diff --git a/move_warn/t2.py b/move_warn/t2.py new file mode 100644 index 0000000..3594004 --- /dev/null +++ b/move_warn/t2.py @@ -0,0 +1,97 @@ +import cv2 +import numpy as np +from winsound import PlaySound,SND_ALIAS,SND_ASYNC +from time import time +# Beep(500,500) + +# camera = cv2.VideoCapture(0) # 参数0表示第一个摄像头 +# camera = cv2.VideoCapture("opt.flv") +camera = cv2.VideoCapture("http://192.168.124.17:8081/live.flv") +# 判断视频是否打开 +if (camera.isOpened()): + print('Open') +else: + print('摄像头未打开') + +# 测试用,查看视频size +size = (int(camera.get(cv2.CAP_PROP_FRAME_WIDTH)), int(camera.get(cv2.CAP_PROP_FRAME_HEIGHT))) +print('size:'+repr(size)) + +es = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (9, 4)) +kernel = np.ones((5, 5), np.uint8) +background = None +cnt = 0 +tot = 0 +last = time() +mask = np.array([(0, 0),(282, 0),(282, 26),(0, 26)]) + +# cv2.waitKey(5) + +while True: +# 读取视频流 + try: + grabbed, frame_lwpCV = camera.read() + cv2.waitKey(5) + cv2.fillConvexPoly(frame_lwpCV, mask,(0,255,0)) + cv2.imshow("src",frame_lwpCV) + except cv2.error: + print("ignore this frame") + continue +# 对帧进行预处理，先转灰度图，再进行高斯滤波。 +# 用高斯滤波进行模糊处理，进行处理的原因：每个输入的视频都会因自然震动、光照变化或者摄像头本身等原因而产生噪声。对噪声进行平滑是为了避免在运动和跟踪时将其检测出来。 + gray_lwpCV = cv2.cvtColor(frame_lwpCV, cv2.COLOR_BGR2GRAY) + gray_lwpCV = cv2.GaussianBlur(gray_lwpCV, (21, 21), 0) +# 将第一帧设置为整个输入的背景 + if background is None: + background = gray_lwpCV + continue +# 对于每个从背景之后读取的帧都会计算其与北京之间的差异，并得到一个差分图（different map）。 +# 还需要应用阈值来得到一幅黑白图像，并通过下面代码来膨胀（dilate）图像，从而对孔（hole）和缺陷（imperfection）进行归一化处理 + diff = cv2.absdiff(background, gray_lwpCV) + # cv2.imshow('abs', diff) + diff = cv2.threshold(diff, 25, 255, cv2.THRESH_BINARY)[1] # 二值化阈值处理 + diff = cv2.dilate(diff, es, iterations=2) # 形态学膨胀 +# 显示矩形框 + contours, hierarchy = cv2.findContours(diff.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE) # 该函数计算一幅图像中目标的轮廓 + contours = [c for c in contours if cv2.contourArea(c) >= 1500] + # 对于矩形区域，只显示大于给定阈值的轮廓，所以一些微小的变化不会显示。对于光照不变和噪声低的摄像头可不设定轮廓最小尺寸的阈值 + total=0 + for c in contours: + # if cv2.contourArea(c) < 1500: + # continue + total += cv2.contourArea(c) + (x, y, w, h) = cv2.boundingRect(c) # 该函数计算矩形的边界框 + cv2.rectangle(frame_lwpCV, (x, y), (x+w, y+h), (0, 255, 0), 2) + + cv2.imshow('contours', frame_lwpCV) + cv2.imshow('dis', diff) + + if len(contours)>0 and total>10000: + cnt+=1 + if cnt > 5: + if time()-last<5: + print(time(),last) + tot+=1 + else: + print("else: ",time(),last) + tot = 1 + last = time() + cnt = 0 + print("################################") + PlaySound("SystemAsterisk",SND_ALIAS|SND_ASYNC) + background = gray_lwpCV + else: + cnt=cnt-1 if cnt>0 else 0 + + if tot>4: + PlaySound("SystemHand",SND_ALIAS) + exit() + + key = cv2.waitKey(1) & 0xFF +# 按'L'健退出循环 + if key == ord('L'): + break + + +camera.release() +cv2.destroyAllWindows() diff --git a/recode/Output/test.txt b/recode/Output/test.txt new file mode 100644 index 0000000..da01559 --- /dev/null +++ b/recode/Output/test.txt @@ -0,0 +1 @@ +ASD¼Ñ¼ÑDSA \ No newline at end of file diff --git a/recode/test.txt b/recode/test.txt new file mode 100644 index 0000000..9b880cb --- /dev/null +++ b/recode/test.txt @@ -0,0 +1 @@ +ASDѼDSA \ No newline at end of file diff --git a/wjx/tmp.html b/wjx/tmp.html new file mode 100644 index 0000000..0219f13 --- /dev/null +++ b/wjx/tmp.html @@ -0,0 +1,275 @@ + + + + + + + 登录页面_问卷星 + + + + + + + + +
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