3d

问题 I have a bit question i couldnt solve. I wanna implement CNN model with fully-connected MLP to my protein database which has 2589 proteins. Each protein has 1287 rows and 69 columns as input and and 1287 rows and 8 columns as output. Actually there was 1287x1 output, but i used one hot encoding for class labels to use crossentropy loss in my model. Also i want if we consider as image i have an 3d matrix ** X_train = (2589, 1287, 69) for input** and y_train =(2589, 1287, 8) output , i mean

问题 I have a bit question i couldnt solve. I wanna implement CNN model with fully-connected MLP to my protein database which has 2589 proteins. Each protein has 1287 rows and 69 columns as input and and 1287 rows and 8 columns as output. Actually there was 1287x1 output, but i used one hot encoding for class labels to use crossentropy loss in my model. Also i want if we consider as image i have an 3d matrix ** X_train = (2589, 1287, 69) for input** and y_train =(2589, 1287, 8) output , i mean

问题 I have a bit question i couldnt solve. I wanna implement CNN model with fully-connected MLP to my protein database which has 2589 proteins. Each protein has 1287 rows and 69 columns as input and and 1287 rows and 8 columns as output. Actually there was 1287x1 output, but i used one hot encoding for class labels to use crossentropy loss in my model. Also i want if we consider as image i have an 3d matrix ** X_train = (2589, 1287, 69) for input** and y_train =(2589, 1287, 8) output , i mean

问题 I have 3d coordinates defining positions of points in my 3D scatter plot with a corresponding number of values who I want to create a colour scale for representing the range of values as such: from mpl_toolkits.mplot3d import Axes3D fig = plt.figure() ax = fig.add_subplot(111, projection='3d') xs,ys,zs = np.random.random(50),np.random.random(50),np.random.random(50) values = np.random.random(50)*10 p = ax.scatter3D(xs, ys, zs=zs, c=values) cbar = fig.colorbar(p) cbar.cmap(plt.cm.Greys)

问题 I am currently working on inhomogeniety removal from MRI data volume which contains voxels. I want to apply sobel operator on those volumes to find the gradient. I am familiar with 2d sobel mask and the neighbourhood of 2d images. sobel mask: 1 2 1 0 0 0 -1 -2 -1 1 0 -1 2 0 -2 1 0 -1 neighbourhood of(x,y): (x+1,y-1) (x+1,y) (x+1,y+1) (x,y-1) (x,y) (x,y+1) (x-1,y-1) (x-1,y) (x-1,y+1) Now I want to apply it on 3d. Please suggest me how should I proceed?? Thank you. 回答1: Wikipedia has a nice

问题 I am trying to implement my own 3D surface animation in JavaFX but i do not understand everything like it should works, could someone help me with understanding which should go where ? Already know that to build Mesh by using class need class object TraingleMesh and then have to add points by using method mesh.getPoints.addAll(...); but.. my Function<Double, Double> after using apply method does not help me at all, cuz the first argument has to be array float type, not double variable after

问题 I am trying to implement my own 3D surface animation in JavaFX but i do not understand everything like it should works, could someone help me with understanding which should go where ? Already know that to build Mesh by using class need class object TraingleMesh and then have to add points by using method mesh.getPoints.addAll(...); but.. my Function<Double, Double> after using apply method does not help me at all, cuz the first argument has to be array float type, not double variable after

问题 I'm trying to find the visible size of a sphere in pixels, after projection to screen space. The sphere is centered at the origin with the camera looking right at it. Thus the projected sphere should be a perfect circle in two dimensions. I am aware of this 1 existing question. However, the formula given there doesn't seem to produce the result I want. It is too small by a few percent. I assume this is because it is not correctly taking perspective into account. After projecting to screen

问题 I'm trying to find the visible size of a sphere in pixels, after projection to screen space. The sphere is centered at the origin with the camera looking right at it. Thus the projected sphere should be a perfect circle in two dimensions. I am aware of this 1 existing question. However, the formula given there doesn't seem to produce the result I want. It is too small by a few percent. I assume this is because it is not correctly taking perspective into account. After projecting to screen

问题 I'm having headaches when trying to extrude a spline to scene's origin. Here's what I'm trying to do : I'm creating a spline with let centerX = 0 let centerY = 0 let radius = 200 let coils = 50 let rotation = 2 * Math.PI let thetaMax = coils * Math.PI let awayStep = radius / thetaMax let chord = 5 let vertices = [] for (let theta = chord / awayStep; theta <= thetaMax;) { let away = awayStep * theta let around = theta + rotation let x = centerX + Math.cos(around) * away let y = centerY + Math