比赛记录

这个是在openmv的代码，请帮我修改为使用USB摄像头连接运行在pycharm中的py代码。 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 import time, os, sys import math from media.sensor import * from media.display import * from media.media import * # 自定义 hypot 函数 def hypot(x, y): return math.sqrt(x**2 + y**2) # 角度计算函数 def calculate_angle(p1, p2, p3): a2 = (p2[0] - p3[0])**2 + (p2[1] - p3[1])** 2 b2 = (p1[0] - p3[0])**2 + (p1[1] - p3[1])** 2 c2 = (p1[0] - p2[0])**2 + (p1[1] - p2[1])** 2 if a2 == 0 or c2 == 0: return 0 cos_angle = (a2 + c2 - b2) / (2 * (a2**0.5) * (c2**0.5)) cos_angle = max(-1.0, min(1.0, cos_angle)) return math.degrees(math.acos(cos_angle)) # 点是否在多边形内（射线法） def point_in_polygon(point, polygon): x, y = point n = len(polygon) inside = False for i in range(n): j = (i + 1) % n xi, yi = polygon[i] xj, yj = polygon[j] if ((yi > y) != (yj > y)): t = (y - yi) / (yj - yi) if (yj - yi) != 0 else 0 x_intersect = xi + t * (xj - xi) if x < x_intersect: inside = not inside return inside # 计算点到线段的距离 def point_to_line_distance(point, line_start, line_end): x, y = point x1, y1 = line_start x2, y2 = line_end # 线段长度的平方 line_len_sq = (x2 - x1)**2 + (y2 - y1)**2 # 如果线段实际上是一个点，则返回点之间的距离 if line_len_sq == 0: return hypot(x - x1, y - y1) # 考虑线段参数化表示：0 <= t <= 1 t = ((x - x1) * (x2 - x1) + (y - y1) * (y2 - y1)) / line_len_sq if t < 0: return hypot(x - x1, y - y1) # 投影在起点之前 elif t > 1: return hypot(x - x2, y - y2) # 投影在终点之后 else: # 投影在线段上 proj_x = x1 + t * (x2 - x1) proj_y = y1 + t * (y2 - y1) return hypot(x - proj_x, y - proj_y) # 判断两个矩形是否嵌套且满足最小间隔要求 def is_nested_with_min_distance(rect1, rect2, min_distance=10): # 检查是否嵌套 rect1_in_rect2 = all(point_in_polygon(p, rect2) for p in rect1) rect2_in_rect1 = all(point_in_polygon(p, rect1) for p in rect2) if not (rect1_in_rect2 or rect2_in_rect1): return False # 确定内外矩形 outer_rect = rect2 if rect1_in_rect2 else rect1 inner_rect = rect1 if rect1_in_rect2 else rect2 # 计算所有边之间的最小距离 min_dist = float('inf') # 对于内矩形的每条边 for i in range(4): inner_start = inner_rect[i] inner_end = inner_rect[(i+1)%4] # 对于外矩形的每条边 for j in range(4): outer_start = outer_rect[j] outer_end = outer_rect[(j+1)%4] # 计算内矩形边的两个端点到外矩形边的距离 d1 = point_to_line_distance(inner_start, outer_start, outer_end) d2 = point_to_line_distance(inner_end, outer_start, outer_end) # 计算外矩形边的两个端点到内矩形边的距离 d3 = point_to_line_distance(outer_start, inner_start, inner_end) d4 = point_to_line_distance(outer_end, inner_start, inner_end) # 更新最小距离 current_min = min(d1, d2, d3, d4) if current_min < min_dist: min_dist = current_min # 检查是否满足最小距离要求 return min_dist >= min_distance # 计算多边形的像素面积（鞋带公式） def calculate_pixel_area(rect): area = 0 n = len(rect) for i in range(n): x_i, y_i = rect[i] x_j, y_j = rect[(i + 1) % n] area += (x_i * y_j - x_j * y_i) return abs(area) / 2 # 判断矩形是否为正方形（四边长度相近且四角为直角） def is_square(rect, angle_threshold=15, side_threshold=0.1): if len(rect) != 4: return False # 计算四条边的长度 sides = [] for i in range(4): p1, p2 = rect[i], rect[(i+1)%4] side_length = hypot(p2[0] - p1[0], p2[1] - p1[1]) sides.append(side_length) # 检查四边是否相近（误差不超过10%） max_side = max(sides) min_side = min(sides) if min_side / max_side < (1 - side_threshold): return False # 检查四个角是否为直角 for i in range(4): p1, p2, p3 = rect[i], rect[(i+1)%4], rect[(i+2)%4] angle = calculate_angle(p1, p2, p3) if abs(angle - 90) > angle_threshold: return False return True sensor_id = 2 sensor = None picture_width = 800 picture_height = 480 ANGLE_THRESHOLD = 15 # 矩形角度阈值 A4_WIDTH = 210 # 最外圈矩形实际宽度(mm) A4_HEIGHT = 297 # 最外圈矩形实际高度(mm) A4_ACTUAL_AREA = A4_WIDTH * A4_HEIGHT # 最外圈矩形实际面积：62370 mm² roi=(300, 50, 200, 380) # ROI区域：(x, y, width, height) # 显示模式选择 DISPLAY_MODE = "LCD" # 嵌套矩形最小间隔(像素) MIN_RECT_DISTANCE = 8 # 可根据实际情况调整 # 显示宽高配置 if DISPLAY_MODE == "VIRT": DISPLAY_WIDTH = ALIGN_UP(1920, 16) DISPLAY_HEIGHT = 1080 elif DISPLAY_MODE == "LCD": DISPLAY_WIDTH = 800 DISPLAY_HEIGHT = 480 elif DISPLAY_MODE == "HDMI": DISPLAY_WIDTH = 1920 DISPLAY_HEIGHT = 1080 else: raise ValueError("未知的 DISPLAY_MODE，请选择 'VIRT', 'LCD' 或 'HDMI'") try: # 初始化摄像头 sensor = Sensor(id=sensor_id) sensor.reset() sensor.set_hmirror(False) sensor.set_vflip(False) sensor.set_framesize(width=picture_width, height=picture_height, chn=CAM_CHN_ID_0) sensor.set_pixformat(Sensor.GRAYSCALE, chn=CAM_CHN_ID_0) # 初始化显示器 if DISPLAY_MODE == "VIRT": Display.init(Display.VIRT, width=DISPLAY_WIDTH, height=DISPLAY_HEIGHT, fps=60) elif DISPLAY_MODE == "LCD": Display.init(Display.ST7701, width=DISPLAY_WIDTH, height=DISPLAY_HEIGHT, to_ide=True) elif DISPLAY_MODE == "HDMI": Display.init(Display.LT9611, width=DISPLAY_WIDTH, height=DISPLAY_HEIGHT, to_ide=True) MediaManager.init() sensor.run() fps = time.clock() while True: fps.tick() os.exitpoint() # 捕获图像并二值化 src_img = sensor.snapshot(chn=CAM_CHN_ID_0) src_img.binary([(120, 255)], invert=False) # 将ROI区域外的部分涂成黑色 src_img.draw_rectangle(0, 0, picture_width, roi[1], color=0, fill=True) src_img.draw_rectangle(0, roi[1]+roi[3], picture_width, picture_height - (roi[1]+roi[3]), color=0, fill=True) src_img.draw_rectangle(0, roi[1], roi[0], roi[3], color=0, fill=True) src_img.draw_rectangle(roi[0]+roi[2], roi[1], picture_width - (roi[0]+roi[2]), roi[3], color=0, fill=True) # 查找符合条件的矩形 rects = src_img.find_rects(threshold=3500) rectangle_corners_list = [] # 存储所有矩形 for rect in rects: corners = rect.corners() if len(corners) != 4: continue # 过滤过小矩形 length1 = hypot(corners[1][0]-corners[0][0], corners[1][1]-corners[0][1]) length2 = hypot(corners[2][0]-corners[1][0], corners[2][1]-corners[1][1]) if length1 < 20 or length2 < 20: continue # 验证直角 is_rectangle = True for i in range(4): p1, p2, p3 = corners[i], corners[(i+1)%4], corners[(i+2)%4] angle = calculate_angle(p1, p2, p3) if abs(angle - 90) > ANGLE_THRESHOLD: is_rectangle = False break if is_rectangle: rectangle_corners_list.append(corners) # 检测嵌套矩形并判断内圈是否为正方形 nested_count = 0 nested_pairs = [] # 存储嵌套矩形对 m = len(rectangle_corners_list) for i in range(m): for j in range(i + 1, m): rect_a, rect_b = rectangle_corners_list[i], rectangle_corners_list[j] # 使用新的嵌套检测函数，加入最小间隔判断 if is_nested_with_min_distance(rect_a, rect_b, MIN_RECT_DISTANCE): nested_count += 1 nested_pairs.append((rect_a, rect_b)) # 仅在恰好检测到一组嵌套矩形且内圈为正方形时输出 if nested_count == 1: rect_a, rect_b = nested_pairs[0] # 区分内外圈（按面积） a_area = calculate_pixel_area(rect_a) b_area = calculate_pixel_area(rect_b) outer_rect = rect_a if a_area > b_area else rect_b inner_rect = rect_b if a_area > b_area else rect_a # 判断内圈是否为正方形 if is_square(inner_rect): # 计算转换系数（最外圈实际面积 / 最外圈像素面积） outer_pixel_area = calculate_pixel_area(outer_rect) if outer_pixel_area == 0: continue conversion_factor = A4_ACTUAL_AREA / outer_pixel_area # 计算正方形的实际面积 square_pixel_area = calculate_pixel_area(inner_rect) square_actual_area = square_pixel_area * conversion_factor # 输出结果 print("检测到嵌套矩形内有正方形：") print(f" 最外圈矩形像素面积：{outer_pixel_area:.1f} 像素") print(f" 正方形像素面积：{square_pixel_area:.1f} 像素") print(f" 正方形实际面积：{square_actual_area:.1f} mm²") print(f" 内外矩形最小间隔：{MIN_RECT_DISTANCE} 像素") print("------------------------") # 显示图像 Display.show_image(src_img, x=0, y=0, layer=Display.LAYER_OSD1) except KeyboardInterrupt as e: print("用户停止: ", e) except BaseException as e: print(f"异常: {e}") finally: if isinstance(sensor, Sensor): sensor.stop() Display.deinit() os.exitpoint(os.EXITPOINT_ENABLE_SLEEP) time.sleep_ms(100) MediaManager.deinit() title: OpenMV 代码改为 PyCharm + USB 摄像头方案

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