AugeLab Studio Manual
English
English
  • ๐Ÿ‘‹Welcome to AugeLab Studio User Manual
  • ๐Ÿ“˜Introduction
    • AugeLab Studio
    • Key Features
    • Use Cases
    • System Requirements
  • ๐Ÿš€Getting Started
    • Signing up
    • Installation
    • First Look
    • Simple Tour
    • Your Very First Project
      • Basics
      • Detection
      • Wrapping Up
    • More Local Examples
    • Further Reading
  • ๐Ÿ–ฅ๏ธAugeLab Studio Interface
    • Detailed Look
    • Scenario Area
    • Menu and Toolbar
    • Managing Projects
    • Installing AI and much more
      • Leverage AI with Module Downloader
  • ๐ŸงฑFunction Blocks
    • Block Structures
    • Sockets
    • Blocks Column
    • Connections
    • All Function Blocks
      • AI Blocks
        • Face Detection
        • Mask Detection
        • Object Detection - Custom
        • Object Detection
        • Pose Estimation
        • Safety Equipment Detection
        • Social Distance Detector
        • Super Resolution
        • Text Detection
        • OCR
      • CNN Blocks
        • Average Pooling 2D
        • Batch Normalization
        • Choose Folder 2D
        • Compile Model
        • Conv. Sep. Layer 2D
        • Conv. Trans. Layer 2D
        • Convolutional Layer 2D
        • Dropout Layer
        • Flatten Layer 2D
        • Fully Connected
        • Global Average Pooling 2D
        • Global Max Pooling 2D
        • Input Layer 2D
        • Loss CCE
        • Max Pooling 2D
        • Metrics Accuracy
        • Model EfficientNet
        • Model MobileNet
        • Model ResNet
        • Model VGG
        • Optimizer Adadelta
        • Optimizer Adagrad
        • Optimizer Adam
        • Optimizer Adamax
        • Optimizer FTRL
        • Optimizer Nadam
        • Optimizer RMSProp
        • Optimizer SGD
        • ReLU Layer
        • Softmax Layer
        • Training Parameters
      • Data/Logic
        • Flow Control
          • Batch Concatenation
          • Batch Processing
          • Debatch
          • Get Batch Size
          • HMI Background
          • Subsystem Enabled
          • Subsystem In
          • Subsystem Loop
          • Subsystem Out
          • Subsystem
        • logic
          • All True
          • And
          • Demux
          • Equals
          • Greater
          • Logic Operations
          • Mux
          • Not
          • Or
          • Set - Reset
          • Smaller
        • Mathmetical Operations
          • Add
          • Counter
          • Divide
          • Math Operations
          • Maximum
          • Minimum
          • Multiply
          • Not Equals
          • Round
          • Square Root
          • Subtract
          • Trigonometry
        • Data Operations
          • Data Memory
          • Data to JSON
          • Data Type Converter
          • Datetime Compare
          • Dictionary Operations
          • Exclude Nones
          • Find Substring
          • Get Element
          • Is None
          • List Operations
          • Parse Data Dictionary
          • Replace None
          • String Merge
          • String Operations
        • Referencing
          • Data Read Global
          • Data Read Local
          • Data Write Global
          • Data Write Local
          • Debug Input
          • Tag From
          • Tag To
        • Signal Operators
          • Delay Step
          • Edge Falling
          • Edge Rising
          • Multi Port Switch
          • OFF Delay
          • ON Delay
      • Image/Transformations
        • Analysis
          • Color Density Percentage
          • Get Dimension
          • Histogram On Curve
          • Histogram On Line
          • Image Color Match
          • Image Memory
          • Image Resolution and Channel Value
          • Maximum Images
          • Mean Value of Image
          • Measure Position Distance
          • Minimum Images
          • Non-zero of Image
          • Std. of Image
          • Structural Similarity
        • Transformation Filters
          • Auto Alignment
          • Auto Contrast
          • Color Quantizer and Clustering
          • Color Space
          • Contrast-Brightness-Gamma
          • Contrast Optimization
          • Deconvolution
          • Denoising
          • Distance Transformation
          • FloodFill
          • Grab Cut Algorithm
        • Color Filters
          • 2D Filter
          • Apply Mask
          • Bilateral Filter
          • Blur
          • Edge Filter
          • HSV Filter
          • Image Adaptive Threshold
          • Image Threshold
          • Invert Image
          • Morphological Transformations
          • Normalize Image
          • RGB Mask
          • RGB Set
          • Sobel Filter
        • Operations
          • Add Images Weighted
          • Add Images
          • Collage Images
          • Divide Images
          • Flip Image
          • Image AutoRotator
          • Image Concatenate
          • Image Resize
          • Image Resizer
          • Merge Channels
          • Multiply Images
          • Polar Transform
          • Rotate Image Angle
          • Slice Image
          • Split Image
          • Subtract Images
      • Detections/Shapes
        • Detectors
          • Barcode Reader
          • Blob Detector
          • Blur Detector
          • Circle Detector
          • Corner Detector
          • Custom CNN Model
          • Data Matrix Reader
          • Detect Reference
          • Feature Detector
          • Find Object - Multiple Image
          • Find Object
          • Find Reference
          • Harris Corner Filter
          • Line Detector
          • Match Shapes
          • Measure Object Distance
          • Shape Detector
        • Draw
          • Draw Detections
          • Draw Line
          • Draw Point
          • Draw Rectangle
          • Draw Result On Image
          • Write Date On Image
          • Write Text On Image
        • Roi Processing
          • Check Area (Polygon)
          • Check Area
          • Get Pixel Mouse
          • Get Pixel
          • Get ROI
          • Image ROI Center
          • Image ROI Polygon
          • Image ROI Select Multi
          • Image ROI Select
          • Image ROI
          • Perspective Transform
          • Rectangles in Rectangle
        • Shape Analysis
          • Approximate Contour
          • Choose Line
          • Contour to Image
          • Fill Contour
          • Find Contour
          • Hull Convex
          • Minimum Circle
          • Minimum Ellipse
          • Minimum Rectangle
          • Minimum Rotated Rectangle
          • Most Similar Shape
          • Point Polygon Test
      • Input/Output
        • Communication
          • Modbus Connect
          • Modbus Read
          • Modbus Write
          • MQTT Publish
          • MQTT Subscribe
          • OPC UA Client
          • OPC UA Read
          • OPC UA Write
          • REST API - Get
          • REST API - Post
          • Send Mail
          • Siemens S7 Connect
          • Siemens S7 Read
          • Siemens S7 Write
        • Data Inputs
          • Date-Time List
          • Date-Time
          • Headless Check
          • Keyboard/Barcode Reader
          • Logic Input
          • Number Input
          • Number Range
          • PWM (Pulse Width Modulation)
          • Rising Edge
          • String Input
          • Text
        • Image Inputs
          • Camera IP (ONVIF)
          • Camera IP
          • Camera USB External
          • Camera USB Vidgear
          • Camera USB
          • Load Image From Path
          • Load Image
          • Make Image
          • Pixel
          • Video
        • Outputs/Exports
          • CSV Export
          • Cycle Timer
          • File/Folder Operations
          • GPU Statistics
          • Image Logger
          • Image Write
          • Led Output
          • Multi Image Write
          • Output
          • Scope
          • Show Image
          • Stop
  • ๐Ÿ“กDevices and Communication
    • Camera Usage
    • Communication Protocols
    • Further Reading
  • ๐ŸงฉExample Projects
    • Demo Projects
    • Circumference Measurement
    • Object Counting
    • Tile Width Measurement
    • Human Detection
    • Object Detection
  • ๐Ÿ”‘Key Features
    • Deploy Custom HMI Applications
    • Annotate Data for Object Detection
    • Train Custom AI Models
      • Choosing the Right Database
      • When to Stop Training
    • Create Plugins
      • Components
      • Coding Reference
    • Share Your Solutions with Community
    • Instal Python Packages
  • ๐Ÿ“‘FAQ
    • Contact Us
    • FAQ
    • Setting up a full project
  • Additional Resources
    • Training Schedule
    • Training Materials
    • AugeLab Experts
  • Appendix
    • Dictionary
    • References
Powered by GitBook
On this page
  • ๐Ÿ“ฅ Inputs
  • ๐Ÿ“ค Outputs
  • ๐Ÿ•น๏ธ Controls
  • ๐ŸŽจ Features
  • ๐Ÿ“ Usage Instructions
  • ๐Ÿ“Š Evaluation
  • ๐Ÿ’ก Tips and Tricks
  • ๐Ÿ› ๏ธ Troubleshooting

Was this helpful?

  1. Function Blocks
  2. All Function Blocks
  3. CNN Blocks

Compile Model

This function block is used to compile a neural network model for 2D data processing in machine learning tasks. It integrates various model parameters, including layers, optimizers, loss functions, and metrics.

๐Ÿ“ฅ Inputs

Layer This input connects to the desired neural network layer to be compiled into the model.

Optimizer This input specifies the optimization algorithm to be used in training the model.

Loss Function This input connects to the chosen loss function that will guide the optimization process.

Metrics This input connects to the performance metrics used to evaluate the model during training.

Training Params This input contains parameters related to the training process, such as paths and configurations.

๐Ÿ“ค Outputs

This function block does not provide any outputs.

๐Ÿ•น๏ธ Controls

Compile Model This button initiates the compilation of the neural network model based on the provided inputs.

๐ŸŽจ Features

Session Management Clears any existing TensorFlow sessions before compiling the model to ensure a clean state.

Error Handling Provides detailed error messages and logging to guide users when inputs are missing or invalid.

Training Window Launching Successfully compile the model and launch a training window for iterative training processes.

๐Ÿ“ Usage Instructions

  1. Connect Inputs: Link appropriate layers to the Layer input, optimizers to the Optimizer input, loss functions to the Loss Function input, and performance metrics to the Metrics input.

  2. Configure Training Parameters: Ensure that valid training parameters are connected to the Training Params input.

  3. Compile the Model: Click the Compile Model button to initiate the model compilation process.

  4. Training: On successful compilation, a training window will appear for further steps in the training process.

๐Ÿ“Š Evaluation

Upon successful execution, this function block compiles the model according to the specified parameters and prepares it for training.

๐Ÿ’ก Tips and Tricks

Ensure Valid Inputs

Always check that all required inputs are connected before attempting to compile the model. Missing inputs can lead to compilation errors.

Use Correct Paths

Make sure that the training path specified in the training parameters exists and is accessible. Incorrect paths will result in validation errors.

More Info on Parameters

If you're unsure about the parameters required by the model or their structure, consult the model documentation or use visual aids like flowcharts to outline required connections.

๐Ÿ› ๏ธ Troubleshooting

Compilation Errors

If an error occurs during compilation, review the provided inputs for correctness and ensure all components are properly configured.

Model Not Training

If the model compiles successfully but does not train, verify your training parametersโ€”especially those related to paths, classes, and optimizers.

PreviousChoose Folder 2DNextConv. Sep. Layer 2D

Last updated 8 months ago

Was this helpful?

๐Ÿงฑ