|
| rmse.a = normal[0] |
|
| rmse.b = normal[1] |
|
| rmse.c = normal[2] |
|
| rmse.C_x = np.cov(xyz.T) |
|
| rmse.colorized = cv.applyColorMap(i8, cv.COLORMAP_JET) |
|
| rmse.crop = orig[int(my):int(My), int(mx):int(Mx)].astype(np.float) |
|
| rmse.d = -np.dot(point, normal) |
|
| rmse.Dcrop = np.zeros_like(crop).astype(np.float) |
|
| rmse.direction_vector = eig_vecs[:, min_eig_val_index].copy() |
|
| rmse.dist = abs(a * x + b * y + c * z + d)/e |
|
| rmse.Dmap = np.dstack((Dcrop, Dcrop, Dcrop)) |
|
| rmse.e = math.sqrt(a * a + b * b + c * c) |
|
| rmse.eig_vals |
|
| rmse.eig_vecs |
|
| rmse.f = open(filename,"r") |
|
| rmse.file_extension |
|
string | rmse.filename = "D:/dataset/gt-4622.png" |
|
| rmse.fname |
|
| rmse.font = cv.FONT_HERSHEY_COMPLEX_SMALL |
|
int | rmse.height = 0 |
|
list | rmse.i = [] |
|
tuple | rmse.i8 = (i * 255.0).astype(np.uint8) |
|
| rmse.im = colorized.copy() |
|
int | rmse.key = cv.waitKey(100)&0xFF |
|
| rmse.m = np.percentile(i, 5) |
|
| rmse.M = np.percentile(i, 95) |
|
| rmse.min_eig_val_index = np.argmin(eig_vals) |
|
int | rmse.mx = 0 |
|
int | rmse.Mx = 0 |
|
int | rmse.my = 0 |
|
int | rmse.My = 0 |
|
| rmse.normal = direction_vector/np.linalg.norm(direction_vector) |
|
| rmse.orig = i.copy() |
|
| rmse.point = np.mean(xyz, axis=0) |
|
| rmse.rmse = math.sqrt(variance) |
|
int | rmse.rmse_mm = rmse*1000 |
|
| rmse.size = i.shape[0] |
|
| rmse.variance = np.min(eig_vals) |
|
int | rmse.width = 0 |
|
list | rmse.X = [] |
|
tuple | rmse.x = (float(j) / width - 0.5)*z |
|
int | rmse.x0 = 0 |
|
int | rmse.x1 = 0 |
|
| rmse.Xcrop = np.zeros_like(crop).astype(np.float) |
|
int | rmse.xx = 0 |
|
| rmse.xyz = np.dstack((X, Y, Z)) |
|
list | rmse.Y = [] |
|
tuple | rmse.y = (float(i) / height - 0.5)*z |
|
int | rmse.y0 = 0 |
|
int | rmse.y1 = 0 |
|
| rmse.Ycrop = np.zeros_like(crop).astype(np.float) |
|
int | rmse.yy = 0 |
|
list | rmse.Z = [] |
|
float | rmse.z = crop[i - my, j - mx]*0.001 |
|
| rmse.Zcrop = np.zeros_like(crop).astype(np.float) |
|