cv2.CascadeClassifier("haarcascade_frontalface_default.xml")

# Load the image
img = cv2.imread("image.jpg")
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

# Detect faces
faces = face_cascade.detectMultiScale(gray, scaleFactor=1.1, minNeighbors=5)

# Draw rectangles around the faces
for (x, y, w, h) in faces:
    cv2.rectangle(img, (x, y), (x + w, y + h), (255, 0, 0), 2)

# Show the image

cv2.imshow("Faces", img)
cv2.waitKey(0)
cv2.destroyAllWindows()

# Import visualization library
import matplotlib.pyplot as plt

# Plot predicted values
model.plot(forecast)
plt.show()

# Plot predicted values with uncertainty intervals
model.plot(forecast)
plt.fill_between(
    forecast["ds"], forecast["yhat_lower"], forecast["yhat_upper"], color="pink"
)
plt.show()

# Plot component of the forecast
model.plot_components(forecast)
plt.show()