# This is a very simplified example and does not use Mocha Pro's API directly.
track_screen() This example does not integrate Mocha Pro directly but illustrates a basic video processing loop. For actual development with Mocha Pro, you would need to refer to Boris FX's official documentation and SDKs.
def track_screen(): # Initialize video capture cap = cv2.VideoCapture('input.mp4') # Define region of interest (simplified example) roi = [(100, 100), (300, 300)] # coordinates while True: ret, frame = cap.read() if not ret: break # Simplified processing; real tracking is much more complex frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB) # Implement your tracking logic here cv2.imshow('Tracking', frame) if cv2.waitKey(1) & 0xFF == ord('q'): break
cap.release() cv2.destroyAllWindows()
import cv2 import numpy as np
# This is a very simplified example and does not use Mocha Pro's API directly.
track_screen() This example does not integrate Mocha Pro directly but illustrates a basic video processing loop. For actual development with Mocha Pro, you would need to refer to Boris FX's official documentation and SDKs. # This is a very simplified example and
def track_screen(): # Initialize video capture cap = cv2.VideoCapture('input.mp4') # Define region of interest (simplified example) roi = [(100, 100), (300, 300)] # coordinates while True: ret, frame = cap.read() if not ret: break # Simplified processing; real tracking is much more complex frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB) # Implement your tracking logic here cv2.imshow('Tracking', frame) if cv2.waitKey(1) & 0xFF == ord('q'): break 300)] # coordinates while True: ret
cap.release() cv2.destroyAllWindows()
import cv2 import numpy as np