이재빈

modify 0421

...@@ -7,36 +7,74 @@ hog = cv2.HOGDescriptor() ...@@ -7,36 +7,74 @@ hog = cv2.HOGDescriptor()
7 hog.setSVMDetector(cv2.HOGDescriptor_getDefaultPeopleDetector()) 7 hog.setSVMDetector(cv2.HOGDescriptor_getDefaultPeopleDetector())
8 8
9 cv2.startWindowThread() 9 cv2.startWindowThread()
10 -fname = "./croppedimg/" 10 +fname = "./croppedimg/human/"
11 # open webcam video stream 11 # open webcam video stream
12 cap = cv2.VideoCapture(0) 12 cap = cv2.VideoCapture(0)
13 i = 0 13 i = 0
14 +def draw_left_path(img,x,y,w,h):
15 + start_point = x+w
16 + cv2.line(img, (320-2*w,480), (start_point, y+int(h)), (255,0,0), 8) #4픽셀 선 그리기
17 + cv2.line(img, (start_point, y+int(h)), (start_point+int(w/5),y+int(h-20)), (255, 0, 0), 10)
18 + start_point = x+2*w
19 + cv2.line(img, (540,480), (start_point, y+int(h)), (255,0,0), 8) #4픽셀 선 그리기
20 + # cv2.line(img, (start_point, y+int(h)), (start_point+int(w/5),y+int(h-20)), (255, 0, 0), 10)
21 + return img
22 +def draw_right_path(img, x, y, w, h):
23 + start_point = x
24 + cv2.line(img, (320+2*w, 480), (start_point, y+int(h)), (255, 0, 0), 8) # 8픽셀 선 그리기
25 + cv2.line(img, (start_point, y+int(h)), (start_point - int(w/5), y+int(h-20)), (255, 0, 0), 8)
26 + start_point = x-2*w
27 + cv2.line(img, (100, 480), (start_point, y + int(h)), (255, 0, 0), 8) # 8픽셀 선 그리기
28 + # cv2.line(img, (start_point, y + int(h)), (start_point - int(w / 5), y + int(h-20)), (255, 0, 0), 8)
29 + return img
14 while (True): 30 while (True):
15 # Capture frame-by-frame 31 # Capture frame-by-frame
16 start = time.time() 32 start = time.time()
17 ret, frame = cap.read() 33 ret, frame = cap.read()
18 # resizing for faster detection[240,160] [320 * 240] 34 # resizing for faster detection[240,160] [320 * 240]
19 - frame = cv2.resize(frame, (240, 160)) 35 + frame = cv2.resize(frame, (640, 480))
20 # using a greyscale picture, also for faster detection 36 # using a greyscale picture, also for faster detection
21 gray = cv2.cvtColor(frame, cv2.COLOR_RGB2GRAY) 37 gray = cv2.cvtColor(frame, cv2.COLOR_RGB2GRAY)
22 38
23 # detect people in the image 39 # detect people in the image
24 # returns the bounding boxes for the detected objects 40 # returns the bounding boxes for the detected objects
25 boxes, weights = hog.detectMultiScale(frame, winStride=(8, 8)) 41 boxes, weights = hog.detectMultiScale(frame, winStride=(8, 8))
26 - 42 + detectCount = 0
27 boxes = np.array([[x, y, x + w, y + h] for (x, y, w, h) in boxes]) 43 boxes = np.array([[x, y, x + w, y + h] for (x, y, w, h) in boxes])
28 for (xA, yA, xB, yB) in boxes: 44 for (xA, yA, xB, yB) in boxes:
29 # display the detected boxes in the colour picture 45 # display the detected boxes in the colour picture
30 cv2.rectangle(frame, (xA, yA), (xB, yB), 46 cv2.rectangle(frame, (xA, yA), (xB, yB),
31 (0, 255, 0), 2) 47 (0, 255, 0), 2)
32 - if(i%10 == 0): 48 + cv2.putText(frame, "Detect", (xA - 50, yA - 10), cv2.FONT_HERSHEY_COMPLEX_SMALL, 1, (0, 0, 255), 1)
33 - cropped = frame[yA:yB,xA:xB] 49 + detectCount = detectCount+1
34 - s = fname + str(i)+'.jpg' 50 + if(detectCount>1):
35 - cv2.imwrite(s, cropped) # IMG File Write 51 + print("Waiting...")
36 - print("time :", time.time() - start) 52 + else :
37 - print("Human Detect!") #Alert 53 + if(i%10 == 0):
38 - if(i > 200): 54 + cropped = frame[yA:yB,xA:xB]
55 + #print("xA : {0}, xB : {1}, yA : {2}, yB : {3}".format(xA, xB,yA,yB)) # Print Width, Height of Cropped Area
39 i=0 56 i=0
57 + if(xB < 380 and xA<260):
58 + print("Left Side Detect.")
59 + try:
60 + frame = draw_left_path(frame, xA,yA,xB-xA,yB-yA)
61 + except:
62 + pass
63 + elif(xA>260 and xB>380):
64 + print("Right Side Detect")
65 + try:
66 + frame = draw_right_path(frame, xA, yA, xB - xA, yB - yA)
67 + except:
68 + pass
69 + else:
70 + try:
71 + frame = draw_right_path(frame, xA, yA, xB - xA, yB - yA)
72 + except:
73 + pass
74 + print("Center Side Detect")
75 + s = fname + str(i)+'.jpg'
76 + cv2.imwrite(s, cropped) # IMG File Write
77 + print("time :", time.time() - start)
40 i= i+1 78 i= i+1
41 # Display the resulting frame 79 # Display the resulting frame
42 80
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