ivancorrales

# scenario-sub.hcl
scenario "operation substract" {   
   examples = [
      { x = 20, y = 10, subResult= 10},
      { x = 10, y = 20, subResult= 10},
      { x = 5, y = 5, subResult= 0},
   ]
   when "subtract y to x" {
      set result {
         value = x - y

ivancorrales

# scenario-mult.hcl
scenario "operation multiplication" {
    examples = [
      { x = 20, y = 10, multResult= 200},
      { x = -1, y = -2, multResult= 2},
      { x = 5, y = 5, multResult= 25},
      { x = 5, y = 0, multResult= 0},   
   ]   
   given "initialie result" {
      set result {

ivancorrales

vars {
  mediaJson = "application/json"
}

func signUp {
  input {
    arg baseApi {
        description = "URL base of the API"
    }
    arg user {

ivancorrales

func dropCollection {
  input {
    arg mongoUri {
      description = "mongo uri"
    }
    arg database {
      description = "Name of the database"
      default = "admin"

ivancorrales

description = <<EOF
    This feature verify that API works as expected
EOF

includes = [
    "includes/database.hcl",
    "includes/api.hcl",
    "happyPath.hcl",
    "signUp-failures.hcl",
    "signIn-failures.hcl",

ivancorrales

scenario "happy path" {
  given "my user details" {
    set user {
      value = {
        fullName = "John Smith"
        username = "[email protected]"
        password = "secret"
      }
    }
  }

ivancorrales

scenario "a user registration fails because required fields are not provcided" {
    examples = [
        { fullName ="", username = "",  password =""},
        { fullName ="Jane Doe", username = "",  password =""},
        { fullName ="Jane Doe", username = "[email protected]",  password =""},
        { fullName ="Jane Doe", username = "",  password ="secret"},

    ]
    when "register the user" {

ivancorrales

# Parameters
nc: 2  # number of classes

depth_multiple: 0.67  # model depth multiple
width_multiple: 0.75  # layer channel multiple
anchors:
  - [10,13, 16,30, 33,23]  # P3/8
  - [30,61, 62,45, 59,119]  # P4/16
  - [116,90, 156,198, 373,326]  # P5/32

ivancorrales

# Path will be the root of train/val/test values
path: /mydrive/tutorials/tutorial_object_detection/dataset
 
train: [images/train/, labels/train/] 
val:  [images/val/,labels/val/]
 
# number of classes
nc: 2
 
# class names

ivancorrales

# YOLOv5 🚀 by Ultralytics, GPL-3.0 license
# Hyperparameters for VOC finetuning
# python train.py --batch 64 --weights yolov5m.pt --data VOC.yaml --img 512 --epochs 50
# See tutorials for hyperparameter evolution https://github.com/ultralytics/yolov5#tutorials

# Hyperparameter Evolution Results
# Generations: 306
#                   P         R     mAP.5 mAP.5:.95       box       obj       cls
# Metrics:        0.6     0.936     0.896     0.684    0.0115   0.00805   0.00146