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目录
Python + OpenCV 简单车辆统计
IDE : PyChram
函数 car_count() 简单车辆统计
- # 这是一个示例 Python 脚本。
-
- # 按 Shift+F10 执行或将其替换为您的代码。
- # 按 双击 Shift 在所有地方搜索类、文件、工具窗口、操作和设置。
- import cv2
- import numpy
- import time
-
-
- def mouse_callback(event, x, y, flags, userdata):
- print(event, x, y, flags, userdata)
-
-
- def mouse_control():
- cv2.namedWindow('mouse', cv2.WINDOW_NORMAL)
- cv2.resizeWindow('mouse', 640, 360)
- img = numpy.zeros((360, 640, 3), numpy.uint8)
- cv2.setMouseCallback('mouse', mouse_callback, '123')
- while True:
- cv2.imshow('mouse', img)
- key = cv2.waitKey(1)
- if key == ord('q'):
- break
- cv2.destroyAllWindows()
-
-
- def test():
- """
- :return:
- """
- print("hello test")
- win_name = "frame"
- cv2.namedWindow(win_name, cv2.WINDOW_NORMAL)
- cv2.resizeWindow(win_name, 640, 480)
- cap = cv2.VideoCapture(0)
- fourcc = cv2.VideoWriter_fourcc(*'mp4v')
- vm = cv2.VideoWriter('output.mp4', fourcc, 20, (640, 480))
-
- if not cap.isOpened():
- print("video capture err")
- exit()
- while True:
- ret, frame = cap.read()
-
- if ret:
- vm.write(frame)
- cv2.imshow(win_name, frame)
-
- if cv2.waitKey(1) & 0xff == ord('q'):
- break
- else:
- break
- cap.release()
- vm.release()
- cv2.destroyAllWindows()
-
-
- def test_split_merge():
- img = numpy.zeros((480, 640, 3), numpy.uint8)
- b, g, r = cv2.split(img)
- b[10:100, 10:100] = 255
- g[10:100, 10:100] = 255
-
- img2 = cv2.merge((b, g, r))
- # 在图像上绘制文本
- font = cv2.FONT_HERSHEY_SIMPLEX
- text = 'Hello, OpenCV!'
- org = (50, 50)
- font_scale = 1
-
- color = (255, 0, 0) # BGR
- thickness = 2
- cv2.putText(img, text, org, font, font_scale, color, thickness, cv2.LINE_AA)
- cv2.line(img, (10, 10), (100, 100), (255, 111, 222))
- cv2.imshow("img", numpy.hstack((img, img2)))
- cv2.waitKey(0)
- cv2.destroyAllWindows()
-
-
- def image_flip(flip_code):
- image = cv2.imread('dog.png')
- image = cv2.flip(image, flip_code)
- image = cv2.rotate(image, cv2.ROTATE_180)
- cv2.imshow('image', image)
- cv2.waitKey(0)
-
-
- def warp_affine():
- dog = cv2.imread('dog.png')
- h, w, ch = dog.shape
- # m = numpy.float32([[1, 0, 100], [0, 1, 0]])
- m = cv2.getRotationMatrix2D((w / 2, h / 2,), 15, 1.0)
- new = cv2.warpAffine(dog, m, (w, h))
- cv2.imshow('new', new)
- cv2.waitKey(0)
-
-
- def print_hi(name):
- # 在下面的代码行中使用断点来调试脚本。
- print(f'Hi, {name}') # 按 Ctrl+F8 切换断点。
- warp_affine()
-
-
- def calculate_rectangle_center(x, y, width, height):
- """
- 根据矩形的起点坐标、宽和高计算中心点的函数
- 参数:
- x, y -- 矩形起点的坐标
- width -- 矩形的宽度
- height -- 矩形的高度
- 返回:
- cx, cy -- 矩形中心点的坐标
- """
- cx = int(x + width / 2)
- cy = int(y + height / 2)
- return cx, cy
-
-
- def car_count():
- print('car count')
- count = 0
- cap = cv2.VideoCapture('./car.mp4')
- if not cap.isOpened():
- print('video open fail')
- exit()
- # 创建一个基于高斯混合模型(Gaussian Mixture Model, GMM)的背景减法器对象
- bgs = cv2.createBackgroundSubtractorMOG2()
- kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (3, 3))
-
- while True:
-
- ret, frame = cap.read()
-
- if not ret:
- # 如果到达视频末尾,则重置视频捕获对象以从头开始播放
- cap.set(cv2.CAP_PROP_POS_FRAMES, 0)
- # 重新读取第一帧
- ret, frame = cap.read()
- count = 0
- # 可选:如果不想立刻重头播放,可以在这里添加一些延时
- time.sleep(2) # 等待2秒
-
- if ret is True:
- if frame is None:
- break
- f_w = 640
- f_h = 480
- # 调整帧的大小
- resized_frame = cv2.resize(frame, (f_w, f_h), interpolation=cv2.INTER_AREA)
- # 灰度化处理
- gray = cv2.cvtColor(resized_frame, cv2.COLOR_BGR2GRAY)
-
- # 去噪
- blur = cv2.GaussianBlur(gray, (3, 3), 5)
- # 使用前面创建的背景减法器对象bgs来对一个视频帧frame进行处理
- fg_mask = bgs.apply(blur)
- # 腐蚀
- erode = cv2.erode(fg_mask, kernel)
- # 膨胀
- dilate = cv2.dilate(erode, kernel)
- # 闭运算
- close = cv2.morphologyEx(dilate, cv2.MORPH_CLOSE, kernel)
- # 查找轮廓
- contours, hierarchy = cv2.findContours(close, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
- # 绘制轮廓
- # 你可以调整第三个参数来绘制所有轮廓或只绘制特定级别的轮廓
- # -1 表示绘制所有轮廓
- # cv2.drawContours(resized_frame, contours, -1, (0, 255, 0), 3)
- # 限制宽高
- w_limit = 40
- h_limit = 40
- # 画线的起点和终点
- line_sx = 10
- line_sy = f_h - 100
- line_ex = f_w - 10
- line_ey = line_sy
- offset = 3
- # 画线
- cv2.line(resized_frame, (line_sx, line_sy), (line_ex, line_ey), (0, 0, 255), 2)
- cars = []
- for contour in contours:
- # 最大外接矩形
- (x, y, w, h) = cv2.boundingRect(contour)
- # 过滤掉小矩形
- if w < w_limit or h < h_limit:
- continue
- if y < (f_h / 2):
- continue
- # print(f"Contour: x={x}, y={y}, width={w}, height={h}")
- cv2.rectangle(resized_frame, (x, y), (x + w, y + h), (0, 255, 0), 2)
- cen_point = calculate_rectangle_center(x, y, w, h)
- cars.append(cen_point)
- cv2.circle(resized_frame, cen_point, 2, (0, 255, 0), -1)
- for (x, y) in cars:
- if (line_ey - offset) < y < (line_ey + offset):
- count += 1
- cars.remove((x, y))
- # print(count)
- cv2.putText(resized_frame, 'Cars Count:' + str(count), (50, 50), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 0, 255), 2)
- cv2.imshow('resized_frame', resized_frame)
-
- if cv2.waitKey(2) & 0xFF == 27:
- break
-
- cap.release()
- cv2.destroyAllWindows()
-
-
- # 按装订区域中的绿色按钮以运行脚本。
- if __name__ == '__main__':
- car_count()
-
- # 访问 https://www.jetbrains.com/help/pycharm/ 获取 PyCharm 帮助
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