DuOtto
148 lines
4.6 KiB
Plaintext
148 lines
4.6 KiB
Plaintext
import cv2, numpy as np
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from calibration import object_calibration
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from hand_detection import detect_hands, check_hand
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from helper import compute_distance
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from source.UI.hud import find_hud_placement
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import math
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from config import PIXELS_PER_INCH, CIRCLE_TOUCH_THRESHOLD
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from config import FRAME_INTERVAL, TARGET_FPS
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from config import DEBUG
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from setup import InitCameras
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#from hud import draw_hud_box, draw_pdf_page
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import time
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# ----- Global State -----
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measuring = False # measurement in progress
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start_pt = None # measurement start point
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calibrating = False # pinch-based calibration flag
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object_calibrating = False # object calibration flag
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fingertip_idx_global = None # last detected fingertip position
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hud_pos = None
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hud_rot = None
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register_hud = False
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# ----- Per-camera Processing -----
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def process_frame(frame, camera_id: int = 0):
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global measuring, start_pt, calibrating
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global object_calibrating
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global fingertip_idx_global
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global register_hud, hud_pos, hud_rot
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frame_vis = cv2.flip(frame, 1)
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# Hand detection
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results = detect_hands(frame_vis)
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fingertip_idx = None
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if results.multi_hand_landmarks:
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hand = results.multi_hand_landmarks[0]
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fingertip_idx, measuring, start_pt = check_hand(hand, frame_vis, object_calibrating)
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fingertip_idx_global = fingertip_idx
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# object calibration
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if object_calibrating and fingertip_idx is not None:
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object_calibration(frame_vis, fingertip_idx, CIRCLE_TOUCH_THRESHOLD)
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object_calibrating = False
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# place hud
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res = None
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if hud_pos is None:
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res = find_hud_placement(frame_vis)
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else:
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res = hud_pos, hud_rot
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# create proj output
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projection_out = np.zeros_like(frame)
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# measuring
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if measuring and start_pt and fingertip_idx_global:
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cv2.line(projection_out, start_pt, fingertip_idx_global, (255,0,0),2)
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px = compute_distance(start_pt, fingertip_idx_global)
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inch = px/PIXELS_PER_INCH; cm = inch*2.54
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mid = ((start_pt[0]+fingertip_idx_global[0])//2,(start_pt[1]+fingertip_idx_global[1])//2)
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cv2.putText(projection_out,f"{inch:.2f}in/{cm:.1f}cm",(mid[0]+10,mid[1]-10), cv2.FONT_HERSHEY_SIMPLEX,0.7,(255,0,255),2)
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# hud
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if res is not None or hud_pos:
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if hud_pos:
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arrow_tip = hud_pos
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dir_vec = hud_rot
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else:
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arrow_tip, dir_vec = res
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dx, dy = dir_vec
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arrow_angle = math.atan2(dy, dx) # result in radians
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#quad = draw_hud_box(projection_out, arrow_tip, arrow_angle, size=(400,400))
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#draw_pdf_page(projection_out, page_index=0, dst_quad=quad)
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if register_hud:
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hud_pos = arrow_tip
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hud_rot = dir_vec
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register_hud = False
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mask = cv2.cvtColor(projection_out, cv2.COLOR_BGR2GRAY) > 0
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frame_vis[mask] = projection_out[mask]
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return frame_vis, projection_out
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# ----- Main ----- -------------------------------------------------------------------------------------
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def main():
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all_captures = InitCameras()
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print(f"Running at up to {TARGET_FPS} FPS (interval={FRAME_INTERVAL:.3f}s)")
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print("Press 'o' for circle calib, 'q' to quit.")
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last_time = time.time()
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while True:
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processed_frames = []
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for camera_id, capture in enumerate(all_captures):
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ok, frame = capture.read()
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if not ok or frame is None:
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continue
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projection, debug = process_frame(frame, camera_id)
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processed_frames.append((camera_id, projection, debug))
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if not processed_frames:
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break
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for camera_id, projection, debug in processed_frames:
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if DEBUG:
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cv2.imshow(f'Debug Output (cam {camera_id})', debug)
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cv2.imshow(f'Projector Output (cam {camera_id})', projection)
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key = cv2.waitKey(1) & 0xFF
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if key == ord('q'):
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break
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elif key == ord('o'):
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global object_calibrating
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object_calibrating = True
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print("Entered circle calibration mode.")
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elif key == ord('j'):
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global register_hud, hud_pos
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register_hud = True
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hud_pos = None
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# ——— frame‐rate limiting ———
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now = time.time()
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elapsed = now - last_time
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to_wait = FRAME_INTERVAL - elapsed
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if to_wait > 0:
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time.sleep(to_wait)
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last_time = time.time()
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for capture in all_captures:
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capture.release()
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cv2.destroyAllWindows()
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if __name__ == '__main__':
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main()
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