openmv 识别直角
- import sensor
- import image
- import time
- import math
- import pyb
- from pyb import Pin, Timer, UART,LED
- from GeometryFeature import GeometryFeature
- # 当光线弱的时候，用于补光
- LED(4).on()
- # 是否开启debug模式
- # 如果是False就不print, 不进行可视化绘制，可以提高帧率
- is_debug = True
- #--------------感光芯片配置 START -------------------
- DISTORTION_FACTOR = 1.5 # 设定畸变系数
- IMG_WIDTH = 64
- IMG_HEIGHT = 64
- def init_sensor():
- '''
- 初始化感光芯片
- '''
- sensor.reset()
- sensor.set_pixformat(sensor.GRAYSCALE)
- sensor.set_framesize(sensor.B64X64) # 分辨率为B64X64
- sensor.skip_frames(time=2000)
- sensor.set_auto_gain(False) # 颜色追踪关闭自动增益
- sensor.set_auto_whitebal(False) # 颜色追踪关闭白平衡
- init_sensor()
- #--------------感光芯片配置 END -------------------
- #--------------定时器部分 START -------------------
- is_need_send_data = False # 是否需要发送数据的信号标志
- def uart_time_trigger(timer):
- '''
- 串口发送数据的定时器，定时器的回调函数
- '''
- global is_need_send_data
- is_need_send_data = True
- # 初始化定时器 频率为20HZ 每秒执行20次
- tim = Timer(4, freq=20)
- # 设定定时器的回调函数
- tim.callback(uart_time_trigger)
- #--------------定时器部分 END -------------------
- #--------------直线与直角检测部分 START -------------------
- INTERSERCT_ANGLE_THRESHOLD = (45,90)
- # 直线灰度图颜色阈值
- LINE_COLOR_THRESHOLD = [(0, 120)]
- # 如果直线是白色的，阈值修改为：
- # LINE_COLOR_THRESHOLD = [(128, 255)]
- # 取样窗口
- ROIS = {
- 'down': (0, 55, 64, 8), # 横向取样-下方 1
- 'middle': (0, 28, 64, 8), # 横向取样-中间 2
- 'up': (0, 0, 64, 8), # 横向取样-上方 3
- 'left': (0, 0, 8, 64), # 纵向取样-左侧 4
- 'right': (56, 0, 8, 64) # 纵向取样-右侧 5
- }
- BLOB_MAX_WIDTH = 15 # 色块的最大宽度
- BLOB_MIN_WIDTH = 5 # 色块的最小宽度
- BLOB_MAX_HEIGHT = 15 # 色块的最大高度
- BLOB_MIN_HEIGHT = 5 # 色块的最小宽度
- def find_blobs_in_rois(img):
- '''
- 在ROIS中寻找色块，获取ROI中色块的中心区域与是否有色块的信息
- '''
- global ROIS
- global is_debug
- roi_blobs_result = {} # 在各个ROI中寻找色块的结果记录
- for roi_direct in ROIS.keys():
- roi_blobs_result[roi_direct] = {
- 'cx': -1,
- 'cy': -1,
- 'blob_flag': False
- }
- for roi_direct, roi in ROIS.items():
- blobs=img.find_blobs(LINE_COLOR_THRESHOLD, roi=roi, merge=True, pixels_area=10)
- if len(blobs) == 0:
- continue
- largest_blob = max(blobs, key=lambda b: b.pixels())
- x,y,width,height = largest_blob[:4]
- if not(width >= BLOB_MIN_WIDTH and width <= BLOB_MAX_WIDTH and height >= BLOB_MIN_HEIGHT and height <= BLOB_MAX_HEIGHT):
- # 根据色块的宽度进行过滤
- continue
- roi_blobs_result[roi_direct]['cx'] = largest_blob.cx()
- roi_blobs_result[roi_direct]['cy'] = largest_blob.cy()
- roi_blobs_result[roi_direct]['blob_flag'] = True
- if is_debug:
- img.draw_rectangle((x,y,width, height), color=(255))
- return roi_blobs_result
- def visualize_result(canvas, cx_mean, cx, cy, is_turn_left, is_turn_right, is_t, is_cross):
- '''
- 可视化结果
- '''
- if not(is_turn_left or is_turn_right or is_t or is_cross):
- mid_x = int(canvas.width()/2)
- mid_y = int(canvas.height()/2)
- # 绘制x的均值点
- canvas.draw_circle(int(cx_mean), mid_y, 5, color=(255))
- # 绘制屏幕中心点
- canvas.draw_circle(mid_x, mid_y, 8, color=(0))
- canvas.draw_line((mid_x, mid_y, int(cx_mean), mid_y), color=(255))
- turn_type = 'N' # 啥转角也不是
- if is_t or is_cross:
- # 十字形或者T形
- canvas.draw_cross(int(cx), int(cy), size=10, color=(255))
- canvas.draw_circle(int(cx), int(cy), 5, color=(255))
- if is_t:
- turn_type = 'T' # T字形状
- elif is_cross:
- turn_type = 'C' # 十字形
- elif is_turn_left:
- turn_type = 'L' # 左转
- elif is_turn_right:
- turn_type = 'R' # 右转
- canvas.draw_string(0, 0, turn_type, color=(0))
- #--------------直线与直角检测部分 END -------------------
- #---------------------MAIN-----------------------
- last_cx = 0
- last_cy = 0
- while True:
- if not is_need_send_data:
- # 不需要发送数据
- continue
- is_need_send_data = False
- # 拍摄图片
- img = sensor.snapshot()
- # 去除图像畸变
- img.lens_corr(DISTORTION_FACTOR)
- # 创建画布
- # canvas = img.copy()
- # 为了IDE显示方便，直接在代码结尾 用IMG绘制
- # 注意：林林的代码里 计算直线之间的交点的代码没有用到
- lines = img.find_lines(threshold=1000, theta_margin = 50, rho_margin = 50)
- # 寻找相交的点 要求满足角度阈值
- intersect_pt = GeometryFeature.find_interserct_lines(lines, angle_threshold=(45,90), window_size=(IMG_WIDTH, IMG_HEIGHT))
- if intersect_pt is None:
- # 直线与直线之间的夹角不满足阈值范围
- intersect_x = 0
- intersect_y = 0
- else:
- intersect_x, intersect_y = intersect_pt
- reslut = find_blobs_in_rois(img)
- # 判断是否需要左转与右转
- is_turn_left = False
- is_turn_right = False
- if (not reslut['up']['blob_flag'] ) and reslut['down']['blob_flag']:
- if reslut['left']['blob_flag']:
- is_turn_left = True
- if reslut['right']['blob_flag']:
- is_turn_right = True
- # 判断是否为T形的轨道
- is_t = False
- # 判断是否十字形轨道
- is_cross = False
- cnt = 0
- for roi_direct in ['up', 'down', 'left', 'right']:
- if reslut[roi_direct]['blob_flag']:
- cnt += 1
- is_t = cnt == 3
- is_cross = cnt == 4
- # cx_mean 用于确定视角中的轨道中心
- # 用于表示左右偏移量
- cx_mean = 0
- for roi_direct in ['up', 'down', 'middle']:
- if reslut[roi_direct]['blob_flag']:
- cx_mean += reslut[roi_direct]['cx']
- else:
- cx_mean += IMG_WIDTH / 2
- cx_mean /= 3
- # cx, cy 只有在T形区域检测出来的时候才有用，
- # 用于确定轨道中圆形的大致区域， 用于定点， 是计算圆心的一种近似方法
- cx = 0
- cy = 0
- if is_cross or is_t:
- # 只在出现十字形或者T字形才计算圆心坐标
- cnt = 0
- for roi_direct in ['up', 'down']:
- if reslut[roi_direct]['blob_flag']:
- cnt += 1
- cx += reslut[roi_direct]['cx']
- if cnt == 0:
- cx = last_cx
- else:
- cx /= cnt
- cnt = 0
- for roi_direct in ['left', 'right']:
- if reslut[roi_direct]['blob_flag']:
- cnt += 1
- cy += reslut[roi_direct]['cy']
- if cnt == 0:
- cy = last_cy
- else:
- cy /= cnt
- last_cx = cx
- last_cy = cy
- if is_debug:
- visualize_result(img, cx_mean, cx, cy, is_turn_left, is_turn_right, is_t, is_cross)
所有资料51hei提供下载:
源代码.rar
(7.31 KB, 下载次数: 160)
|
[复制链接]
