feat: 根据激光测算中心坐标

laser_detector.py

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+from maix import camera, image, time
+
+_USE_CV = False
+try:
+    import cv2
+    import numpy as np
+    _USE_CV = True
+except ImportError:
+    pass
+
+WIDTH = 640
+HEIGHT = 480
+THRESHOLD = 100
+RED_RATIO = 1.3
+SEARCH_RADIUS = 60
+STABLE_COUNT = 5
+
+
+def find_ellipse(img_cv, cx, cy, roi_r, th, ratio):
+    x1 = max(0, cx - roi_r)
+    x2 = min(WIDTH, cx + roi_r)
+    y1 = max(0, cy - roi_r)
+    y2 = min(HEIGHT, cy + roi_r)
+    roi = img_cv[y1:y2, x1:x2]
+    if roi.size == 0:
+        return None
+    r = roi[:, :, 0].astype(np.int32)
+    g = roi[:, :, 1].astype(np.int32)
+    b = roi[:, :, 2].astype(np.int32)
+    mask = (r > th) & (r > g * ratio) & (r > b * ratio)
+    oe = (r > 200) & (g > 200) & (b > 200) & (r >= g) & (r >= b) & ((r - g) > 10) & ((r - b) > 10)
+    combined = (mask | oe).astype(np.uint8) * 255
+    contours, _ = cv2.findContours(combined, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
+    if not contours:
+        return None
+    largest = max(contours, key=cv2.contourArea)
+    if cv2.contourArea(largest) < 5:
+        return None
+    cnt = largest.copy()
+    for pt in cnt:
+        pt[0][0] += x1
+        pt[0][1] += y1
+    if len(cnt) >= 5:
+        (ex, ey), (ew, eh), ang = cv2.fitEllipse(cnt)
+        mask_ellipse = np.zeros((HEIGHT, WIDTH), dtype=np.uint8)
+        cv2.ellipse(mask_ellipse, (int(ex), int(ey)), (int(ew / 2), int(eh / 2)), ang, 0, 360, 255, -1)
+        brightness = img_cv[:, :, 0].astype(np.int32) + img_cv[:, :, 1].astype(np.int32) + img_cv[:, :, 2].astype(np.int32)
+        masked = np.where(mask_ellipse > 0, brightness, 0)
+        vals = masked[masked > 0]
+        if len(vals) > 0:
+            bth = np.percentile(vals, 90)
+            bmask = (masked >= bth).astype(np.uint8) * 255
+            bcontours, _ = cv2.findContours(bmask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
+            if bcontours:
+                blargest = max(bcontours, key=cv2.contourArea)
+                if cv2.contourArea(blargest) >= 3 and len(blargest) >= 5:
+                    (ix, iy), _, _ = cv2.fitEllipse(blargest)
+                    return (float(ix), float(iy))
+                M = cv2.moments(blargest)
+                if M["m00"] > 0:
+                    return (float(M["m10"] / M["m00"]), float(M["m01"] / M["m00"]))
+        return (float(ex), float(ey))
+    M = cv2.moments(cnt)
+    if M["m00"] > 0:
+        return (float(M["m10"] / M["m00"]), float(M["m01"] / M["m00"]))
+    return None
+
+
+def find_brightest_bytes(frame, cx, cy, roi_r, th, ratio):
+    x1 = max(0, cx - roi_r)
+    x2 = min(WIDTH, cx + roi_r)
+    y1 = max(0, cy - roi_r)
+    y2 = min(HEIGHT, cy + roi_r)
+    data = frame.to_bytes()
+    best_score = 0
+    best_pos = None
+    for y in range(y1, y2, 2):
+        for x in range(x1, x2, 2):
+            idx = (y * WIDTH + x) * 3
+            r = data[idx]; g = data[idx+1]; b = data[idx+2]
+            if (r > th and r > g * ratio and r > b * ratio) or \
+               (r > 200 and g > 200 and b > 200 and r >= g and r >= b and (r - g) > 10 and (r - b) > 10):
+                score = r + g + b
+                dx = x - cx; dy = y - cy
+                score *= max(0.5, 1.0 - ((dx*dx + dy*dy) ** 0.5 / roi_r) * 0.5)
+                if score > best_score:
+                    best_score = score
+                    best_pos = (x, y)
+    if best_pos is None:
+        return None
+    fx, fy = best_pos
+    x1f = max(0, fx - 3); x2f = min(WIDTH, fx + 4)
+    y1f = max(0, fy - 3); y2f = min(HEIGHT, fy + 4)
+    best_bright = 0
+    final_pos = best_pos
+    for y in range(y1f, y2f):
+        for x in range(x1f, x2f):
+            idx = (y * WIDTH + x) * 3
+            r = data[idx]; g = data[idx+1]; b = data[idx+2]
+            if (r > th and r > g * ratio and r > b * ratio) or \
+               (r > 200 and g > 200 and b > 200 and r >= g and r >= b and (r - g) > 10 and (r - b) > 10):
+                rgb_sum = r + g + b
+                if rgb_sum > best_bright:
+                    best_bright = rgb_sum
+                    final_pos = (float(x), float(y))
+    return final_pos
+
+
+def get_stable_laser_point(cam=None, timeout_ms=15000, stable_count=STABLE_COUNT):
+    own_cam = False
+    if cam is None:
+        try:
+            cam = camera.Camera(WIDTH, HEIGHT)
+            own_cam = True
+        except Exception:
+            return None
+    try:
+        last_pos = None
+        stable = 0
+        start = time.ticks_ms()
+        cx, cy = WIDTH // 2, HEIGHT // 2
+        while True:
+            if abs(time.ticks_diff(time.ticks_ms(), start)) > timeout_ms:
+                return None
+            frame = cam.read()
+            if frame is None:
+                time.sleep_ms(10)
+                continue
+            pos_bright = find_brightest_bytes(frame, cx, cy, SEARCH_RADIUS, THRESHOLD, RED_RATIO)
+            pos = pos_bright
+            print(f"pos:{pos},stable:{stable}")
+            if _USE_CV:
+                img_cv = image.image2cv(frame, False, False)
+                pos_ellipse = find_ellipse(img_cv, cx, cy, SEARCH_RADIUS, THRESHOLD, RED_RATIO)
+                if pos_ellipse is not None:
+                    pos = pos_ellipse
+            if pos is not None:
+                if last_pos and abs(pos[0] - last_pos[0]) < 1 and abs(pos[1] - last_pos[1]) < 1:
+                    stable += 1
+                else:
+                    stable = 1
+                last_pos = pos
+                if stable >= stable_count:
+                    return (int(pos[0]), int(pos[1]))
+            time.sleep_ms(500)
+    finally:
+        if own_cam:
+            try:
+                cam.close()
+            except:
+                pass