yanfengliu

def transform_matrix_tensor(theta, d, a, alpha):
    # tensor version of transform matrix
    matrix = [[tf.cos(theta), tf.multiply(-tf.sin(theta), tf.cos(alpha)), tf.multiply(tf.sin(theta), tf.sin(alpha)), tf.multiply(a, tf.cos(theta))], 
              [tf.sin(theta), tf.multiply(tf.cos(theta), tf.cos(alpha)), tf.multiply(-tf.cos(theta), tf.sin(alpha)), tf.multiply(a, tf.sin(theta))], 
              [tf.zeros_like(theta), tf.sin(alpha), tf.cos(alpha), d], 
              [tf.zeros_like(theta), tf.zeros_like(theta), tf.zeros_like(theta), tf.ones_like(theta)]]
    return matrix

def forward_kinematics_loss_2(y_true, y_pred):
    # y_true is the xy position

yanfengliu

def transformMatrix(theta, d, a, alpha):
    return np.array([[np.cos(theta), -np.sin(theta)*np.cos(alpha), np.sin(theta)*np.sin(alpha), a*np.cos(theta)], 
                     [np.sin(theta), np.cos(theta)*np.cos(alpha), -np.cos(theta)*np.sin(alpha), a*np.sin(theta)], 
                     [0, np.sin(alpha), np.cos(alpha), d], 
                     [0, 0, 0, 1]])

def forwardKinematics_2(theta1, theta2):
    T00 = transformMatrix(theta1,0,1,0)
    T01 = transformMatrix(theta2,0,1,0)
    pos = [0, 0, 0, 1]

yanfengliu

model = Sequential([
    Dense(256, input_shape=(2,)),
    LeakyReLU(),
    Dense(256),
    LeakyReLU(),
    Dense(256),
    LeakyReLU(),
    Dense(256),
    LeakyReLU(),
    Dense(256),

yanfengliu

def transform_matrix_tensor(theta, d, a, alpha):
    # tensor version of transform matrix
    matrix = [[tf.cos(theta), tf.multiply(-tf.sin(theta), tf.cos(alpha)), tf.multiply(tf.sin(theta), tf.sin(alpha)), tf.multiply(a, tf.cos(theta))], 
              [tf.sin(theta), tf.multiply(tf.cos(theta), tf.cos(alpha)), tf.multiply(-tf.cos(theta), tf.sin(alpha)), tf.multiply(a, tf.sin(theta))], 
              [tf.zeros_like(theta), tf.sin(alpha), tf.cos(alpha), d], 
              [tf.zeros_like(theta), tf.zeros_like(theta), tf.zeros_like(theta), tf.ones_like(theta)]]
    return matrix
  
def batch_matmul(location_v, batch_theta_v):
    # perform matrix multiplication between the location vector and the transform matrix, 

yanfengliu

import keras 
import numpy as np
from keras.models import Sequential, Model
from keras.layers import Dense, Activation, LeakyReLU, Input, Lambda, Concatenate
from keras.losses import mean_absolute_error, mean_squared_error
import os
import sys
%matplotlib inline
import matplotlib.pyplot as plt
from keras import optimizers

yanfengliu

describe("buttons", () => {
  it("can change class", () => {
    cy.getById("label_class").select("class1");
    dot_mode_coordinates_2.forEach((coordinate) => {
      cy.get("canvas").click(coordinate.x, coordinate.y);
    });
    cy.get("canvas").matchImageSnapshot("multi_class");
  });
}

yanfengliu

name: Turkey end-to-end tests chrome headless
on: [push]
jobs:
  cypress-run:
    runs-on: ubuntu-20.04
    steps:
      - uses: actions/checkout@v2
      - uses: cypress-io/github-action@v2
        with:
          start: npm start

yanfengliu

- uses: actions/upload-artifact@v1
  if: failure()
  with:
    name: cypress-screenshots
    path: cypress/screenshots
- uses: actions/upload-artifact@v1
  if: always()
  with:
    name: cypress-videos
    path: cypress/videos

yanfengliu

...
jobs:
  cypress-run:
    runs-on: ubuntu-latest
    container: cypress/included:8.0.0 # this line specifies the docker image we want
...

yanfengliu

FROM cypress/included:8.0.0
WORKDIR /app
COPY . .
RUN npm install
ENTRYPOINT ["npm", "run", "test:chrome"]