update laser cabration
This commit is contained in:
huangzhenwei2
184
laser_manager.py
184
laser_manager.py
@@ -175,23 +175,189 @@ class LaserManager:
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if logger:
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logger.error(f"闪激光失败: {e}")
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def find_red_laser(self, frame, threshold=150):
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"""在图像中查找最亮的红色激光点（基于 RGB 阈值）"""
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# def find_red_laser(self, frame, threshold=150):
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# """在图像中查找最亮的红色激光点（基于 RGB 阈值）"""
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# w, h = frame.width(), frame.height()
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# img_bytes = frame.to_bytes()
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# max_sum = 0
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# best_pos = None
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# for y in range(0, h, 2):
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# for x in range(0, w, 2):
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# idx = (y * w + x) * 3
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# r, g, b = img_bytes[idx], img_bytes[idx+1], img_bytes[idx+2]
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# if r > threshold and r > g * 2 and r > b * 2:
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# rgb_sum = r + g + b
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# if rgb_sum > max_sum:
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# max_sum = rgb_sum
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# best_pos = (x, y)
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# return best_pos
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# def find_red_laser(self, frame, threshold=150, search_radius=50):
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# """
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# 在图像中心附近查找最亮的红色激光点（基于 RGB 阈值）
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# Args:
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# frame: 图像帧
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# threshold: 红色通道阈值（默认150）
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# search_radius: 搜索半径（像素），从图像中心开始搜索（默认150）
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# Returns:
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# (x, y) 坐标，如果未找到则返回 None
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# """
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# w, h = frame.width(), frame.height()
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# center_x, center_y = w // 2, h // 2
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# # 只在中心区域搜索
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# x_min = max(0, center_x - search_radius)
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# x_max = min(w, center_x + search_radius)
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# y_min = max(0, center_y - search_radius)
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# y_max = min(h, center_y + search_radius)
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# img_bytes = frame.to_bytes()
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# max_score = 0
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# best_pos = None
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# for y in range(y_min, y_max, 2):
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# for x in range(x_min, x_max, 2):
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# idx = (y * w + x) * 3
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# r, g, b = img_bytes[idx], img_bytes[idx+1], img_bytes[idx+2]
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# # 判断是否为红色或过曝的红色（发白）
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# is_red = False
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# is_overexposed_red = False
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# # 情况1：正常红色（r 明显大于 g 和 b）
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# if r > threshold and r > g * 2 and r > b * 2:
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# is_red = True
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# # 情况2：过曝的红色（发白，r, g, b 都接近255，但 r 仍然最大）
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# # 过曝时，r, g, b 都接近 255，但 r 应该仍然是最高的
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# elif r > 200 and g > 200 and b > 200: # 接近白色
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# if r >= g and r >= b and (r - g) > 10 and (r - b) > 10: # r 仍然明显最大
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# is_overexposed_red = True
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# if is_red or is_overexposed_red:
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# # 计算得分：RGB 总和 + 距离中心权重（越靠近中心得分越高）
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# rgb_sum = r + g + b
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# # 计算到中心的距离
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# dx = x - center_x
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# dy = y - center_y
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# distance_from_center = (dx * dx + dy * dy) ** 0.5
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# # 距离权重：距离越近，权重越高（最大权重为 1.0，距离为 0 时）
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# # 当距离为 search_radius 时，权重为 0.5
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# distance_weight = 1.0 - (distance_from_center / search_radius) * 0.5
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# distance_weight = max(0.5, distance_weight) # 最小权重 0.5
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# # 综合得分：RGB 总和 * 距离权重
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# score = rgb_sum * distance_weight
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# if score > max_score:
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# max_score = score
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# best_pos = (x, y)
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# print("best_pos:", best_pos)
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# return best_pos
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def find_red_laser(self, frame, threshold=150, search_radius=150):
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"""
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在图像中心附近查找最亮的红色激光点（基于 RGB 阈值）
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使用两阶段搜索：先粗搜索找到候选区域，再精细搜索找到最亮点
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Args:
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frame: 图像帧
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threshold: 红色通道阈值（默认150）
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search_radius: 搜索半径（像素），从图像中心开始搜索（默认150）
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Returns:
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(x, y) 坐标，如果未找到则返回 None
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"""
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w, h = frame.width(), frame.height()
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center_x, center_y = w // 2, h // 2
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# 只在中心区域搜索
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x_min = max(0, center_x - search_radius)
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x_max = min(w, center_x + search_radius)
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y_min = max(0, center_y - search_radius)
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y_max = min(h, center_y + search_radius)
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img_bytes = frame.to_bytes()
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max_sum = 0
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best_pos = None
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for y in range(0, h, 2):
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for x in range(0, w, 2):
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max_score = 0
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candidate_pos = None
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# 第一阶段：粗搜索（每2像素采样），找到候选点
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for y in range(y_min, y_max, 2):
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for x in range(x_min, x_max, 2):
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idx = (y * w + x) * 3
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r, g, b = img_bytes[idx], img_bytes[idx+1], img_bytes[idx+2]
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# 判断是否为红色或过曝的红色（发白）
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is_red = False
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is_overexposed_red = False
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# 情况1：正常红色（r 明显大于 g 和 b）
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if r > threshold and r > g * 2 and r > b * 2:
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is_red = True
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# 情况2：过曝的红色（发白，r, g, b 都接近255，但 r 仍然最大）
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elif r > 200 and g > 200 and b > 200: # 接近白色
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if r >= g and r >= b and (r - g) > 10 and (r - b) > 10: # r 仍然明显最大
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is_overexposed_red = True
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if is_red or is_overexposed_red:
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# 计算得分：RGB 总和 + 距离中心权重
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rgb_sum = r + g + b
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if rgb_sum > max_sum:
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max_sum = rgb_sum
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dx = x - center_x
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dy = y - center_y
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distance_from_center = (dx * dx + dy * dy) ** 0.5
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distance_weight = 1.0 - (distance_from_center / search_radius) * 0.5
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distance_weight = max(0.5, distance_weight)
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score = rgb_sum * distance_weight
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if score > max_score:
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max_score = score
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candidate_pos = (x, y)
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# 如果没有找到候选点，直接返回
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if candidate_pos is None:
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return None
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# 第二阶段：在候选点周围进行精细搜索（1像素间隔）
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# 在候选点周围 5x5 或 7x7 区域内找最亮的点
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refine_radius = 3 # 精细搜索半径（像素）
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cx, cy = candidate_pos
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x_min_fine = max(0, cx - refine_radius)
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x_max_fine = min(w, cx + refine_radius + 1)
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y_min_fine = max(0, cy - refine_radius)
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y_max_fine = min(h, cy + refine_radius + 1)
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max_brightness = 0
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best_pos = candidate_pos
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# 精细搜索：1像素间隔，只考虑亮度（RGB总和）
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for y in range(y_min_fine, y_max_fine, 1):
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for x in range(x_min_fine, x_max_fine, 1):
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idx = (y * w + x) * 3
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r, g, b = img_bytes[idx], img_bytes[idx+1], img_bytes[idx+2]
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# 判断是否为红色或过曝的红色
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is_red = False
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is_overexposed_red = False
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if r > threshold and r > g * 2 and r > b * 2:
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is_red = True
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elif r > 200 and g > 200 and b > 200:
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if r >= g and r >= b and (r - g) > 10 and (r - b) > 10:
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is_overexposed_red = True
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if is_red or is_overexposed_red:
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rgb_sum = r + g + b
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# 精细搜索阶段只考虑亮度，不考虑距离权重
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if rgb_sum > max_brightness:
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max_brightness = rgb_sum
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best_pos = (x, y)
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return best_pos
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def calibrate_laser_position(self):
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"""执行一次激光校准：拍照 → 找红点 → 保存坐标"""
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time.sleep_ms(80)
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85
main.py
85
main.py
@@ -23,17 +23,91 @@ from logger_manager import logger_manager
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from time_sync import sync_system_time_from_4g
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from power import init_ina226, get_bus_voltage, voltage_to_percent
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from laser_manager import laser_manager
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from vision import detect_circle_v3, estimate_distance, compute_laser_position, save_shot_image
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from vision import detect_circle_v3, estimate_distance, compute_laser_position, save_shot_image, save_calibration_image
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from network import network_manager
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from ota_manager import ota_manager
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from hardware import hardware_manager
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# def laser_calibration_worker():
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# """后台线程：持续检测是否需要执行激光校准"""
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# from maix import camera
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# from laser_manager import laser_manager
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# from ota_manager import ota_manager
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# logger = logger_manager.logger
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# if logger:
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# logger.info("[LASER] 激光校准线程启动")
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# while True:
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# try:
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# try:
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# if ota_manager.ota_in_progress:
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# time.sleep_ms(200)
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# continue
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# except Exception as e:
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# logger = logger_manager.logger
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# if logger:
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# logger.error(f"[LASER] OTA检查异常: {e}")
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# time.sleep_ms(200)
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# continue
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# if laser_manager.calibration_active:
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# cam = None
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# try:
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# cam = camera.Camera(640, 480)
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# start = time.ticks_ms()
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# timeout_ms = 8000
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# while laser_manager.calibration_active and time.ticks_diff(time.ticks_ms(), start) < timeout_ms:
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# frame = cam.read()
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# pos = laser_manager.find_red_laser(frame)
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# if pos:
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# laser_manager.set_calibration_result(pos)
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# laser_manager.stop_calibration()
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# laser_manager.save_laser_point(pos)
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# logger = logger_manager.logger
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# if logger:
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# logger.info(f"✅ 后台校准成功: {pos}")
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# break
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# time.sleep_ms(60)
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# except Exception as e:
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# logger = logger_manager.logger
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# if logger:
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# logger.error(f"[LASER] calibration error: {e}")
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# import traceback
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# logger.error(traceback.format_exc())
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# time.sleep_ms(200)
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# finally:
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# try:
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# if cam is not None:
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# del cam
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# except Exception as e:
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# logger = logger_manager.logger
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# if logger:
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# logger.error(f"[LASER] 释放相机资源异常: {e}")
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# if laser_manager.calibration_active:
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# time.sleep_ms(300)
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# else:
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# time.sleep_ms(50)
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# except Exception as e:
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# # 线程顶层异常捕获，防止线程静默退出
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# logger = logger_manager.logger
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# if logger:
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# logger.error(f"[LASER] 校准线程异常: {e}")
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# import traceback
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# logger.error(traceback.format_exc())
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# else:
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# print(f"[LASER] 校准线程异常: {e}")
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# import traceback
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# traceback.print_exc()
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# time.sleep_ms(1000) # 等待1秒后继续
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def laser_calibration_worker():
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"""后台线程：持续检测是否需要执行激光校准"""
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from maix import camera
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from laser_manager import laser_manager
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from ota_manager import ota_manager
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from vision import save_calibration_image # 添加导入
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logger = logger_manager.logger
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if logger:
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@@ -62,6 +136,14 @@ def laser_calibration_worker():
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frame = cam.read()
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pos = laser_manager.find_red_laser(frame)
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if pos:
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# 保存校准图像（带标注）
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try:
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save_calibration_image(frame, pos)
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except Exception as e:
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logger = logger_manager.logger
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if logger:
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logger.error(f"[LASER] 保存校准图像失败: {e}")
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laser_manager.set_calibration_result(pos)
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laser_manager.stop_calibration()
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laser_manager.save_laser_point(pos)
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@@ -103,7 +185,6 @@ def laser_calibration_worker():
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traceback.print_exc()
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time.sleep_ms(1000) # 等待1秒后继续
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def cmd_str():
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"""主程序入口"""
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# ==================== 第一阶段：硬件初始化 ====================
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75
vision.py
75
vision.py
@@ -12,6 +12,81 @@ from maix import image
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import config
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from logger_manager import logger_manager
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def save_calibration_image(frame, laser_pos, photo_dir=None):
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"""
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保存激光校准图像（带标注）
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在找到的激光点位置绘制圆圈，便于检查算法是否正确
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Args:
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frame: 原始图像帧
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laser_pos: 找到的激光点坐标 (x, y)
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photo_dir: 照片存储目录，如果为None则使用 config.PHOTO_DIR
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Returns:
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str: 保存的文件路径，如果保存失败则返回 None
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"""
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# 检查是否启用图像保存
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if not config.SAVE_IMAGE_ENABLED:
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return None
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if photo_dir is None:
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photo_dir = config.PHOTO_DIR
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try:
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# 确保照片目录存在
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try:
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if photo_dir not in os.listdir("/root"):
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os.mkdir(photo_dir)
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except:
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pass
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# 生成文件名
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try:
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all_images = [f for f in os.listdir(photo_dir) if f.endswith(('.bmp', '.jpg', '.jpeg'))]
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img_count = len(all_images)
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except:
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img_count = 0
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x, y = laser_pos
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filename = f"{photo_dir}/calibration_{int(x)}_{int(y)}_{img_count:04d}.bmp"
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logger = logger_manager.logger
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if logger:
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logger.info(f"保存校准图像: {filename}, 激光点: ({x}, {y})")
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# 转换图像为 OpenCV 格式以便绘制
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img_cv = image.image2cv(frame, False, False)
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# 绘制激光点圆圈（用绿色圆圈标出找到的激光点）
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cv2.circle(img_cv, (int(x), int(y)), 10, (0, 255, 0), 2) # 外圈：绿色，半径10
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cv2.circle(img_cv, (int(x), int(y)), 5, (0, 255, 0), 2) # 中圈：绿色，半径5
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cv2.circle(img_cv, (int(x), int(y)), 2, (0, 255, 0), -1) # 中心点：绿色实心
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# 可选：绘制十字线帮助定位
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cv2.line(img_cv,
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(int(x - 20), int(y)),
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(int(x + 20), int(y)),
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(0, 255, 0), 1) # 水平线
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cv2.line(img_cv,
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(int(x), int(y - 20)),
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(int(x), int(y + 20)),
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(0, 255, 0), 1) # 垂直线
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# 转换回 MaixPy 图像格式并保存
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result_img = image.cv2image(img_cv, False, False)
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result_img.save(filename)
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if logger:
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logger.debug(f"校准图像已保存: {filename}")
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return filename
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except Exception as e:
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logger = logger_manager.logger
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if logger:
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logger.error(f"保存校准图像失败: {e}")
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import traceback
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logger.error(traceback.format_exc())
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return None
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def detect_circle_v3(frame, laser_point=None):
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"""检测图像中的靶心（优先清晰轮廓，其次黄色区域）- 返回椭圆参数版本
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Reference in New Issue
Block a user