This learning path is designed for developers interested in quickly getting up to speed on what IBM Maximo Visual Inspection offers and how to use it. The learning path consists of step-by-step tutorials, deep-dive videos, and complete examples of working code. As you proceed through the learning path, you will learn about more advanced features as well as different use cases for Maximo Visual Inspection.
To get started, click on a card below, or see the table above for a complete list of topics covered.
Intro to computer vision
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Learn about:
- Image classification
- Object detection
- Object tracking in videos
- Creating custom models
- Using your model
- Example use cases
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Introduction to IBM Maximo Visual Inspection
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Learn about:
- Creating a data set
- Assigning categories for image classification
- Labeling objects for object detection
- Training a model
- Testing the model
- Using it in an app
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Build and deploy an IBM Maximo Visual Inspection model and use it in an iOS app
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Learn about:
- Creating a data set
- Training a model for image classification
- Deploying it to a web API
- Integrating the API into an iOS app
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Locate and count items with object detection
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Learn about:
- Creating a data set
- Training a model for object detection
- Deploying it to a web API
- Testing the model with REST calls
- Integrating object detection into a Node.js web app
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Object tracking in video with OpenCV and deep learning
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Learn about:
- Using automatic labeling to create an object detection classifier from a video
- Processing frames of a video using a Jupyter Notebook, OpenCV, and IBM Maximo Visual Inspection
- Detecting objects in video frames with IBM Maximo Visual Inspection
- Tracking objects from frame to frame with OpenCV
- Counting objects in motion as they enter a region of interest
- Annotating a video with bounding boxes, labels, and statistics
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Validate computer vision deep learning models
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Learn about:
- Classifing images using an existing model and a Jupyter Notebook
- Collecting statistics to evaluate a model
- Visualizing model accuracy with a confusion matrix
- Producing a variety of accuracy measure for model validation
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Develop analytical dashboards for AI projects with IBM Maximo Visual Inspection
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Learn about:
- Uploading training images to IBM Maximo Visual Inspection
- Training and deploying a model in IBM Maximo Visual Inspection
- Uploading images to be processed through the dashboard
- Viewing the processed images and graphs in the dashboard
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Automate visual recognition model training
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Learn about:
- Automating categorizing and uploading of images to IBM Maximo Visual Inspection
- Automating model training in IBM Maximo Visual Inspection
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Load IBM Maximo Visual Inspection inference results in a dashboard
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Learn about:
- Extract information from an IBM Maximo Visual Inspection instance as a CSV file
- How to visualize and filter the data within a web browser
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Build an object detection model to identify license plates from images of cars
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Learn about:
- Build an object detection model
- Trigger a post-processing script when specific objects are detected
- Use Python Opencv libraries to prepare an image for OCR
- Adjust Tesseract OCR to detect specific fonts
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Automate your video analysis
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Learn about:
- Installing and activating the provided script
- Training and deploying an inference model within Maximo Visual Inspection
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Glean insights with AI on live camera streams and videos
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Learn about:
- Display live RTSP camera streams or prerecorded videos
- Get different visualizations such as a list, a pie chart, and a data table
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Analyze live video streams using IBM Maximo Visual Inspection
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Learn about:
- Apply object detection and image classification to live camera feeds
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Monitor objects over time with IBM Maximo Visual Inspection
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Learn about:
- View the stages of any given process in chronological order
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Start: Introduction to computer vision