Nico769

import numpy as np
import cv2 as cv
from sklearn.decomposition import PCA

# Instead of using opencv, we can use numpy
# def global_grayscale_threshold(input_image, threshold):
#     return np.where(input_image > threshold, 255, 0).astype(np.uint8)


def simple_frame_differencing(curr_frame, bg_frame, threshold):

Nico769

• Create a Python project with default Venv in the same folder where Dockerfile and docker-compose.yml are located
• Go to Settings -> Build, Execution, Deployment -> Docker and create a new Docker server. Use unix socket. "Successfully connected" should appear.
• Configure Docker Compose as a remote Pycharm interpreter as per documentation.
• Configure the Jupyter Server as per documentation, DO NOT use Managed Server option.
• In the Project panel, right click on docker-compose.yml and run it.
• Manually connect to Docker in the Services panel.
• Run the Jupyter Notebook cells.