up

Former-commit-id: 3beec1f80e66a86223b0f0f5c98a1e1405a90a29 Former-commit-id: 39d11dd75ed5b66095bb2603c54ca790236af6af
2022-10-07 13:39:52 +08:00
parent 606861b3a1
commit 3356e36e73
5 changed files with 386 additions and 0 deletions
--- a/move_warn/t2.py
+++ 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()