Annotation Basics (OLD) - V7 Darwin AI Academy

V7
17 Oct 201909:49

TLDRThis tutorial introduces the basics of using v7 Darwyn, a tool for image annotation. It covers navigation, zooming, and panning within images, as well as creating bounding boxes and polygon masks for object detection. The script details the process of annotating various objects, including灯笼, people, and canopies, and demonstrates the use of shortcuts for efficiency. It also explains how to handle video frames, classify images, and manage annotations with tags and sub-annotations for more complex tasks. The tutorial concludes with guidance on skipping blurry images and encourages user feedback for improvement.

Takeaways

  • 🎨 Navigation: Users can pan around the image by clicking and dragging or using the middle mouse click.
  • 🔍 Zooming: Zoom in and out can be achieved with the scroll wheel or by pressing control with the scroll wheel.
  • 🖼️ Bounding Box: The shortcut for the bounding box tool is 'B', used to create a box around objects for classification.
  • 🏷️ Class Selection: After creating a bounding box, users can select a class, like 'Lantern', for the object.
  • 👤 Small Object Annotation: For tiny objects like people, users can switch to the 'Person' class and annotate them with a bounding box.
  • 📏 Polygon Masks: The 'Auto Annotate' feature helps create polygon masks around objects, which is useful for various object types.
  • 🔧 Manual Precision: The polygon tool (shortcut 'P') allows for manual, precise annotations when needed.
  • 📚 Layer Management: Users can define and manipulate layers, such as background (sky) and foreground (wall), to create accurate annotations.
  • 🔄 Copy and Paste: Annotations can be copied from one image to another, adjusting for movement in video frames.
  • ⏏️ Skip and Classify: Blurry images can be skipped, while images can be classified with tags for further categorization.
  • 🔄 Sub-Annotations: Users can create annotations within annotations, like directional vectors and attributes for specific classes.
  • 📝 Text Annotation: Attributes can be added to text within images, such as 'handwritten' with sub-annotations for the actual text content.

Q & A

  • What is the shortcut for the Edit tool in v7 Darwyn?

    -The shortcut for the Edit tool is 'V'.

  • How can you pan around an image in v7 Darwyn?

    -You can pan by clicking and dragging, using the middle mouse click, or by pressing the 'V' key to select the Edit tool and then dragging.

  • What are the methods to zoom in or out in v7 Darwyn?

    -You can zoom using the scroll wheel, pressing control while scrolling, or by using the zoom tool (shortcut 'Z') and clicking on the image.

  • How do you create a bounding box in v7 Darwyn?

    -Use the bounding box tool (shortcut 'B') or click on the bounding box button on the left, then enclose the object with a box and choose the appropriate class.

  • What is the purpose of the auto annotate button in v7 Darwyn?

    -The auto annotate button allows you to automatically create polygon masks around objects, which helps in annotating images more efficiently.

  • How can you adjust the layers in an annotation?

    -You can adjust layers by selecting the desired layer item on the right, double-clicking it, and changing its class to define the background or foreground elements.

  • What is the use of the polygon tool in v7 Darwyn?

    -The polygon tool (shortcut 'P') is used for manual annotations, allowing precise control over the type of annotations made, which is recommended for pixel-perfect or accurate ground truth annotations.

  • How do you copy and paste annotations from one image to another in v7 Darwyn?

    -You can copy an annotation by pressing 'Ctrl C' or 'Command C' on Macs, and then paste it with 'Command V' or 'Ctrl V'. The 'copy instances' button can also be used to copy over annotations from the previous image.

  • What should you do with blurry images in v7 Darwyn?

    -Blurry images should be skipped as they can reduce the accuracy of the trained AI. You can use the 'skip image' button and select 'out-of-focus' to archive the image and prevent it from being used in training.

  • How can you classify images with additional tags in v7 Darwyn?

    -You can add tags by clicking on the 'tag' button on the right, selecting the desired tags (e.g., 'sharp', 'egg', 'marine'), and typing in additional tags if needed. These tags are used for creating classifiers.

  • What are sub-annotations and how are they used in v7 Darwyn?

    -Sub-annotations are annotations within an annotation. They can include directional vectors to indicate the direction of an object or attributes to provide additional information. For example, you can add a directional vector for the flow direction of a river and attributes for bar levels or pressure in a gauge.

Outlines

00:00

🖼️ Image Navigation and Basic Annotation

This paragraph introduces the user to the basics of navigating and annotating images within the v7 Darwyn platform. Users can pan around an image by clicking and dragging or using the scroll wheel on their mouse. Zooming in and out is achieved with the scroll wheel or by using the zoom tool (shortcut Z). The process of creating bounding boxes around objects, such as lanterns, is detailed, including selecting the object class and the use of keyboard shortcuts like B for bounding box. The paragraph also explains how to cycle through images and switch between different object classes, like switching from 'Lantern' to 'Person' for annotating small people in the image.

05:01

📏 Advanced Annotation Techniques and Layer Management

The second paragraph delves into more advanced annotation techniques within the Darwyn platform. It covers the use of polygon masks and the auto-annotate feature, which allows for the AI to create polygon masks around objects within a specified box. The paragraph explains how to manually adjust these masks and how to exclude certain elements from the annotation. It also introduces the concept of layers, with an example of defining a background layer (sky) and foreground layers (wall and chimney stacks). The process of tagging images for classification and the use of sub-annotations for adding directional vectors and attributes to objects are also discussed. The paragraph concludes with instructions on annotating text and the various ways to copy, paste, and edit annotations.

Mindmap

Keywords

💡Darwyn

Darwyn is the name of the AI annotation tool being discussed in the tutorial. It is a platform that allows users to annotate images for training AI models. The tool offers various functionalities such as creating bounding boxes, polygon masks, and sub-annotations, which are essential for precise object detection and classification in images.

💡Navigation

Navigation refers to the操作方法 used to move around and interact with the image within the Darwyn platform. It includes panning, zooming, and selecting tools, which are crucial for accurately annotating images. The script provides shortcuts and techniques for efficient navigation, such as using the scroll wheel or pressing control scroll to zoom in and out.

💡Bounding Box

A bounding box is a rectangular selection that defines the area around an object in an image. It is a fundamental annotation type in image recognition and machine learning, used to identify and classify objects. In the context of the tutorial, users create bounding boxes to outline objects like lanterns and people, which is a crucial step in training AI models to recognize these objects.

💡Polygon Masks

Polygon masks are a type of annotation that allows for more intricate and precise outlining of objects within an image. Unlike bounding boxes, which are rectangular, polygon masks can be composed of multiple points to closely follow the contours of an object. This provides a more detailed level of annotation, which is beneficial for complex shapes or objects with irregular boundaries.

💡Layers

In the context of the tutorial, layers refer to the hierarchical organization of annotations within an image. Users can define different classes, such as the background layer (sky) and foreground layers (wall, chimney stacks), and arrange them in a specific order. This layering is important for the interpretation of the annotated data, ensuring that the correct object is recognized as being in front of or behind another.

💡Sub-Annotations

Sub-annotations are annotations that exist within a primary annotation, providing additional information or attributes about a specific aspect of the primary object. They are used to capture more detailed data about an object's characteristics, such as direction, level, or status. Sub-annotations enhance the complexity and usefulness of the data for training AI models.

💡Shortcuts

Shortcuts are quick key combinations or single key presses that allow users to perform actions more efficiently within the Darwyn platform. They are essential for speeding up the annotation process and improving productivity. The tutorial provides various shortcuts for navigation, annotation, and layer manipulation.

💡Annotation

Annotation refers to the process of marking and labeling elements within an image to provide context and information for AI model training. It involves selecting specific tools and techniques within the Darwyn platform to identify and classify objects, such as using bounding boxes, polygon masks, or sub-annotations.

💡Classes

In the context of AI annotation, classes are categories or groups of similar objects that are used for object classification. They are essential for organizing and training AI models to recognize and differentiate between various types of objects within images. The tutorial demonstrates how to select and apply classes to annotations, such as 'Lantern', 'Person', 'Canopy', and 'Wall'.

💡Video Frame

A video frame refers to a single image extracted from a video. In video analysis and annotation, each frame can be treated as a separate image for the purpose of object detection and classification. The tutorial mentions working with video frames, where the images are almost identical, with only slight movements between them.

💡Tags

Tags are labels or keywords that are assigned to images or annotations to provide additional metadata and context. They are used for organizing, filtering, and training AI models based on specific characteristics or attributes. In the tutorial, tags like 'sharp', 'egg', and 'marine' are used to classify images and create classifiers for AI training.

Highlights

Navigation and image panning techniques using the Edit tool or mouse functions.

Zooming in and out with scroll wheel, control scroll, or zoom tool shortcuts.

Creating bounding boxes with the shortcut B for object identification.

Class selection for annotated objects, such as choosing 'Lantern' for lanterns.

Cycling through images using the period button for efficient annotation.

Switching classes to annotate different objects, like selecting 'Person' for small people.

Using the auto annotate button for automatic polygon masks around objects.

Manually adjusting AI-generated polygon masks for precision.

Layer management for complex annotations, such as defining background and foreground layers.

Changing class labels and layer order for accurate training data.

Skipping blurry images to maintain the quality of AI training data.

Classifying images with tags for creating specific classifiers.

Utilizing sub-annotations for detailed object information, like directional vectors and attributes.

Annotating text with attributes to indicate content, such as 'handwritten text'.

Copying and pasting annotations for efficient annotation of similar objects.

Contact options for feedback and feature requests to enhance the platform.

The tutorial provides a comprehensive overview of the v7 Darwyn annotation tool's features and functionalities.

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