idk
This commit is contained in:
DuOtto
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import cv2
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import mediapipe as mp
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import numpy as np
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import cv2, numpy as np, time, fitz
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from calibration import object_calibration, draw_cal_circle
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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 hud import find_hud_placement, draw_hud
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import math
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# ----- Helper Functions -----
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def compute_distance(p1, p2):
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return np.hypot(p2[0] - p1[0], p2[1] - p1[1])
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from config import CAMERA_INDICES, FRAME_WIDTH, FRAME_HEIGHT, PIXELS_PER_INCH, CIRCLE_TOUCH_THRESHOLD
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from config import DEBUG
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# ----- Configuration -----
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CAMERA_INDICES = [0] # List of camera device indices
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FRAME_WIDTH = 1280
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FRAME_HEIGHT = 720
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PIXELS_PER_INCH = 20 # will be set by calibration
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PINCH_THRESHOLD = 40 # px to start touch
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RELEASE_THRESHOLD = 60 # px to end touch
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CIRCLE_TOUCH_THRESHOLD = 20 # px tolerance for circle touch
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from hud import draw_hud_box, draw_pdf_page
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# ----- Initialize Hand Detector -----
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mp_hands = mp.solutions.hands
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mp_draw = mp.solutions.drawing_utils
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hands = mp_hands.Hands(
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static_image_mode=False,
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max_num_hands=1,
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min_detection_confidence=0.7,
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min_tracking_confidence=0.5
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)
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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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cal_start = None # pinch calibration start point
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object_calibrating = False # object calibration flag
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cal_circle = None # reference circle (x,y,r)
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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):
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global measuring, start_pt, calibrating, cal_start, object_calibrating, cal_circle, PIXELS_PER_INCH, fingertip_idx_global
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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_out = cv2.flip(frame, 1)
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h, w, _ = frame_out.shape
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frame_vis = frame_out.copy()
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projection_debug = frame_out.copy()
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# Hand detection
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rgb = cv2.cvtColor(frame_out, cv2.COLOR_BGR2RGB)
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rgb.flags.writeable = False
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results = hands.process(rgb)
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rgb.flags.writeable = True
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frame_vis = cv2.cvtColor(rgb, cv2.COLOR_RGB2BGR)
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results = detect_hands(frame_out)
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fingertip_idx = None
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fingertip_mid = None
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if results.multi_hand_landmarks:
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hand = results.multi_hand_landmarks[0]
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mp_draw.draw_landmarks(frame_vis, hand, mp_hands.HAND_CONNECTIONS)
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# get index and middle finger tips and PIP joints
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idx_tip = hand.landmark[mp_hands.HandLandmark.INDEX_FINGER_TIP]
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idx_pip = hand.landmark[mp_hands.HandLandmark.INDEX_FINGER_PIP]
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mid_tip = hand.landmark[mp_hands.HandLandmark.MIDDLE_FINGER_TIP]
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mid_pip = hand.landmark[mp_hands.HandLandmark.MIDDLE_FINGER_PIP]
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ix, iy = int(idx_tip.x * w), int(idx_tip.y * h)
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mx, my = int(mid_tip.x * w), int(mid_tip.y * h)
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fingertip_idx = (ix, iy)
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fingertip_mid = (mx, my)
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fingertip_idx_global = fingertip_idx
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# draw fingertips
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cv2.circle(frame_vis, fingertip_idx, 8, (0,255,0), -1)
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cv2.circle(frame_vis, fingertip_mid, 8, (0,255,0), -1)
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# check extension
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index_ext = idx_tip.y < idx_pip.y
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middle_ext = mid_tip.y < mid_pip.y
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# if measurement in progress but fingers no longer both extended, stop measuring
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if measuring and not (index_ext and middle_ext):
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measuring = False
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# pinch distance
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pinch = compute_distance(fingertip_idx, fingertip_mid)
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cv2.putText(frame_vis, f"Pinch: {int(pinch)} px", (10,30), cv2.FONT_HERSHEY_SIMPLEX, 0.6, (0,255,0),2)
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# pinch calibration
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if calibrating:
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if pinch < PINCH_THRESHOLD and cal_start is None:
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cal_start = fingertip_idx
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print("Pinch calibration start set")
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elif pinch > RELEASE_THRESHOLD and cal_start is not None:
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cal_end = fingertip_idx
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px = compute_distance(cal_start, cal_end)
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inches = float(input("Enter actual distance between points (inches): "))
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PIXELS_PER_INCH = px / inches
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print(f"Calibrated: {PIXELS_PER_INCH:.2f} px/inch")
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calibrating = False
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cal_start = None
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# measurement gesture
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elif not object_calibrating and index_ext and middle_ext:
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if pinch < PINCH_THRESHOLD and not measuring:
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measuring = True
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start_pt = fingertip_idx
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elif pinch > RELEASE_THRESHOLD and measuring:
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measuring = False
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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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hsv = cv2.cvtColor(frame_vis, cv2.COLOR_BGR2HSV)
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mask = cv2.inRange(hsv, np.array([10,100,100]), np.array([25,255,255]))
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masked = cv2.bitwise_and(frame_vis, frame_vis, mask=mask)
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gray = cv2.cvtColor(masked, cv2.COLOR_BGR2GRAY)
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gray = cv2.medianBlur(gray,5)
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circles = cv2.HoughCircles(gray, cv2.HOUGH_GRADIENT, 1.2, 100,
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param1=50, param2=30, minRadius=10, maxRadius=300)
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if circles is not None:
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circles = np.round(circles[0]).astype(int)
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touched = [(x,y,r) for x,y,r in circles
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if abs(compute_distance((x,y), fingertip_idx)-r) < CIRCLE_TOUCH_THRESHOLD]
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if touched:
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touched.sort(key=lambda c: abs(compute_distance((c[0],c[1]), fingertip_idx)-c[2]))
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x,y,r = touched[0]
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cal_circle = (x,y,r)
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PIXELS_PER_INCH = 2 * r
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print(f"Circle calib: {PIXELS_PER_INCH:.2f} px/inch")
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object_calibrating = False
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object_calibration(frame_vis, fingertip_idx, CIRCLE_TOUCH_THRESHOLD)
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object_calibrating = False
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# permanent reference circle
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if cal_circle:
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cx,cy,cr = cal_circle
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cv2.circle(frame_vis,(cx,cy),cr,(0,0,255),2)
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cv2.drawMarker(frame_vis,(cx,cy),(0,0,255),cv2.MARKER_TILTED_CROSS,15,1)
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cv2.putText(frame_vis,f"Ref r={cr} px",(cx-cr,cy+cr+20),cv2.FONT_HERSHEY_SIMPLEX,0.5,(0,0,255),1)
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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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if res is not None:
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arrow_tip, dir_vec = res
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draw_hud(frame_vis, arrow_tip, dir_vec)
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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(frame_vis, arrow_tip, arrow_angle, size=(400,400))
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draw_pdf_page(frame_vis, 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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return frame_vis
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# ----- Main -----
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# ----- Main ----- -------------------------------------------------------------------------------------
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def main():
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caps = []
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global register_hud, hud_pos, hud_rot
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all_captures = []
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for idx in CAMERA_INDICES:
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cap = cv2.VideoCapture(idx)
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cap.set(cv2.CAP_PROP_FRAME_WIDTH, FRAME_WIDTH)
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cap.set(cv2.CAP_PROP_FRAME_HEIGHT, FRAME_HEIGHT)
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caps.append(cap)
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if not all(cap.isOpened() for cap in caps):
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capture = cv2.VideoCapture(idx)
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capture.set(cv2.CAP_PROP_FRAME_WIDTH, FRAME_WIDTH)
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capture.set(cv2.CAP_PROP_FRAME_HEIGHT, FRAME_HEIGHT)
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all_captures.append(capture)
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if not all(capture.isOpened() for capture in all_captures):
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print("Error: could not open all cameras")
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return
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print("Press 'c' for pinch calib, 'o' for circle calib, 'q' to quit.")
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print("Press 'o' for circle calib, 'q' to quit.")
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while True:
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frames = [cap.read()[1] for cap in caps]
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frames = [capture.read()[1] for capture in all_captures]
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frame = next((f for f in frames if f is not None), None)
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if frame is None:
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break
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# process
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full_view = process_frame(frame)
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# create proj output
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proj = np.zeros_like(full_view)
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if cal_circle:
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cx,cy,cr = cal_circle
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cv2.circle(proj,(cx,cy),cr,(0,0,255),2)
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projection_out = np.zeros_like(full_view)
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if measuring and start_pt and fingertip_idx_global:
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cv2.line(proj, start_pt, fingertip_idx_global, (255,0,0),2)
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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(proj,f"{inch:.2f}in/{cm:.1f}cm",(mid[0]+10,mid[1]-10),
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cv2.FONT_HERSHEY_SIMPLEX,0.7,(255,0,0),2)
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cv2.putText(projection_out,f"{inch:.2f}in/{cm:.1f}cm",(mid[0]+10,mid[1]-10),
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cv2.FONT_HERSHEY_SIMPLEX,0.7,(255,0,255),2)
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if hud_pos:
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dx, dy = hud_rot
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arrow_angle = math.atan2(dy, dx) # result in radians
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quad = draw_hud_box(projection_out, hud_pos, arrow_angle, size=(400,400))
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draw_pdf_page(projection_out, page_index=0, dst_quad=quad)
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# overlay proj onto debug
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debug = full_view.copy()
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# overlay ref circle
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if cal_circle:
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cx,cy,cr = cal_circle
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cv2.circle(debug,(cx,cy),cr,(0,0,255),2)
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# overlay measurement
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if measuring and start_pt and fingertip_idx_global:
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cv2.line(debug, start_pt, fingertip_idx_global, (255,0,0),2)
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cv2.line(debug, start_pt, fingertip_idx_global, (255,255,0),2)
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cv2.putText(debug,f"{inch:.2f}in/{cm:.1f}cm",(mid[0]+10,mid[1]-10),
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cv2.FONT_HERSHEY_SIMPLEX,0.7,(255,0,0),2)
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cv2.FONT_HERSHEY_SIMPLEX,0.7,(255,0,0),2)
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# show windows
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cv2.imshow('Hand Measure', debug)
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cv2.imshow('Projector Output', proj)
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cv2.imshow('Debug Output', debug)
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cv2.imshow('Projector Output', projection_out)
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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('c'):
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global calibrating
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calibrating = True
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cal_start = None
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print("Entered pinch calibration mode.")
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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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register_hud = True
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hud_pos = None
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for capture in all_captures:
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capture.release()
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for cap in caps:
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cap.release()
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cv2.destroyAllWindows()
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if __name__ == '__main__':
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-279
@@ -1,279 +0,0 @@
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import cv2
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import mediapipe as mp
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import numpy as np
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# ----- Helper Functions -----
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def compute_distance(p1, p2):
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return np.hypot(p2[0] - p1[0], p2[1] - p1[1])
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# ----- Configuration -----
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CAMERA_INDICES = [0] # List of camera device indices
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FRAME_WIDTH = 1280
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FRAME_HEIGHT = 720
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PIXELS_PER_INCH = 38 # will be set by calibration
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PINCH_THRESHOLD = 40 # px to start touch
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RELEASE_THRESHOLD = 60 # px to end touch
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CIRCLE_TOUCH_THRESHOLD = 20 # px tolerance for circle touch
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# HSV range for shape color (tune for your arrow: now tailored for orange)
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LOWER_SHAPE = np.array([10, 100, 100]) # hue from 10° (orange) to
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UPPER_SHAPE = np.array([30, 255, 255]) # hue up to 30°, full sat/val range
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# dynamic list of registered arrows
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# each entry will be {'lower': np.array, 'upper': np.array, 'tip': (x,y) or None}
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shape_ranges = []
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# ----- Initialize Hand Detector -----
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mp_hands = mp.solutions.hands
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mp_draw = mp.solutions.drawing_utils
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hands = mp_hands.Hands(
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static_image_mode=False,
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max_num_hands=1,
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min_detection_confidence=0.7,
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min_tracking_confidence=0.5
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)
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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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cal_start = None # pinch calibration start point
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object_calibrating = False # object calibration flag
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cal_circle = None # reference circle (x,y,r)
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fingertip_idx_global = None # last detected fingertip position
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arrow_tip = None # detected arrow tip position
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# ----- Per-camera Processing -----
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def process_frame(frame):
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global measuring, start_pt, calibrating, cal_start
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global object_calibrating, cal_circle, PIXELS_PER_INCH
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global fingertip_idx_global, arrow_tip
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frame_out = cv2.flip(frame, 1)
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h, w, _ = frame_out.shape
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# Hand detection
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rgb = cv2.cvtColor(frame_out, cv2.COLOR_BGR2RGB)
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rgb.flags.writeable = False
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results = hands.process(rgb)
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rgb.flags.writeable = True
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frame_vis = cv2.cvtColor(rgb, cv2.COLOR_RGB2BGR)
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fingertip_idx = None
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fingertip_mid = None
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if results.multi_hand_landmarks:
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hand = results.multi_hand_landmarks[0]
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mp_draw.draw_landmarks(frame_vis, hand, mp_hands.HAND_CONNECTIONS)
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# get index and middle finger tips and PIP joints
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idx_tip = hand.landmark[mp_hands.HandLandmark.INDEX_FINGER_TIP]
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idx_pip = hand.landmark[mp_hands.HandLandmark.INDEX_FINGER_PIP]
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mid_tip = hand.landmark[mp_hands.HandLandmark.MIDDLE_FINGER_TIP]
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mid_pip = hand.landmark[mp_hands.HandLandmark.MIDDLE_FINGER_PIP]
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ix, iy = int(idx_tip.x * w), int(idx_tip.y * h)
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mx, my = int(mid_tip.x * w), int(mid_tip.y * h)
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fingertip_idx = (ix, iy)
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fingertip_mid = (mx, my)
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fingertip_idx_global = fingertip_idx
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# draw fingertips
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cv2.circle(frame_vis, fingertip_idx, 8, (0,255,0), -1)
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cv2.circle(frame_vis, fingertip_mid, 8, (0,255,0), -1)
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# check extension
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index_ext = idx_tip.y < idx_pip.y
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middle_ext = mid_tip.y < mid_pip.y
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# if measurement in progress but fingers no longer both extended, stop measuring
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if measuring and not (index_ext and middle_ext):
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measuring = False
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# pinch distance
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pinch = compute_distance(fingertip_idx, fingertip_mid)
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cv2.putText(frame_vis, f"Pinch: {int(pinch)} px", (10,30), cv2.FONT_HERSHEY_SIMPLEX, 0.6, (0,255,0),2)
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# pinch calibration
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if calibrating:
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if pinch < PINCH_THRESHOLD and cal_start is None:
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cal_start = fingertip_idx
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print("Pinch calibration start set")
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elif pinch > RELEASE_THRESHOLD and cal_start is not None:
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cal_end = fingertip_idx
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px = compute_distance(cal_start, cal_end)
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inches = float(input("Enter actual distance between points (inches): "))
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PIXELS_PER_INCH = px / inches
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print(f"Calibrated: {PIXELS_PER_INCH:.2f} px/inch")
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calibrating = False
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cal_start = None
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# measurement gesture
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elif not object_calibrating and index_ext and middle_ext:
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if pinch < PINCH_THRESHOLD and not measuring:
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measuring = True
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start_pt = fingertip_idx
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elif pinch > RELEASE_THRESHOLD and measuring:
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measuring = False
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# object calibration
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if object_calibrating and fingertip_idx is not None:
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hsv = cv2.cvtColor(frame_vis, cv2.COLOR_BGR2HSV)
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mask = cv2.inRange(hsv, np.array([10,100,100]), np.array([25,255,255]))
|
||||
masked = cv2.bitwise_and(frame_vis, frame_vis, mask=mask)
|
||||
gray = cv2.cvtColor(masked, cv2.COLOR_BGR2GRAY)
|
||||
gray = cv2.medianBlur(gray,5)
|
||||
circles = cv2.HoughCircles(gray, cv2.HOUGH_GRADIENT, 1.2, 100,
|
||||
param1=50, param2=30, minRadius=10, maxRadius=300)
|
||||
if circles is not None:
|
||||
circles = np.round(circles[0]).astype(int)
|
||||
touched = [(x,y,r) for x,y,r in circles
|
||||
if abs(compute_distance((x,y), fingertip_idx)-r) < CIRCLE_TOUCH_THRESHOLD]
|
||||
if touched:
|
||||
touched.sort(key=lambda c: abs(compute_distance((c[0],c[1]), fingertip_idx)-c[2]))
|
||||
x,y,r = touched[0]
|
||||
cal_circle = (x,y,r)
|
||||
PIXELS_PER_INCH = 2 * r
|
||||
print(f"Circle calib: {PIXELS_PER_INCH:.2f} px/inch")
|
||||
object_calibrating = False
|
||||
|
||||
# permanent reference circle
|
||||
if cal_circle:
|
||||
cx,cy,cr = cal_circle
|
||||
cv2.circle(frame_vis,(cx,cy),cr,(0,0,255),2)
|
||||
cv2.drawMarker(frame_vis,(cx,cy),(0,0,255),cv2.MARKER_TILTED_CROSS,15,1)
|
||||
cv2.putText(frame_vis,f"Ref r={cr} px",(cx-cr,cy+cr+20),cv2.FONT_HERSHEY_SIMPLEX,0.5,(0,0,255),1)
|
||||
|
||||
# ----- Arrow Shape Detection & HUD Placement -----
|
||||
# 1) Build a clean orange mask
|
||||
hsv = cv2.cvtColor(frame_vis, cv2.COLOR_BGR2HSV)
|
||||
mask = cv2.inRange(hsv, LOWER_SHAPE, UPPER_SHAPE)
|
||||
kern = cv2.getStructuringElement(cv2.MORPH_RECT, (5,5))
|
||||
mask = cv2.morphologyEx(mask, cv2.MORPH_OPEN, kern)
|
||||
mask = cv2.morphologyEx(mask, cv2.MORPH_CLOSE, kern)
|
||||
|
||||
# 2) Find and filter contours
|
||||
contours, _ = cv2.findContours(mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
|
||||
for cnt in contours:
|
||||
area = cv2.contourArea(cnt)
|
||||
if area < 1000:
|
||||
continue
|
||||
|
||||
# Approximate to polygon and require exactly 5 corners
|
||||
peri = cv2.arcLength(cnt, True)
|
||||
approx = cv2.approxPolyDP(cnt, 0.02 * peri, True)
|
||||
if len(approx) != 5:
|
||||
continue
|
||||
|
||||
pts = approx.reshape(-1,2)
|
||||
centroid = np.mean(pts, axis=0)
|
||||
|
||||
# Find the arrow tip as the corner farthest from centroid
|
||||
dists = [np.linalg.norm(pt - centroid) for pt in pts]
|
||||
tip_pt = pts[int(np.argmax(dists))]
|
||||
raw_tip = (int(tip_pt[0]), int(tip_pt[1]))
|
||||
|
||||
# 3) Smooth the tip over time
|
||||
alpha = 0.2
|
||||
if arrow_tip is None:
|
||||
arrow_tip = raw_tip
|
||||
else:
|
||||
arrow_tip = (
|
||||
int(alpha * raw_tip[0] + (1-alpha) * arrow_tip[0]),
|
||||
int(alpha * raw_tip[1] + (1-alpha) * arrow_tip[1])
|
||||
)
|
||||
|
||||
# Draw the arrow & tip
|
||||
cv2.drawContours(frame_vis, [pts], -1, (0,255,255), 2)
|
||||
cv2.circle(frame_vis, arrow_tip, 8, (0,255,255), -1)
|
||||
cv2.putText(frame_vis, "Arrow Tip", arrow_tip,
|
||||
cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0,255,255), 2)
|
||||
|
||||
# Place the HUD box in the arrow’s pointing direction
|
||||
dir_vec = tip_pt - centroid
|
||||
norm = np.linalg.norm(dir_vec)
|
||||
if norm>0:
|
||||
dir_unit = dir_vec / norm
|
||||
offset = 50
|
||||
hud_center = (int(arrow_tip[0] + dir_unit[0]*offset),
|
||||
int(arrow_tip[1] + dir_unit[1]*offset))
|
||||
|
||||
# Build and rotate a 120×60 HUD rectangle
|
||||
w2, h2 = 60, 30
|
||||
theta = np.arctan2(dir_unit[1], dir_unit[0])
|
||||
R = np.array([[ np.cos(theta), -np.sin(theta)],
|
||||
[ np.sin(theta), np.cos(theta)]])
|
||||
corners = np.array([[-w2,-h2], [w2,-h2], [w2,h2], [-w2,h2]])
|
||||
hud_pts = (corners @ R.T) + np.array(hud_center)
|
||||
hud_pts = hud_pts.astype(int)
|
||||
|
||||
cv2.drawContours(frame_vis, [hud_pts], -1, (255,0,255), 2)
|
||||
cv2.putText(frame_vis, "HUD", hud_center,
|
||||
cv2.FONT_HERSHEY_SIMPLEX, 0.6, (255,0,255), 2)
|
||||
|
||||
|
||||
|
||||
return frame_vis
|
||||
|
||||
# ----- Main -----
|
||||
def main():
|
||||
caps = []
|
||||
for idx in CAMERA_INDICES:
|
||||
cap = cv2.VideoCapture(idx)
|
||||
cap.set(cv2.CAP_PROP_FRAME_WIDTH, FRAME_WIDTH)
|
||||
cap.set(cv2.CAP_PROP_FRAME_HEIGHT, FRAME_HEIGHT)
|
||||
caps.append(cap)
|
||||
if not all(cap.isOpened() for cap in caps):
|
||||
print("Error: could not open all cameras")
|
||||
return
|
||||
|
||||
print("Press 'c' for pinch calib, 'o' for circle calib, 'q' to quit.")
|
||||
while True:
|
||||
frames = [cap.read()[1] for cap in caps]
|
||||
frame = next((f for f in frames if f is not None), None)
|
||||
if frame is None:
|
||||
break
|
||||
# process
|
||||
full_view = process_frame(frame)
|
||||
# create proj output
|
||||
proj = np.zeros_like(full_view)
|
||||
if cal_circle:
|
||||
cx,cy,cr = cal_circle
|
||||
cv2.circle(proj,(cx,cy),cr,(0,0,255),2)
|
||||
if measuring and start_pt and fingertip_idx_global:
|
||||
cv2.line(proj, start_pt, fingertip_idx_global, (255,0,0),2)
|
||||
px = compute_distance(start_pt, fingertip_idx_global)
|
||||
inch = px/PIXELS_PER_INCH; cm = inch*2.54
|
||||
mid = ((start_pt[0]+fingertip_idx_global[0])//2,(start_pt[1]+fingertip_idx_global[1])//2)
|
||||
cv2.putText(proj,f"{inch:.2f}in/{cm:.1f}cm",(mid[0]+10,mid[1]-10),
|
||||
cv2.FONT_HERSHEY_SIMPLEX,0.7,(255,0,0),2)
|
||||
# overlay proj onto debug
|
||||
debug = full_view.copy()
|
||||
# overlay ref circle
|
||||
if cal_circle:
|
||||
cx,cy,cr = cal_circle
|
||||
cv2.circle(debug,(cx,cy),cr,(0,0,255),2)
|
||||
# overlay measurement
|
||||
if measuring and start_pt and fingertip_idx_global:
|
||||
cv2.line(debug, start_pt, fingertip_idx_global, (255,0,0),2)
|
||||
cv2.putText(debug,f"{inch:.2f}in/{cm:.1f}cm",(mid[0]+10,mid[1]-10),
|
||||
cv2.FONT_HERSHEY_SIMPLEX,0.7,(255,0,0),2)
|
||||
|
||||
# show windows
|
||||
cv2.imshow('Hand Measure', debug)
|
||||
cv2.imshow('Projector Output', proj)
|
||||
|
||||
key = cv2.waitKey(1) & 0xFF
|
||||
if key == ord('q'):
|
||||
break
|
||||
elif key == ord('c'):
|
||||
global calibrating
|
||||
calibrating = True
|
||||
cal_start = None
|
||||
print("Entered pinch calibration mode.")
|
||||
elif key == ord('o'):
|
||||
global object_calibrating
|
||||
object_calibrating = True
|
||||
print("Entered circle calibration mode.")
|
||||
|
||||
for cap in caps:
|
||||
cap.release()
|
||||
cv2.destroyAllWindows()
|
||||
|
||||
if __name__ == '__main__':
|
||||
main()
|
||||
Binary file not shown.
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@@ -0,0 +1,32 @@
|
||||
import cv2, numpy as np
|
||||
|
||||
from helper import compute_distance
|
||||
|
||||
cal_circle = None # reference circle (x,y,r)
|
||||
|
||||
def object_calibration(frame_vis, fingertip_idx, CIRCLE_TOUCH_THRESHOLD):
|
||||
global cal_circle
|
||||
hsv = cv2.cvtColor(frame_vis, cv2.COLOR_BGR2HSV)
|
||||
mask = cv2.inRange(hsv, np.array([10,100,100]), np.array([25,255,255]))
|
||||
masked = cv2.bitwise_and(frame_vis, frame_vis, mask=mask)
|
||||
gray = cv2.cvtColor(masked, cv2.COLOR_BGR2GRAY)
|
||||
gray = cv2.medianBlur(gray,5)
|
||||
circles = cv2.HoughCircles(gray, cv2.HOUGH_GRADIENT, 1.2, 100,
|
||||
param1=50, param2=30, minRadius=10, maxRadius=300)
|
||||
if circles is not None:
|
||||
circles = np.round(circles[0]).astype(int)
|
||||
touched = [(x,y,r) for x,y,r in circles
|
||||
if abs(compute_distance((x,y), fingertip_idx)-r) < CIRCLE_TOUCH_THRESHOLD]
|
||||
if touched:
|
||||
touched.sort(key=lambda c: abs(compute_distance((c[0],c[1]), fingertip_idx)-c[2]))
|
||||
x,y,r = touched[0]
|
||||
cal_circle = (x,y,r)
|
||||
PIXELS_PER_INCH = 2 * r
|
||||
print(f"Circle calib: {PIXELS_PER_INCH:.2f} px/inch")
|
||||
|
||||
def draw_cal_circle(frame_vis):
|
||||
global cal_circle
|
||||
cx,cy,cr = cal_circle
|
||||
cv2.circle(frame_vis,(cx,cy),cr,(0,0,255),2)
|
||||
cv2.drawMarker(frame_vis,(cx,cy),(0,0,255),cv2.MARKER_TILTED_CROSS,15,1)
|
||||
cv2.putText(frame_vis,f"Ref r={cr} px",(cx-cr,cy+cr+20),cv2.FONT_HERSHEY_SIMPLEX,0.5,(0,0,255),1)
|
||||
@@ -0,0 +1,27 @@
|
||||
import numpy as np
|
||||
|
||||
# ----- Configuration -----
|
||||
CAMERA_INDICES = [0] # List of camera device indices
|
||||
FRAME_WIDTH = 3980
|
||||
FRAME_HEIGHT = 2560
|
||||
PIXELS_PER_INCH = 38 # will be set by calibration
|
||||
PINCH_THRESHOLD = 40 # px to start touch
|
||||
RELEASE_THRESHOLD = 60 # px to end touch
|
||||
CIRCLE_TOUCH_THRESHOLD = 20 # px tolerance for circle touch
|
||||
|
||||
# HSV range for shape color (tune for your arrow: now tailored for orange)
|
||||
LOWER_SHAPE = np.array([10, 100, 100]) # hue from 10° (orange) to
|
||||
UPPER_SHAPE = np.array([30, 255, 255]) # hue up to 30°, full sat/val range
|
||||
|
||||
DEBOUNCE_TIME = 1.0 # seconds
|
||||
|
||||
# ——— Constants for Tabs & Buttons ———
|
||||
TAB_W, TAB_H = 40, 60
|
||||
TAB_X = 600 # adjust this to your projector output width
|
||||
TAB_Y0 = 50
|
||||
TAB_GAP = 10
|
||||
# left/right arrow buttons
|
||||
LEFT_BTN_TOP = (TAB_X, TAB_Y0+2*(TAB_H+TAB_GAP)+20)
|
||||
RIGHT_BTN_TOP = (TAB_X, LEFT_BTN_TOP[1]+TAB_H+TAB_GAP)
|
||||
|
||||
DEBUG = True
|
||||
@@ -0,0 +1,84 @@
|
||||
import mediapipe as mp
|
||||
import cv2, numpy as np, time, fitz
|
||||
from helper import compute_distance
|
||||
from config import PINCH_THRESHOLD, RELEASE_THRESHOLD
|
||||
|
||||
# ----- Initialize Hand Detector -----
|
||||
mp_hands = mp.solutions.hands
|
||||
mp_draw = mp.solutions.drawing_utils
|
||||
hands = mp_hands.Hands(
|
||||
static_image_mode=False,
|
||||
max_num_hands=2,
|
||||
min_detection_confidence=0.7,
|
||||
min_tracking_confidence=0.5
|
||||
)
|
||||
|
||||
start_pt = None # measurement start point
|
||||
measuring = False # measurement in progress
|
||||
|
||||
def detect_hands(frame):
|
||||
rgb = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
|
||||
rgb.flags.writeable = False
|
||||
results = hands.process(rgb)
|
||||
|
||||
return results
|
||||
|
||||
|
||||
def check_hand(hand, frame_vis, object_calibrating):
|
||||
h, w, _ = frame_vis.shape
|
||||
|
||||
fingertip_idx = None
|
||||
fingertip_mid = None
|
||||
|
||||
mp_draw.draw_landmarks(frame_vis, hand, mp_hands.HAND_CONNECTIONS)
|
||||
# get index and middle finger tips and PIP joints
|
||||
idx_tip = hand.landmark[mp_hands.HandLandmark.INDEX_FINGER_TIP]
|
||||
mid_tip = hand.landmark[mp_hands.HandLandmark.MIDDLE_FINGER_TIP]
|
||||
ix, iy = int(idx_tip.x * w), int(idx_tip.y * h)
|
||||
mx, my = int(mid_tip.x * w), int(mid_tip.y * h)
|
||||
fingertip_idx = (ix, iy)
|
||||
fingertip_mid = (mx, my)
|
||||
|
||||
# draw fingertips
|
||||
cv2.circle(frame_vis, fingertip_idx, 8, (255,255,0), -1)
|
||||
cv2.circle(frame_vis, fingertip_mid, 8, (0,255,0), -1)
|
||||
|
||||
measuring, start_pt = is_measuring(frame_vis, hand, object_calibrating)
|
||||
|
||||
return fingertip_idx, measuring, start_pt
|
||||
|
||||
def is_measuring(frame_vis, hand, object_calibrating):
|
||||
global measuring, start_pt
|
||||
h, w, _ = frame_vis.shape
|
||||
|
||||
idx_tip = hand.landmark[mp_hands.HandLandmark.INDEX_FINGER_TIP]
|
||||
idx_pip = hand.landmark[mp_hands.HandLandmark.INDEX_FINGER_PIP]
|
||||
mid_tip = hand.landmark[mp_hands.HandLandmark.MIDDLE_FINGER_TIP]
|
||||
mid_pip = hand.landmark[mp_hands.HandLandmark.MIDDLE_FINGER_PIP]
|
||||
|
||||
ix, iy = int(idx_tip.x * w), int(idx_tip.y * h)
|
||||
mx, my = int(mid_tip.x * w), int(mid_tip.y * h)
|
||||
fingertip_idx = (ix, iy)
|
||||
fingertip_mid = (mx, my)
|
||||
|
||||
# check extension
|
||||
index_ext = idx_tip.y < idx_pip.y
|
||||
middle_ext = mid_tip.y < mid_pip.y
|
||||
|
||||
# if measurement in progress but fingers no longer both extended, stop measuring
|
||||
if measuring and not (index_ext and middle_ext):
|
||||
measuring = False
|
||||
|
||||
# pinch distance
|
||||
pinch = compute_distance(fingertip_idx, fingertip_mid)
|
||||
cv2.putText(frame_vis, f"Pinch: {int(pinch)} px", (10,30), cv2.FONT_HERSHEY_SIMPLEX, 0.6, (0,255,0),2)
|
||||
|
||||
# measurement gesture
|
||||
if not object_calibrating and index_ext and middle_ext:
|
||||
if pinch < PINCH_THRESHOLD and not measuring:
|
||||
measuring = True
|
||||
start_pt = fingertip_idx
|
||||
elif pinch > RELEASE_THRESHOLD and measuring:
|
||||
measuring = False
|
||||
|
||||
return measuring, start_pt
|
||||
@@ -0,0 +1,6 @@
|
||||
import numpy as np
|
||||
|
||||
# ----- Helper Functions -----
|
||||
def compute_distance(p1, p2):
|
||||
return np.hypot(p2[0] - p1[0], p2[1] - p1[1])
|
||||
|
||||
@@ -0,0 +1,136 @@
|
||||
import cv2, numpy as np
|
||||
from config import LOWER_SHAPE, UPPER_SHAPE
|
||||
import cv2
|
||||
import numpy as np
|
||||
import time
|
||||
import fitz # PyMuPDF for PDF rendering
|
||||
|
||||
|
||||
|
||||
def find_hud_placement(frame_vis):
|
||||
# ----- Arrow Shape Detection & HUD Placement -----
|
||||
# 1) Build a clean orange mask
|
||||
hsv = cv2.cvtColor(frame_vis, cv2.COLOR_BGR2HSV)
|
||||
mask = cv2.inRange(hsv, LOWER_SHAPE, UPPER_SHAPE)
|
||||
kern = cv2.getStructuringElement(cv2.MORPH_RECT, (5,5))
|
||||
mask = cv2.morphologyEx(mask, cv2.MORPH_OPEN, kern)
|
||||
mask = cv2.morphologyEx(mask, cv2.MORPH_CLOSE, kern)
|
||||
|
||||
# 2) Find and filter contours
|
||||
contours, _ = cv2.findContours(mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
|
||||
for cnt in contours:
|
||||
area = cv2.contourArea(cnt)
|
||||
if area < 1000:
|
||||
continue
|
||||
|
||||
# Approximate to polygon and require exactly 5 corners
|
||||
peri = cv2.arcLength(cnt, True)
|
||||
approx = cv2.approxPolyDP(cnt, 0.02 * peri, True)
|
||||
if len(approx) != 5:
|
||||
continue
|
||||
|
||||
pts = approx.reshape(-1,2)
|
||||
centroid = np.mean(pts, axis=0)
|
||||
|
||||
# Find the arrow tip as the corner farthest from centroid
|
||||
dists = [np.linalg.norm(pt - centroid) for pt in pts]
|
||||
tip_pt = pts[int(np.argmax(dists))]
|
||||
arrow_tip = (int(tip_pt[0]), int(tip_pt[1]))
|
||||
|
||||
# Place the HUD box in the arrow’s pointing direction
|
||||
dir_vec = tip_pt - centroid
|
||||
|
||||
#ToDo remove
|
||||
cv2.drawContours(frame_vis, [pts], -1, (0,255,255), 2)
|
||||
|
||||
return arrow_tip, dir_vec
|
||||
|
||||
# ——————————————————————————————————————————————
|
||||
# PDF loading / rasterization at import time
|
||||
# ——————————————————————————————————————————————
|
||||
PDF_PATH = "DarkAngles.pdf" # change this to your file
|
||||
PDF_DPI = 600 # controls resolution of rasterization
|
||||
|
||||
_doc = fitz.open(PDF_PATH)
|
||||
_pdf_pages = []
|
||||
for page in _doc:
|
||||
# render page to pixmap at desired zoom
|
||||
zoom = PDF_DPI / 72.0
|
||||
mat = fitz.Matrix(zoom, zoom)
|
||||
pix = page.get_pixmap(matrix=mat, alpha=False)
|
||||
# convert pixmap to ndarray
|
||||
img = np.frombuffer(pix.samples, dtype=np.uint8)
|
||||
img = img.reshape(pix.height, pix.width, pix.n)
|
||||
if pix.n == 4:
|
||||
img = cv2.cvtColor(img, cv2.COLOR_RGBA2BGR)
|
||||
_pdf_pages.append(img)
|
||||
_doc.close()
|
||||
|
||||
# ——————————————————————————————————————————————
|
||||
# HUD drawing routines
|
||||
# ——————————————————————————————————————————————
|
||||
|
||||
# rotated rectangle → 4 pts
|
||||
def _rect_to_pts(center, size, angle_rad):
|
||||
cx, cy = center
|
||||
w, h = size
|
||||
# local corners
|
||||
pts = np.array([
|
||||
[-w/2, -h/2],
|
||||
[ w/2, -h/2],
|
||||
[ w/2, h/2],
|
||||
[-w/2, h/2],
|
||||
])
|
||||
# rotation
|
||||
c, s = np.cos(angle_rad), np.sin(angle_rad)
|
||||
R = np.array([[c, -s],[s, c]])
|
||||
pts = pts.dot(R.T)
|
||||
pts += np.array([cx, cy])
|
||||
return pts.astype(np.float32)
|
||||
|
||||
def draw_hud_box(frame, tip, angle_rad, size=(120, 60), color=(255,0,255), thickness=2):
|
||||
"""Draw a rotated HUD rectangle at `tip` pointing along `angle_rad`."""
|
||||
# compute box corners
|
||||
pts = _rect_to_pts(center=tip, size=size, angle_rad=angle_rad)
|
||||
cv2.drawContours(frame, [pts.astype(int)], -1, color, thickness)
|
||||
# label
|
||||
cv2.putText(frame, "HUD", (int(tip[0]+5), int(tip[1]+5)), cv2.FONT_HERSHEY_SIMPLEX, 0.6, color, 2)
|
||||
return pts # return the quad for PDF warping
|
||||
|
||||
def draw_pdf_page(frame, page_index, dst_quad):
|
||||
"""
|
||||
Warp PDF page image #page_index into the quadrilateral dst_quad.
|
||||
dst_quad: 4×2 float32 array of destination corners in clock-wise order.
|
||||
"""
|
||||
if page_index < 0 or page_index >= len(_pdf_pages):
|
||||
return
|
||||
src = _pdf_pages[page_index]
|
||||
h, w = src.shape[:2]
|
||||
|
||||
# source corners (tl, tr, br, bl)
|
||||
src_quad = np.array([[0,0], [w,0], [w,h], [0,h]], dtype=np.float32)
|
||||
# compute homography
|
||||
M = cv2.getPerspectiveTransform(src_quad, dst_quad)
|
||||
# warp PDF page into place (transparent where outside)
|
||||
warp = cv2.warpPerspective(src, M, (frame.shape[1], frame.shape[0]))
|
||||
mask = cv2.warpPerspective(np.ones((h,w), dtype=np.uint8)*255, M, (frame.shape[1], frame.shape[0]))
|
||||
# composite onto frame
|
||||
inv = cv2.bitwise_not(mask)
|
||||
bg = cv2.bitwise_and(frame, frame, mask=inv)
|
||||
fg = cv2.bitwise_and(warp, warp, mask=mask)
|
||||
np.copyto(frame, bg+fg)
|
||||
|
||||
# hud.py
|
||||
class HUD:
|
||||
def __init__(self, marker_id, pdf_pages, default_page=0):
|
||||
self.id = marker_id
|
||||
self.page_index = default_page
|
||||
self.pdf_pages = pdf_pages # list of preloaded page images
|
||||
self.ref_quad = None # the 4-corner quad where to draw the PDF
|
||||
self.last_seen = 0 # for timeout if arrow goes away
|
||||
|
||||
def update(self, marker):
|
||||
return
|
||||
|
||||
def draw(self, frame):
|
||||
return
|
||||
@@ -0,0 +1,140 @@
|
||||
import cv2, numpy as np
|
||||
from calibration import object_calibration
|
||||
from hand_detection import detect_hands, check_hand
|
||||
from helper import compute_distance
|
||||
from hud import find_hud_placement
|
||||
import math
|
||||
|
||||
from config import CAMERA_INDICES, FRAME_WIDTH, FRAME_HEIGHT, PIXELS_PER_INCH, CIRCLE_TOUCH_THRESHOLD
|
||||
from config import DEBUG
|
||||
|
||||
from hud import draw_hud_box, draw_pdf_page
|
||||
|
||||
# ----- Global State -----
|
||||
measuring = False # measurement in progress
|
||||
start_pt = None # measurement start point
|
||||
calibrating = False # pinch-based calibration flag
|
||||
object_calibrating = False # object calibration flag
|
||||
fingertip_idx_global = None # last detected fingertip position
|
||||
|
||||
hud_pos = None
|
||||
hud_rot = None
|
||||
register_hud = False
|
||||
|
||||
# ----- Per-camera Processing -----
|
||||
def process_frame(frame):
|
||||
global measuring, start_pt, calibrating
|
||||
global object_calibrating
|
||||
global fingertip_idx_global
|
||||
|
||||
global register_hud, hud_pos, hud_rot
|
||||
|
||||
frame_vis = cv2.flip(frame, 1)
|
||||
|
||||
# Hand detection
|
||||
results = detect_hands(frame_vis)
|
||||
|
||||
fingertip_idx = None
|
||||
if results.multi_hand_landmarks:
|
||||
hand = results.multi_hand_landmarks[0]
|
||||
fingertip_idx, measuring, start_pt = check_hand(hand, frame_vis, object_calibrating)
|
||||
|
||||
fingertip_idx_global = fingertip_idx
|
||||
|
||||
# object calibration
|
||||
if object_calibrating and fingertip_idx is not None:
|
||||
object_calibration(frame_vis, fingertip_idx, CIRCLE_TOUCH_THRESHOLD)
|
||||
object_calibrating = False
|
||||
|
||||
# place hud
|
||||
res = None
|
||||
if hud_pos is None:
|
||||
res = find_hud_placement(frame_vis)
|
||||
else:
|
||||
res = hud_pos, hud_rot
|
||||
|
||||
|
||||
|
||||
# create proj output
|
||||
projection_out = np.zeros_like(frame)
|
||||
|
||||
# measuring
|
||||
if measuring and start_pt and fingertip_idx_global:
|
||||
cv2.line(projection_out, start_pt, fingertip_idx_global, (255,0,0),2)
|
||||
px = compute_distance(start_pt, fingertip_idx_global)
|
||||
inch = px/PIXELS_PER_INCH; cm = inch*2.54
|
||||
mid = ((start_pt[0]+fingertip_idx_global[0])//2,(start_pt[1]+fingertip_idx_global[1])//2)
|
||||
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)
|
||||
|
||||
# hud
|
||||
if res is not None or hud_pos:
|
||||
if hud_pos:
|
||||
arrow_tip = hud_pos
|
||||
dir_vec = hud_rot
|
||||
else:
|
||||
arrow_tip, dir_vec = res
|
||||
|
||||
dx, dy = dir_vec
|
||||
arrow_angle = math.atan2(dy, dx) # result in radians
|
||||
quad = draw_hud_box(projection_out, arrow_tip, arrow_angle, size=(400,400))
|
||||
draw_pdf_page(projection_out, page_index=0, dst_quad=quad)
|
||||
|
||||
if register_hud:
|
||||
hud_pos = arrow_tip
|
||||
hud_rot = dir_vec
|
||||
register_hud = False
|
||||
|
||||
|
||||
mask = cv2.cvtColor(projection_out, cv2.COLOR_BGR2GRAY) > 0
|
||||
frame_vis[mask] = projection_out[mask]
|
||||
|
||||
return frame_vis, projection_out
|
||||
|
||||
# ----- Main ----- -------------------------------------------------------------------------------------
|
||||
def main():
|
||||
all_captures = []
|
||||
for idx in CAMERA_INDICES:
|
||||
capture = cv2.VideoCapture(idx)
|
||||
capture.set(cv2.CAP_PROP_FRAME_WIDTH, FRAME_WIDTH)
|
||||
capture.set(cv2.CAP_PROP_FRAME_HEIGHT, FRAME_HEIGHT)
|
||||
all_captures.append(capture)
|
||||
if not all(capture.isOpened() for capture in all_captures):
|
||||
print("Error: could not open all cameras")
|
||||
return
|
||||
|
||||
print("Press 'o' for circle calib, 'q' to quit.")
|
||||
while True:
|
||||
frames = [capture.read()[1] for capture in all_captures]
|
||||
frame = next((f for f in frames if f is not None), None)
|
||||
|
||||
if frame is None:
|
||||
break
|
||||
|
||||
# process
|
||||
projection, debug = process_frame(frame)
|
||||
|
||||
# show windows
|
||||
if DEBUG:
|
||||
cv2.imshow('Debug Output', debug)
|
||||
cv2.imshow('Projector Output', projection)
|
||||
|
||||
key = cv2.waitKey(1) & 0xFF
|
||||
|
||||
if key == ord('q'):
|
||||
break
|
||||
elif key == ord('o'):
|
||||
global object_calibrating
|
||||
object_calibrating = True
|
||||
print("Entered circle calibration mode.")
|
||||
elif key == ord('j'):
|
||||
global register_hud, hud_pos
|
||||
register_hud = True
|
||||
hud_pos = None
|
||||
|
||||
for capture in all_captures:
|
||||
capture.release()
|
||||
|
||||
cv2.destroyAllWindows()
|
||||
|
||||
if __name__ == '__main__':
|
||||
main()
|
||||
Reference in New Issue
Block a user