Determine golf club head speed from single raspiraw Raspberry v2 camera high framerate video frame (640x240@383fps, 640x75@1007fps, ...)

golf.club_head_speed.py

#!/usr/bin/python3
#
# Determine club head speed of a golf swing (high framerate video) frame:
# https://forums.raspberrypi.com/viewtopic.php?t=345368#p2070418

import cv2
import numpy as np
from sys import argv, exit


# https://www.geeksforgeeks.org/linear-regression-python-implementation/
def estimate_coef(x, y):
	# number of observations/points
	n = np.size(x)

	# mean of x and y vector
	m_x = np.mean(x)
	m_y = np.mean(y)

	# calculating cross-deviation and deviation about x
	SS_xy = np.sum(y*x) - n*m_y*m_x
	SS_xx = np.sum(x*x) - n*m_x*m_x

	# calculating regression coefficients
	b_1 = SS_xy / SS_xx
	b_0 = m_y - b_1*m_x

	return (b_0, b_1)


# https://stackoverflow.com/a/70385257/5674289
def imread_url(u):
    cap = cv2.VideoCapture(u)

    return cap, cap.read()  # Read the image as a video frame


# image_url = 'out.1817.png'
# image_url = 'https://forums.raspberrypi.com/download/file.php?id=58662'
# image_url = 'https://forums.raspberrypi.com/download/file.php?id=58663'
# image_url = 'https://forums.raspberrypi.com/download/file.php?id=58664'
# image_url = 'out.3360.png'
# image_url = 'https://forums.raspberrypi.com/download/file.php?id=58675'
# image_url = 'https://forums.raspberrypi.com/download/file.php?id=58676'
# image_url = 'https://forums.raspberrypi.com/download/file.php?id=58677'
image_url = 'https://stamm-wilbrandt.de/en/forum/golf_out.1817.png'
dbg = 1
delay = 0

if len(argv) > 1:
    if argv[1] in ["-h", "--help"]:
        print(argv[0],"[-h|--help|dbg [frameurl [delay (in ms, default 0)]]]")
        print("dbg=0 outputs speed only in frame window")
        print("dbg=1 in addition to 0, debug pixels in frame window")
        print("dbg=2 in addition to 0, debug pixels in analysis window")
        print("dbg=3 in addition to 2, show edge detection window")
        exit(0)

    dbg = int(argv[1])
    if len(argv) > 2:
        image_url = argv[2]
        if len(argv) > 3:
            delay = int(argv[3])


cap,(success,img) = imread_url(image_url)
assert success


# https://forums.raspberrypi.com/viewtopic.php?p=2079331#p2079136
b,g,r = cv2.split(img)
ball = cv2.addWeighted(r,8.0,b,-8.0,-128)
blur = cv2.GaussianBlur(ball, (19,19), 0)
edge = cv2.Canny(blur, 50, 100, 7, L2gradient=True)
if dbg >= 3:
    cv2.imshow('edge', edge)


# edge detection, golf ball middle slope determination
h,w = edge.shape
X=[]
Y=[]
xmin = w
d = 0

def high():
    return h >= 100

thr = 15 if high() else 5

for y in range(h):
    l = 0
    while l < w and edge[y][l] == 0:
        l += 1

    if l < w:
        r = w - 1
        while edge[y][r] == 0:
            r -= 1

        if l + thr > r:          # eliminate row y completely (all pixels black)
            while l <= r:
                edge[y][l] = 0
                l += 1
            continue

        x = l + 1              # black all pixels between leftmost and rightmost
        while x < r:
            edge[y][x] = 0
            x += 1

        if dbg == 1:
            img[y][l] = img[y][r] = (255, 255, 0)

        mx = (l+r)//2
        if mx < xmin:
            xmin = mx

        if mx <= xmin + thr:
            edge[y][mx] = 64
            if dbg == 1:
                img[y][mx] = (255, 255, 0)
        else:
            edge[y][mx] = 128
            X.append(mx)
            Y.append(y)
            if r - l > d:
                d = r - l

            if dbg == 1:
                img[y][mx] = (255, 0, 0)
        

if dbg >= 2:
    cv2.imshow('analysis', edge)


b = estimate_coef(np.array(X), np.array(Y)) if len(X) > 2 else (0, 1)

D = 0.04267                  # golf ball diameter [m]
line_time_s = 0.000019517    # Raspberry v2 camera, raspiraw mode7

ms = ((D / d) / b[1]) / line_time_s if d > 0 else 0
#         D / d: golf ball diameter divided by measured diameter [m/pixel]
#        / b[1]: div by middle pixels slope; 1 line time horizontal distance [m]
# / line_time_s: speed [m/s]


txt = f"speed: {ms:.2f}m/s ({ms * 3.6:.1f}km/h)"


# horizontally centered OpenCV text output
font = cv2.FONT_HERSHEY_PLAIN
thck = font_scale = 2 if high() else 1
txtSize = cv2.getTextSize(txt, font, font_scale, thck)

cv2.putText(img, txt, ((w - txtSize[0][0])//2, h//4), font, font_scale,
            (255, 0, 0), thck, cv2.LINE_AA)


# frame window is shown always
cv2.imshow('frame', img)


cv2.waitKey(delay)
print(txt)

cap.release()
cv2.destroyAllWindows()

3 windows output with dbg=3 in next comment:
https://forums.raspberrypi.com/viewtopic.php?p=2079384#p2079384

https://forums.raspberrypi.com/viewtopic.php?p=2079555#p2079555