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Using Raspberry pi Cam to track a piece of shiny tape as you would a Light gun in an arcade game. Think 'Point Blank' or 'Terminator' games where a light gun is pointed at screen to fire.
Using a python script to capture camera input. Detecting a dot reflected from the reflective tape the script creates a virtual screen that gets mapped to whatever screen you are using.
lightgun_cam_mouse.py
PythonLight gun cam mouse tracking, make sure to add a shinny tape spot on the bottom of your mouse
#!/usr/bin/env python3
import argparse
import json
import os
import time
import cv2
import numpy as np
from pynput.mouse import Controller as MouseController
def load_calibration(path):
if not os.path.exists(path):
return None
with open(path, "r") as f:
data = json.load(f)
H = np.array(data["H"], dtype=np.float64)
screen_w = int(data["screen_w"])
screen_h = int(data["screen_h"])
return H, screen_w, screen_h
def save_calibration(path, H, screen_w, screen_h):
data = {"H": H.tolist(), "screen_w": int(screen_w), "screen_h": int(screen_h), "saved_at": time.time()}
with open(path, "w") as f:
json.dump(data, f, indent=2)
def apply_homography(H, x, y):
pt = np.array([[[x, y]]], dtype=np.float64)
mapped = cv2.perspectiveTransform(pt, H)[0][0]
return float(mapped[0]), float(mapped[1])
def clamp(v, lo, hi):
return max(lo, min(hi, v))
def find_bright_blob(frame_bgr, thresh=235, min_area=20):
"""
Bright-spot tracking:
- grayscale
- blur
- threshold
- morphology open
- largest contour centroid
"""
gray = cv2.cvtColor(frame_bgr, cv2.COLOR_BGR2GRAY)
gray = cv2.GaussianBlur(gray, (5, 5), 0)
_, mask = cv2.threshold(gray, thresh, 255, cv2.THRESH_BINARY)
kernel = np.ones((3, 3), np.uint8)
mask = cv2.morphologyEx(mask, cv2.MORPH_OPEN, kernel, iterations=1)
cnts, _ = cv2.findContours(mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
if not cnts:
return None, None, None, mask
best = max(cnts, key=cv2.contourArea)
area = cv2.contourArea(best)
if area < min_area:
return None, None, None, mask
M = cv2.moments(best)
if M["m00"] == 0:
return None, None, None, mask
cx = int(M["m10"] / M["m00"])
cy = int(M["m01"] / M["m00"])
return cx, cy, area, mask
def main():
ap = argparse.ArgumentParser()
ap.add_argument("--cam", type=int, default=0)
ap.add_argument("--width", type=int, default=640)
ap.add_argument("--height", type=int, default=480)
ap.add_argument("--fps", type=int, default=60)
ap.add_argument("--thresh", type=int, default=235, help="0-255 threshold; lower = easier to detect")
ap.add_argument("--min-area", type=int, default=20)
ap.add_argument("--smooth", type=float, default=0.25, help="0..1 smoothing; higher=snappier")
ap.add_argument("--screen-w", type=int, default=1920)
ap.add_argument("--screen-h", type=int, default=1080)
ap.add_argument("--calib", default="calibration.json")
ap.add_argument("--preview", action="store_true")
ap.add_argument("--show-mask", action="store_true")
args = ap.parse_args()
cap = cv2.VideoCapture(args.cam, cv2.CAP_V4L2)
cap.set(cv2.CAP_PROP_FRAME_WIDTH, args.width)
cap.set(cv2.CAP_PROP_FRAME_HEIGHT, args.height)
cap.set(cv2.CAP_PROP_FPS, args.fps)
if not cap.isOpened():
raise RuntimeError("Could not open camera. Try --cam 0/1 and ensure /dev/video0 works.")
mouse = MouseController()
H = None
screen_w, screen_h = args.screen_w, args.screen_h
loaded = load_calibration(args.calib)
if loaded:
H, screen_w, screen_h = loaded
print(f"[OK] Loaded calibration {args.calib} ({screen_w}x{screen_h})")
else:
print("[INFO] No calibration loaded. Press 'c' to calibrate.")
calibrating = False
cam_points = {} # 1..4
smx = smy = None
print("\nControls:")
print(" c = start calibration (aim corner, press 1/2/3/4)")
print(" s = save calibration")
print(" r = reset calibration")
print(" q / ESC = quit\n")
while True:
ok, frame = cap.read()
if not ok:
continue
cx, cy, area, mask = find_bright_blob(frame, thresh=args.thresh, min_area=args.min_area)
debug = frame.copy()
if cx is not None:
cv2.circle(debug, (cx, cy), 8, (0, 255, 0), 2)
cv2.putText(debug, f"blob area={int(area)}", (10, 20),
cv2.FONT_HERSHEY_SIMPLEX, 0.6, (0, 255, 0), 2)
if H is not None and cx is not None:
mx, my = apply_homography(H, cx, cy)
mx = clamp(mx, 0, screen_w - 1)
my = clamp(my, 0, screen_h - 1)
if smx is None:
smx, smy = mx, my
else:
a = args.smooth
smx = (1 - a) * smx + a * mx
smy = (1 - a) * smy + a * my
mouse.position = (int(smx), int(smy))
cv2.putText(debug, f"screen=({int(mx)},{int(my)})", (10, 45),
cv2.FONT_HERSHEY_SIMPLEX, 0.6, (255, 255, 255), 2)
if calibrating:
cv2.putText(debug, "CAL: aim corners TL/TR/BR/BL then press 1/2/3/4", (10, args.height - 15),
cv2.FONT_HERSHEY_SIMPLEX, 0.55, (0, 255, 255), 2)
cv2.putText(debug, f"Captured: {sorted(cam_points.keys())}", (10, args.height - 40),
cv2.FONT_HERSHEY_SIMPLEX, 0.55, (0, 255, 255), 2)
if args.preview:
cv2.imshow("lightgun debug", debug)
if args.show_mask:
cv2.imshow("mask", mask)
k = cv2.waitKey(1) & 0xFF
if k in (27, ord('q')):
break
elif k == ord('c'):
calibrating = True
cam_points = {}
H = None
print("[CAL] Started. Press 1/2/3/4 for TL/TR/BR/BL.")
elif k == ord('r'):
calibrating = False
cam_points = {}
H = None
print("[CAL] Reset.")
elif k == ord('s'):
if H is not None:
save_calibration(args.calib, H, screen_w, screen_h)
print(f"[OK] Saved {args.calib}")
else:
print("[WARN] No calibration to save.")
if calibrating and cx is not None and k in (ord('1'), ord('2'), ord('3'), ord('4')):
idx = int(chr(k))
cam_points[idx] = (cx, cy)
print(f"[CAL] Point {idx} captured at camera=({cx},{cy})")
if all(i in cam_points for i in (1, 2, 3, 4)):
# 1=top-left, 2=top-right, 3=bottom-right, 4=bottom-left
src = np.array([cam_points[1], cam_points[2], cam_points[3], cam_points[4]], dtype=np.float32)
dst = np.array([[0, 0],
[screen_w - 1, 0],
[screen_w - 1, screen_h - 1],
[0, screen_h - 1]], dtype=np.float32)
H, _ = cv2.findHomography(src, dst, method=0)
calibrating = False
print("[OK] Calibration complete. Mouse should now follow marker. Press 's' to save.")
cap.release()
cv2.destroyAllWindows()
if __name__ == "__main__":
main()
from flask import Flask, Response
from picamera2 import Picamera2
import cv2
import time
app = Flask(__name__)
picam2 = Picamera2()
config = picam2.create_video_configuration(main={"format": "RGB888", "size": (640, 480)})
picam2.configure(config)
picam2.start()
time.sleep(0.5)
def gen():
while True:
frame = picam2.capture_array() # RGB
frame = cv2.cvtColor(frame, cv2.COLOR_RGB2BGR) # BGR for OpenCV encode
ok, jpg = cv2.imencode(".jpg", frame, [int(cv2.IMWRITE_JPEG_QUALITY), 80])
if not ok:
continue
yield (b"--frame\r\n"
b"Content-Type: image/jpeg\r\n\r\n" + jpg.tobytes() + b"\r\n")
@app.route("/stream.mjpg")
def stream():
return Response(gen(), mimetype="multipart/x-mixed-replace; boundary=frame")
@app.route("/")
def index():
return '<html><body><h3>Pi Camera Stream</h3><img src="/stream.mjpg"></body></html>'
if __name__ == "__main__":
# 0.0.0.0 = listen on all interfaces so other devices can connect
app.run(host="0.0.0.0", port=8000, threaded=True)
3 projects • 2 followers
My name is Joel Laguna. I am a game programmer. Game programming has been a long time passion. I use Python.
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