Detect upperbody and crop a video around it (needs a pass of stabilization afterward, experiment with different classifiers)

fix-upperbody.py

import cv2

target_cascade = cv2.CascadeClassifier('haarcascade_upperbody.xml')
video_capture = cv2.VideoCapture('your_video.mp4')

fps = int(video_capture.get(cv2.CAP_PROP_FPS))

output_width, output_height = 400, 300
fourcc = cv2.VideoWriter_fourcc(*'XVID')
output_video = cv2.VideoWriter('output_video2.mp4', fourcc, fps, (output_width, output_height))

counter = 0
last_target = None
while True:
    print("Frame: " + str(counter))
    ret, frame = video_capture.read()
    
    if not ret:
        break
    
    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
    
    targets = target_cascade.detectMultiScale(gray, scaleFactor=1.1, minNeighbors=5, minSize=(30, 30))
    
    target = None

    if len(targets) > 0:
        target = min(targets, key=lambda rect: rect[1])
        last_target = target
    else:
        target = last_target
        print("SKIPPED but RECOVERED")

    (x, y, w, h) = target
    center_x = x + w // 2
    center_y = y + h // 2
    
    crop_x = max(0, center_x - output_width // 2)
    crop_y = max(0, center_y - output_height // 2)
    crop_x2 = min(frame.shape[1], crop_x + output_width)
    crop_y2 = min(frame.shape[0], crop_y + output_height)
    
    cropped_frame = frame[crop_y:crop_y2, crop_x:crop_x2]
    
    cropped_frame = cv2.resize(cropped_frame, (output_width, output_height))
    
    output_video.write(cropped_frame)
    counter = counter + 1
        

video_capture.release()
output_video.release()