BocceBallDL/CamUtils.py at main · RustinS/BocceBallDL · GitHub

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
import numpy as np
import cv2
import yaml
import imutils


def calibration(nx, ny, path, numexamples):
    objpoints = []
    imgpoints = []
    objp = np.zeros((nx*ny,3), np.float32)
    for _ in range(1):
        for i in range(1,numexamples+1):
            print(i)
            if i <= 4 :
                fname = path + '%s.png'%i
                img = cv2.imread(fname)
                gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
            else:
                fname = path + '%s.png'%i
                img = cv2.imread(fname)
                gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
            ret, corners = cv2.findChessboardCorners(gray, (nx, ny), None)

            objp[:,:2] = np.mgrid[0:27,0:9].T.reshape(-1,2)
            imgp = corners

            cv2.drawChessboardCorners(img, (7,6), imgp, ret)
            cv2.imshow('img', img)
            cv2.waitKey(500)

            if ret == True:
                imgpoints.append(imgp)
                objpoints.append(objp)

    return objpoints,imgpoints


def get_parametrs(nx, ny, train_path, n):
    objpoints,imgpoints = calibration(nx,ny,train_path,n)
    ret, mtx, dist, rvecs, tvecs = cv2.calibrateCamera(objpoints, imgpoints,(1080, 3), None, None)
    save_parametes(ret, mtx, dist, rvecs, tvecs)
    return ret, mtx, dist, rvecs, tvecs


def save_parametes(ret, mtx, dist, rvecs, tvecs):
    data = {'camera_matrix': np.asarray(mtx).tolist(),
        'dist_coeff': np.asarray(dist).tolist()}
    with open("calibration_matrix.yaml", "w") as f:
         yaml.dump(data, f)


def load_parametrs(path):
    if path == '':
        with open("calibration_matrix.yaml", "r") as f:
            data = yaml.load(f, Loader=yaml.FullLoader)
            return data
    else:
        with open(path, 'r') as f:
            data = yaml.load(f, Loader=yaml.FullLoader)
            return data


def undistorter(img, data):
    mtx = data['camera_matrix']
    dist = data['dist_coeff']
    h, w =  img.shape[:2]

    mtx = np.array(mtx)
    dist = np.array(dist)
    newcameramtx, roi = cv2.getOptimalNewCameraMatrix(mtx,dist,(w,h),0,(w,h))
    dst = cv2.undistort(img, mtx, dist, None, newcameramtx)

    x,y,w,h = roi
    dst = dst[y:y+h, x:x+w]

    height = 1088
    width = int((height / dst.shape[0]) * dst.shape[1])

    xScale = width / dst.shape[1]
    yScale = height / dst.shape[0]

    xSkew = int(x * xScale)
    ySkew = int(y * yScale)

    dst = cv2.resize(dst, (width, height))
    return dst, (xSkew, ySkew), (xScale, yScale)


def getFrame(cap):
    _, frame = cap.read()

    if frame is None:
        print('frame fetch failure')
        return 0

    # frame = imutils.resize(frame, 1000)
    # frame = frame[:, 100:900]

    return frame


def cropFrameCenter1(frame, newWidth,x):

    return frame[:, int(frame.shape[1]/2-newWidth/2+x):int(frame.shape[1]/2+newWidth/2+x), :]


def cropFrameCenter2(frame, newWidth,x):

    return frame[:, int(frame.shape[1]/2-newWidth/2+x):int(frame.shape[1]/2+newWidth/2+x), :]


def cropFrameCenter3(frame, newWidth,x):

    return frame[:, int(frame.shape[1]/2-newWidth/2+x):int(frame.shape[1]/2+newWidth/2+x), :]


def cropFrameCenter4(frame, newWidth,x):

    return frame[:, int(frame.shape[1]/2-newWidth/2+x):int(frame.shape[1]/2+newWidth/2+x), :]

def cropFrameWithPoints(frame, points):
    return frame[points[3]:points[1], points[2]:points[0], :]


# rtsp = "rtsp://admin:admin123456@192.168.5.190:554/main"
# cap = cv2.VideoCapture(rtsp)
# cap.set(cv2.CAP_PROP_BUFFERSIZE, 1)
# frame = getFrame(cap)
# frame = cropFrameCenter(frame,640)
# cv2.imwrite('ff.png',frame)

# path = "calibration_matrix.yaml"
# data = load_parametrs(path)
# frame = undistorter(frame,data)
# cv2.imshow('ff',frame)
# cv2.waitKey(0)

if __name__ == '__main__':
    nx = 40
    ny = 50
    objpoints = []
    imgpoints = []
    objp = np.zeros((nx*ny,3), np.float32)

    criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 30, 0.001)

    img = cv2.imread('./chessBoard5.jpg')
    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

    cv2.imshow('a', imutils.resize(gray, 700))
    cv2.waitKey(0)
    ret, corners = cv2.findChessboardCorners(gray, (nx, ny), None)

    if ret == True:
        print(corners)
    else:
        print('No Corners')
        exit(0)

    objp[:,:2] = np.mgrid[0:nx,0:ny].T.reshape(-1,2)
    imgp = corners
    corners2 = cv2.cornerSubPix(gray,corners, (11,11), (-1,-1), criteria)

    cv2.drawChessboardCorners(img, (nx,ny), corners2, ret)
    cv2.imshow('img', imutils.resize(img, 700))
    cv2.waitKey(0)