3.1 Pipeline Protocol

Basic Format

The task pipeline is described using JSON format and consists of several nodes. Each node contains the following core attributes:

{
    "NodeA": {
        "recognition": "OCR",    // Recognition algorithm
        "action": "Click",       // Action to be executed
        "next": [                // List of subsequent nodes
            "NodeB",
            "NodeC"
        ],
        // Other extended properties...
    },
    // Other node definitions...
}

Execution Logic

Process Control Mechanism

1. Task Triggering

   • Start the task by specifying the entry node through the tasker.post_task interface

2. Sequential Detection:

   • Perform sequential detection on the current node's next list
   • Attempt to identify the recognition features configured for each sub-node in sequence

3. Interruption Mechanism:

   • When a sub-node is successfully matched, immediately terminate subsequent node detections
   • Execute the operation defined by the matched node's action

4. Successor Processing:

   • After the operation is completed, switch the active node to the current node
   • Repeat the above detection process

Termination Conditions

The task process terminates when any of the following conditions are met:

• The current node's next list is empty
• All subsequent node detections continuously fail until timeout

Application Examples

Scenario Description

There are menus Display/Storage/Accessibility in the Android settings interface, among which Storage contains the submenus Games/Apps after opening.

Configuration Example

{
    "Start Example": {
        "next": [
            "Enter Display",
            "Enter Storage",
            "Enter Accessibility"
        ]
    },
    "Enter Display": {
        "recognition": "XXX",
        "action": "Click",
        // ...
    },
    "Enter Storage": {
        "recognition": "XXX",
        "action": "Click",
        "next": [
            "Enter Games Submenu",
            "Enter Applications Submenu"
        ]
    },
    "Enter Accessibility": {
        // ...
    },
    "Enter Games Submenu": {
        "action": "Swipe",
        "next": []
    },
    "Enter Applications Submenu": {
        // ...
    },
    // ...
}

Execution Process Simulation

Case 1

Case 2

Property Fields

TIP

For mandatory fields, they may remain empty in the Pipeline JSON file, but must be set via the interface before actual execution.
Folders and JSON files that begin with a dot (.) will not be read.
JSON root fields that begin with a $ will not be parsed.

roi / box / target Differences

• roi: Region of Interest (ROI), defining the image recognition boundary; related image processing is performed only within this area.
• The recognition scope is jointly determined by roi and roi_offset.
• box: The matched bounding box returned after recognition succeeds, indicating “where it was recognized”.
• target: The action target area, used to decide “where to click / swipe / scroll”.
• The action target is jointly determined by target and target_offset.
• The default value of target is true, which means using the current recognized box as target; users can also explicitly set target to a fixed point, fixed area, or another node.

Typical flow: recognize inside roi (with roi_offset), get box, then calculate target (with target_offset) and execute the action.

Version Changes

Version	Changes
v5.0	Added attach field; Added TouchDown, TouchMove, TouchUp, KeyDown, KeyUp actions; Added contact, pressure fields to Click / LongPress / Swipe / MultiSwipe; target supports [x, y] binary coordinates
v5.1	Added anchor, max_hit fields; Added Scroll action; Added node attributes (jump_back / anchor); next / on_error support NodeAttr; order_by supports Expected sorting; is_sub / interrupt deprecated
v5.3	Added repeat, repeat_delay, repeat_wait_freezes fields; Added And, Or recognition types; Added Shell action; TemplateMatch method supports 10001; Added default attributes (default_pipeline.json)
v5.5	timeout supports -1 (wait indefinitely); Scroll supports target, target_offset
v5.6	roi / target support negative coordinates and dimensions
v5.7	anchor supports object format (specifying target node / clearing anchor); And / Or support node name reference
v5.8	OCR added color_filter field; Shell timeout renamed to shell_timeout; Added Screencap action

Pipeline v1

• recognition: string
  Recognition algorithm type. Optional, default is DirectHit.
  Possible values: DirectHit | TemplateMatch | FeatureMatch | ColorMatch | OCR | NeuralNetworkClassify | NeuralNetworkDetect | And | Or | Custom
  See Algorithm Types for details.

• action: string
  Action to execute. Optional, default is DoNothing.
  Possible values: DoNothing | Click | LongPress | Swipe | MultiSwipe | Scroll | ClickKey | LongPressKey | InputText | StartApp | StopApp | StopTask | Command | Shell | Screencap | Custom
  See Action Types for details.

• next : string | NodeAttr | list<string | NodeAttr, >
  List of nodes to execute next. Optional, default is empty.
  It recognizes each node in sequence and executes the first one it recognizes.
  💡 Since v5.1, nodes with attributes, NodeAttr objects, or heterogeneous arrays combining both are supported. See Node Attributes for details.

• is_sub: bool
  (Deprecated in version 5.1, use [JumpBack] in Node Attributes instead)
  We provide a migration script to help you automatically convert your pipeline to the new style without loss of quality.

• interrupt : string | list<string, >
  (Deprecated in version 5.1, use [JumpBack] in Node Attributes instead)
  We provide a migration script to help you automatically convert your pipeline to the new style without loss of quality.

• rate_limit: uint
  Identification rate limit, in milliseconds. Optional, default 1000.
  Each round of identification consumes at least rate_limit milliseconds, and sleep will wait if the time is less than that.

• timeout: int
  Timeout for loop recognition in the next list, in milliseconds. Optional, default is 20 * 1000 milliseconds (20 seconds).
  Set to -1 to wait indefinitely without timeout. 💡 v5.5
  The detailed logic is while(!timeout) { foreach(next); sleep_until(rate_limit); }

• on_error : string | NodeAttr | list<string | NodeAttr, >
  When recognition timeout or the action fails to execute, the nodes in this list will be executed next. Optional, empty by default.
  💡 Since v5.1, nodes with attributes, NodeAttr objects, or heterogeneous arrays combining both are supported. See Node Attributes for details.

• anchor: string | list<string, > | object 💡 v5.1
  Anchor name. Optional, default is empty.
  When the node executes successfully, the anchor name will be set to the corresponding node. Multiple nodes can set the same anchor name, with later executions overwriting earlier ones.
  Supports three formats:

  • String: "anchor": "MyAnchor" - Sets the anchor to the current node

  • String Array: "anchor": ["A", "B"] - Sets multiple anchors to the current node

  • Object 💡 v5.7: "anchor": {"A": "TargetNode", "B": ""} - Sets anchor A to TargetNode, clears anchor B (empty string means clear the anchor)

    In next or on_error, you can reference this anchor using the [Anchor] attribute, which resolves at runtime to the last node that set this anchor. If the referenced anchor is not set or has been cleared, the node will be skipped (not executed).
    See Node Attributes for details.

• inverse: bool
  Reverse the recognition result: recognized as not recognized, and not recognized as recognized. Optional, default is false.
  Please note that nodes recognized through this setting will have their own clicking actions disabled (because nothing was actually recognized). If there is a need, you can set the target separately.

• enabled: bool
  Whether to enable this node. Optional, default is true.
  If set to false, this node will be skipped when it appears in the "next" lists of other nodes, meaning it won't be recognized or executed.

• max_hit: uint 💡 v5.1
  The maximum number of times this node can be recognized successfully. Optional, default is UINT_MAX (unlimited).
  If this count is exceeded, this node will be skipped when it appears in the "next" lists of other nodes, meaning it won't be recognized or executed.

• pre_delay: uint
  Delay in milliseconds between recognizing a node and executing the action. Optional, default is 200 milliseconds.
  It is recommended to add intermediate nodes whenever possible and use less delay to maintain both speed and stability.

• post_delay: uint
  Delay in milliseconds between executing the action and recognizing the "next" nodes. Optional, default is 200 milliseconds.
  It is recommended to add intermediate nodes whenever possible and use less delay to maintain both speed and stability.

• pre_wait_freezes: uint | object
  Time in milliseconds to wait for the screen to stop changing between recognizing a node and executing the action. Optional, default is 0 (no waiting).
  It will exit the action only when the screen has not had significant changes for "pre_wait_freezes" milliseconds in a row.
  If it's an object, more parameters can be set, see Waiting for the Screen to Stabilize for details. The specific order is pre_wait_freezes - pre_delay - action - post_wait_freezes - post_delay.

• post_wait_freezes: uint | object
  Time in milliseconds to wait for the screen to stop changing between executing the action and recognizing the "next" nodes. Optional, default is 0 (no waiting).
  Other logic is the same as pre_wait_freezes.

• repeat: uint 💡 v5.3
  Number of times to repeat the action. Optional, default is 1 (no repeat).
  The execution flow is action - [repeat_wait_freezes - repeat_delay - action] × (repeat-1).

• repeat_delay: uint 💡 v5.3
  Delay between each repeated action in milliseconds. Optional, default is 0.
  Only effective when repeat > 1, waits before the second and subsequent action executions.

• repeat_wait_freezes: uint | object 💡 v5.3
  Time in milliseconds to wait for the screen to stop changing between each repeated action. Optional, default is 0 (no waiting).
  Only effective when repeat > 1, waits for the screen to stabilize before the second and subsequent action executions.
  If it's an object, more parameters can be set, see Waiting for the Screen to Stabilize for details.

• focus: object
  Focus on the node, resulting in additional callback messages. Optional, default is null (no messages).
  Each message type value supports string (legacy behavior, equivalent to display: "log") or object (new behavior, with explicit display channel).
  See Node Notifications for details.

• attach: object 💡 v5.0
  Additional JSON object for storing additional node configuration. Optional, default is an empty object.
  This field can be used to store custom configuration information that does not affect the node's execution logic but can be retrieved through related interfaces.
  Note: This field will be merged with the attach in the default value using dict merge, not overwritten. That is, the attach in the node will be merged with the attach in the default value, where values with the same keys will be overwritten by the node's values, but other keys will be preserved.

The lifecycle of a node is as follows:

Pipeline v2

NOTE

MaaFW supports Pipeline v2 protocol since version v4.4.0, and is compatible with v1.

Compared with v1, the main difference is that the fields related to recognition and action are put into the secondary dictionary (the type is put into the type field, and the other parameters are put into the param field), and the rest are the same. Example:

{
    "NodeA": {
        "recognition": {
            "type": "TemplateMatch",
            "param": {
                // Recognition related fields are placed in recognition.param, and the keys and values ​​remain unchanged from v1
                "template": "A.png",
                "roi": [100, 100, 10, 10]
            }
        },
        "action": {
            "type": "Click",
            "param": {
                // Action related fields are placed in action.param, and the keys and values ​​remain unchanged from v1
                "target": "XXX"
            }
        },
        // Non-recognition and action fields remain unchanged from v1
        "next": ["NodeB"],
        "pre_delay": 1000,
        // ...
    }
}

Default Properties

💡 v5.3
Please refer to default_pipeline.json

default_pipeline.json is used to set default parameters for all nodes and specific algorithm/action types, reducing redundant configuration. This file is automatically loaded during resource loading, and the configurations within serve as baseline defaults inherited by all nodes.

Configuration Structure

{
    "Default": {
        // Default values for common fields, applicable to all nodes
        "rate_limit": 1000,
        "timeout": 20000,
        "pre_delay": 200
    },
    "TemplateMatch": {
        // Default parameters for TemplateMatch algorithm
        // Can use v1 or v2 format
        "recognition": "TemplateMatch",  // v1 format: directly in root object
        "threshold": 0.7
        // Or use v2 format:
        // "recognition": { "type": "TemplateMatch", "param": { "threshold": 0.7 } }
    },
    "Click": {
        // Default parameters for Click action
        "action": "Click",  // v1 format
        "target": true
        // Or use v2 format:
        // "action": { "type": "Click", "param": { "target": true } }
    }
}

Field Description

• Default object: Can set default values for all common Pipeline fields (such as rate_limit, timeout, pre_delay, post_delay, etc.)
• Algorithm name objects (e.g., TemplateMatch, OCR, FeatureMatch): Can set default parameters for the corresponding recognition algorithm type
• Action name objects (e.g., Click, Swipe, StartApp): Can set default parameters for the corresponding action type

Inheritance Priority

Parameter priority from highest to lowest:

1. Parameters directly defined in the node
2. Default parameters for the corresponding algorithm/action type in default_pipeline.json
3. Default parameters in the Default object of default_pipeline.json
4. Built-in default values in the framework

Usage Example

Assuming default_pipeline.json is configured as follows:

{
    "Default": {
        "rate_limit": 2000
    },
    "TemplateMatch": {
        "recognition": "TemplateMatch",
        "threshold": 0.7
    }
}

In Pipeline JSON:

{
    "NodeA": {
        "recognition": "TemplateMatch",
        "template": "A.png"
        // rate_limit will inherit 2000 from Default
        // threshold will inherit 0.7 from TemplateMatch
    },
    "NodeB": {
        "recognition": "TemplateMatch",
        "template": "B.png",
        "threshold": 0.9,  // Override default value
        "rate_limit": 1000 // Override default value
    }
}

Notes

• default_pipeline.json should be placed in the root directory of the resource bundle (Bundle), at the same level as the pipeline folder
• The key names for algorithm/action objects must exactly match the corresponding algorithm/action type names (e.g., TemplateMatch, OCR, Click), case-sensitive
• The attach field will be dictionary merged (dict merge) rather than overwritten, meaning the node's attach will merge with the default attach
• If you don't need a certain default configuration, simply set it explicitly to another value in the node to override

Multiple Bundle Loading Behavior

When loading multiple Bundles sequentially:

• Their default_pipeline.json files are merged (dict merge) in order, with later-loaded fields overriding earlier ones
• Already-loaded nodes are NOT affected by subsequent Bundle's default_pipeline.json
• Each node uses the merged defaults at the time of its first loading, and remains unchanged thereafter

Example: Bundle_Base → Bundle_Debug

// Bundle_Base/default_pipeline.json
{ "Default": { "rate_limit": 2000 } }

// Bundle_Base/pipeline/main.json
{ "NodeA": { "recognition": "OCR" } }  // Uses rate_limit: 2000

// Bundle_Debug/default_pipeline.json  
{ "Default": { "rate_limit": 100 } }   // Overrides defaults

// Bundle_Debug/pipeline/debug.json
{ "NodeB": { "recognition": "OCR" } }  // Uses rate_limit: 100

After loading, NodeA keeps rate_limit: 2000, NodeB uses rate_limit: 100.

Best Practice: Separating Special Configurations

Organize nodes with special configurations into a separate Bundle with dedicated default_pipeline.json to achieve configuration isolation.

Example: Separate debug nodes into an independent Bundle

MaaResourcePostPath(resource, "resource/base");   // base nodes use rate_limit: 2000
MaaResourcePostPath(resource, "resource/debug");  // debug nodes use rate_limit: 100

Since already-loaded nodes are not affected by subsequent defaults, base Bundle nodes retain their original configuration while debug Bundle nodes use the new defaults.

Algorithm Types

DirectHit

Direct hit, meaning no recognition is performed, and the action is executed directly.

This algorithm property requires additional fields:

• roi: array<int, 4> | string
  Region of Interest (ROI), defining the image recognition boundary; related image processing is performed only within this area. Optional, default [0, 0, 0, 0], i.e. full screen.

  • array<int, 4>: Recognition area coordinates [x, y, w, h]. Supports negative values 💡 v5.6: negative x/y means calculating from right/bottom edge; w/h of 0 means extending to edge, negative means taking absolute value and treating (x, y) as bottom-right corner.
  • string: Fill in the node name to perform recognition within the target range produced by a previously executed node. Also supports [Anchor]AnchorName format to reference the node corresponding to an anchor 💡 v5.9. If the referenced pre-task or anchor has no recognition result, the recognition is treated as failed.

• roi_offset: array<int, 4>
  Move additionally based on roi as the range, and add the four values separately. Optional, default [0, 0, 0, 0].

TemplateMatch

Template matching, also known as "find image."

This algorithm property requires additional fields:

• roi: array<int, 4> | string
  Same as DirectHit.roi.

• roi_offset: array<int, 4>
  Same as DirectHit.roi_offset.

• template: string | list<string, >
  Path to the template image, relative to the "image" folder. Required.
  The images used need to be cropped from the lossless original image and scaled to 720p. Reference to Image Files.
  Supports filling in folder paths, and all image files in them will be recursively loaded.

• threshold: double | list<double, >
  Template matching threshold. Optional, default is 0.7.
  If it's an array, its length should match the length of the template array.

• order_by: string
  How the results are sorted. Optional, default is Horizontal.
  Possible values: Horizontal | Vertical | Score | Random.
  You can use it with the index field.

• index: int
  Index to hit. Optional, default is 0.
  If there are N results in total, the value range of index is [-N, N - 1], where negative numbers are converted to N - index using Python-like rules. If it exceeds the range, it is considered that there is no result in the current identification.

• method: int
  Template matching algorithm, equivalent to cv::TemplateMatchModes. Optional, default is 5.
  For more details, refer to the OpenCV official documentation.
  10001 is the inverted version of TM_SQDIFF_NORMED, where higher scores indicate better matches (opposite to the original). 💡 v5.3

  method	Algorithm Name	Speed	Color Sensitivity	Lighting Robustness	Use Case
  10001	TM_SQDIFF_NORMED (Inverted) 💡 v5.3	Fast	Sensitive	Poor	Precise matching, easy threshold setting
  3	TM_CCORR_NORMED	Medium	Sensitive	Medium	Works well with bright templates
  5	TM_CCOEFF_NORMED	Slower	Insensitive	Good	Recommended, easy threshold setting

• green_mask: bool
  Whether to apply a green mask. Optional, default is false.
  If set to true, you can paint the unwanted parts in the image green with RGB: (0, 255, 0), and those green parts won't be matched.
  Note: The algorithm itself has strong robustness, so this feature is usually unnecessary for normal background variations. If you do need to use it, only mask the interfering areas and avoid excessive masking that could cause loss of main subject edge features.

FeatureMatch

Feature matching, a more powerful "find image" with better generalization, resistant to perspective and size changes.

This algorithm property requires additional fields:

• roi: array<int, 4> | string
  Same as DirectHit.roi.

• roi_offset: array<int, 4>
  Same as DirectHit.roi_offset.

• template: string | list<string, >
  Path to the template image, relative to the "image" folder. Required.
  Supports filling in folder paths, and all image files in them will be recursively loaded.
  Notes:

  • Template images should not be too small; at least 64x64 pixels is recommended. Otherwise, too few feature points may cause matching failures or false matches.
  • Templates should contain sufficient texture details (such as edges and corners); solid color or gradient areas have sparse feature points.
  • Avoid templates with large amounts of repetitive textures (such as grids or stripes), which may cause feature point matching confusion.

• count: uint
  The minimum number of matching feature points required (threshold). Optional, default is 4.

• order_by: string
  How the results are sorted. Optional, default is Horizontal.
  Possible values: Horizontal | Vertical | Score | Area | Random.
  You can use it with the index field.

• index: int
  Index to hit. Optional, default is 0.
  If there are N results in total, the value range of index is [-N, N - 1], where negative numbers are converted to N - index using Python-like rules. If it exceeds the range, it is considered that there is no result in the current identification.

• green_mask: bool
  Whether to apply a green mask. Optional, default is false.
  If set to true, you can paint the unwanted parts in the image green with RGB: (0, 255, 0), and those green parts won't be matched.
  Note: The algorithm itself has strong robustness, so this feature is usually unnecessary for normal background variations. If you do need to use it, only mask the interfering areas and avoid excessive masking that could cause loss of main subject edge features.

• detector: string
  Feature detector. Optional, default is SIFT.

  Detector	Speed	Scale Invariance	Rotation Invariance	Accuracy	Use Case
  SIFT	Slow	Yes	Yes	Highest	Recommended, high accuracy requirements
  KAZE	Slower	Yes	Yes	High	2D/3D images, good edge preservation
  AKAZE	Medium	Yes	Yes	Good	Balance between speed and accuracy
  BRISK	Fast	Yes	Yes	Medium	Real-time requirements
  ORB	Fastest	No	Yes	Lower	Use when template and target have same scale

• ratio: double
  The distance ratio for KNN matching, [0 - 1.0], where larger values make the matching more lenient (easier to connect). Optional, default is 0.6.

ColorMatch

Color matching, also known as "find color."

This algorithm property requires additional fields:

• roi: array<int, 4> | string
  Same as DirectHit.roi.

• roi_offset: array<int, 4>
  Same as DirectHit.roi_offset.

• method: int
  Color matching method, equivalent to cv::ColorConversionCodes. Optional, default is 4 (RGB).
  Common values are 4 (RGB, 3 channels), 40 (HSV, 3 channels), and 6 (GRAY, 1 channel).
  For more details, refer to the OpenCV official documentation.

• lower: list<int, > | list<list<int, >>
  Lower bound for colors. Required. The innermost list length should match the number of channels in the method.

• upper: list<int, > | list<list<int, >>
  Upper bound for colors. Required. The innermost list length should match the number of channels in the method.

• count: uint
  The minimum number of matching pixels required (threshold). Optional, default is 1.

• order_by: string
  How the results are sorted. Optional, default is Horizontal.
  Possible values: Horizontal | Vertical | Score | Area | Random.
  You can use it with the index field.

• index: int
  Index to hit. Optional, default is 0.
  If there are N results in total, the value range of index is [-N, N - 1], where negative numbers are converted to N - index using Python-like rules. If it exceeds the range, it is considered that there is no result in the current identification.

• connected: bool
  Whether to count only connected points. Optional, default is false.
  If set to true, after applying color filtering, it will only count the maximum connected block of pixels.
  If set to false, it won't consider whether these pixels are connected.

OCR

Text recognition.

This algorithm property requires additional fields:

• roi: array<int, 4> | string
  Same as DirectHit.roi.

• roi_offset: array<int, 4>
  Same as DirectHit.roi_offset.

• expected: string | list<string, >
  The expected results, supports regular expressions. Optional, default matches all.

• threshold: double
  Model confidence threshold. Optional, default is 0.3.

• replace: array<string, 2> | list<array<string, 2>>
  Some text recognition results may not be accurate, so replacements are performed. Optional.

• order_by: string
  How the results are sorted. Optional, default is Horizontal.
  Possible values: Horizontal | Vertical | Area | Length | Random | Expected.
  You can use it with the index field.

• index: int
  Index to hit. Optional, default is 0.
  If there are N results in total, the value range of index is [-N, N - 1], where negative numbers are converted to N - index using Python-like rules. If it exceeds the range, it is considered that there is no result in the current identification.

• only_rec: bool
  Whether to recognize only (without detection, requires precise roi). Optional, default is false.

• model: string
  Model folder path. Use a relative path to the "model/ocr" folder. Optional, default is empty.
  If empty, it will use the models in the root of the "model/ocr" folder. The folder should include three files: rec.onnx, det.onnx, and keys.txt.

• color_filter: string 💡 v5.8
  Color filter. Specify a ColorMatch node name. The image will be binarized using that node's color parameters (method, lower, upper) before being sent to OCR recognition. Optional, default is empty.
  Only the color binarization logic of the referenced node is used; its count, order_by, and other result parameters are not involved.
  OCR nodes with this field set will not participate in batch optimization.

NeuralNetworkClassify

Deep learning classification, to determine if the image in a fixed position matches the expected "category."

This algorithm property requires additional fields:

• roi: array<int, 4> | string
  Same as DirectHit.roi.

• roi_offset: array<int, 4>
  Same as DirectHit.roi_offset.

• labels: list<string, >
  Labels, meaning the names of each category. Optional.
  It only affects debugging images and logs. If not filled, it will be filled with "Unknown."

• model: string
  Model file path. Use a relative path to the "model/classify" folder. Required.
  Currently, only ONNX models are supported. Refer to NNClassify Recipe.

• expected: int | list<int, >
  The expected category index. Optional, default matches all.

• order_by: string
  How the results are sorted. Optional, default is Horizontal.
  Possible values: Horizontal | Vertical | Score | Random | Expected.
  You can use it with the index field.

• index: int
  Index to hit. Optional, default is 0.
  If there are N results in total, the value range of index is [-N, N - 1], where negative numbers are converted to N - index using Python-like rules. If it exceeds the range, it is considered that there is no result in the current identification.

For example, if you want to recognize whether a cat or a mouse appears in a fixed position in the image, and you've trained a model that supports this three-category classification, and you want to click when it recognizes a cat or a mouse but not when it recognizes a dog, the relevant fields would be:

{
    "labels": ["Cat", "Dog", "Mouse"],
    "expected": [0, 2]
}

Please note that these values should match the actual model output.

NeuralNetworkDetect

Deep learning object detection, an advanced version of "find image."

The main difference from classification is the flexibility to find objects at arbitrary positions. However, this often requires more complex models, more training data, longer training times, and significantly higher resource usage during inference.

This algorithm property requires additional fields:

• roi: array<int, 4> | string
  Same as DirectHit.roi.

• roi_offset: array<int, 4>
  Same as DirectHit.roi_offset.

• labels: list<string, >
  Labels, meaning the names of each category. Optional.
  It only affects debugging images and logs. If not filled, it will be automatically read from the model metadata (supports reading from names, name, labels, class_names fields), generally no need to set manually. If the model metadata also doesn't contain labels, it will be filled with "Unknown."

• model: string
  Model file path. Use a relative path to the "model/detect" folder. Required.
  Currently supports ONNX models exported from YOLOv8 and YOLOv11. Other Yolo models with the same input/output should theoretically be supported but are untested.
  Training reference: NNDetect Recipe.

• expected: int | list<int, >
  The expected category index.

• threshold: double | list<double, >
  Model confidence threshold. Optional, default is 0.3.
  If it's an array, its length should match the length of the expected array.

• order_by: string
  How the results are sorted. Optional, default is Horizontal.
  Possible values: Horizontal | Vertical | Score | Area | Random | Expected.
  You can use it with the index field.

• index: int
  Index to hit. Optional, default is 0.
  If there are N results in total, the value range of index is [-N, N - 1], where negative numbers are converted to N - index using Python-like rules. If it exceeds the range, it is considered that there is no result in the current identification.

For example, if you want to detect cats, dogs, and mice in an image and only click when a cat or a mouse is detected but not when a dog is detected, the relevant fields would be:

{
    "labels": ["Cat", "Dog", "Mouse"],
    "expected": [0, 2]
}

Please note that these values should match the actual model output.

And

💡 v5.3
Composite recognition (logical AND). All sub-recognitions must succeed for the node to be recognized.

This algorithm property requires additional fields:

• all_of: list<string | object>
  Sub-recognitions array. All sub-recognitions must succeed for the node to be recognized. Required.
  Each element can be:

  • string 💡 v5.7: node name reference, uses that node's recognition algorithm and parameters at runtime
  • object: inline recognition definition, uses the same format as normal nodes (supports both v1 and v2 forms, and they can be mixed)

• box_index: int
  Selects which sub-recognition's result box will be used as the overall recognition box. Optional, default is 0.
  Must satisfy 0 <= box_index < all_of.length.

• sub_name: string
  Optional alias for a sub-recognition element.
  Later sub-recognitions can use roi: sub_name to reference the filtered boxes of a previous sub-recognition.
  Available only within the current node.

Example:

{
    "NodeA": {
        "recognition": "And",
        "all_of": [
            {
                "sub_name": "icon",
                "recognition": "TemplateMatch",
                "template": "storage_icon.png",
                "threshold": 0.7
            },
            {
                "recognition": "OCR",
                "roi": "icon",
                "roi_offset": [0, 0, 100, 100],
                "expected": "Storage"
            }
        ],
        "box_index": 0
    }
}

Example using node name references:

{
    "CheckIcon": {
        "recognition": "TemplateMatch",
        "template": "icon.png"
    },
    "CheckText": {
        "recognition": "OCR",
        "expected": "Confirm"
    },
    "ConfirmDialog": {
        "recognition": "And",
        "all_of": [
            "CheckIcon",   // References CheckIcon node's recognition params
            "CheckText"    // References CheckText node's recognition params
        ]
    }
}

For Pipeline v2, put these fields in recognition.param as usual.

Or

💡 v5.3
Composite recognition (logical OR). Recognition succeeds when the first sub-recognition matches, subsequent ones are not executed.

This algorithm property requires additional fields:

• any_of: list<string | object>
  Sub-recognitions array. Recognition succeeds when the first sub-recognition matches, subsequent ones are not executed. Required.
  Each element can be:
  • string 💡 v5.7: node name reference, uses that node's recognition algorithm and parameters at runtime
  • object: inline recognition definition, uses the same format as normal nodes (supports both v1 and v2 forms, and they can be mixed)

Example:

{
    "NodeB": {
        "recognition": "Or",
        "any_of": [
            {
                "recognition": "TemplateMatch",
                "template": "confirm.png"
            },
            {
                "recognition": "OCR",
                "expected": ["OK", "Confirm"]
            }
        ]
    }
}

Example using node name references:

{
    "ConfirmButton": {
        "recognition": "TemplateMatch",
        "template": "confirm.png"
    },
    "CancelButton": {
        "recognition": "TemplateMatch",
        "template": "cancel.png"
    },
    "AnyButton": {
        "recognition": "Or",
        "any_of": [
            "ConfirmButton",  // References ConfirmButton node's recognition params
            "CancelButton"    // References CancelButton node's recognition params
        ]
    }
}

For Pipeline v2, put these fields in recognition.param as usual.

Custom

Execute the recognition handle passed in through the MaaResourceRegisterCustomRecognition interface

This algorithm property requires additional fields:

• custom_recognition: string
  Recognition name, same as the one passed in through the registration interface. It will also be passed through MaaCustomRecognitionCallback.custom_recognition_name. Required.

• custom_recognition_param: any
  Recognition parameter, any type, will be passed through MaaCustomRecognitionCallback.custom_recognition_param. Optional, default null.

• roi: array<int, 4> | string
  Same as DirectHit.roi, will be passed through MaaCustomRecognitionCallback.roi. Optional, default [0, 0, 0, 0].

• roi_offset: array<int, 4>
  Same as DirectHit.roi_offset.

Action Types

DoNothing

Does nothing.

Click

Clicks.

Additional properties for this action:

• target: true | string | array<int, 2> | array<int, 4>
  The position of the click target. Optional, default is true.

  • true: The target is the position just recognized in this node (i.e., itself).
  • string: Enter the node name, as the target, to use the position recognized by a previously executed node. Also supports [Anchor]AnchorName format to reference the node corresponding to an anchor 💡 v5.9. If the referenced pre-task or anchor has no recognition result, the action is treated as failed.
  • array<int, 2>: Fixed coordinate point [x, y] 💡 v5.0. Supports negative values 💡 v5.6, meaning calculating from right/bottom edge.
  • array<int, 4>: Fixed coordinate area [x, y, w, h]. A point is sampled inside the rectangle with higher probability near center. Supports negative values 💡 v5.6, same meaning as roi.

• target_offset: array<int, 4>
  Additional movement from the target before clicking, where the four values are added together. Optional, default is [0, 0, 0, 0].

• contact: uint 💡 v5.0
  Contact id used to distinguish different touch points. Optional, default 0.

  • Adb Controller: Finger id (0 for first finger, 1 for second finger, etc., maximum is 10)
  • Win32 Controller: Mouse button id (0 for left, 1 for right, 2 for middle, 3 for XBUTTON1, 4 for XBUTTON2)

• pressure: int 💡 v5.0
  Touch pressure. Optional, default 1.

LongPress

Long press。

Additional properties for this action:

• target: true | string | array<int, 2> | array<int, 4>
  The position of the long press target. Optional, default is true. The values are the same as Click.target.

• target_offset: array<int, 4>
  Additional movement from the target before long pressing, where the four values are added together. Optional, default is [0, 0, 0, 0].

• duration: uint
  Duration of the long press in milliseconds. Optional, default is 1000.

• contact: uint 💡 v5.0
  Contact id used to distinguish different touch points. Optional, default 0.

  • Adb Controller: Finger id (0 for first finger, 1 for second finger, etc., maximum is 10)
  • Win32 Controller: Mouse button id (0 for left, 1 for right, 2 for middle, 3 for XBUTTON1, 4 for XBUTTON2)

• pressure: int 💡 v5.0
  Touch pressure. Optional, default 1.

Swipe

Linear swipe.

Additional properties for this action:

• begin: true | string | array<int, 2> | array<int, 4>
  The starting point of the swipe. Optional, default is true. The values are the same as Click.target.

• begin_offset: array<int, 4>
  Additional movement from the begin before swiping, where the four values are added together. Optional, default is [0, 0, 0, 0].

• end: true | string | array<int, 2> | array<int, 4> | list<true | string | array<int, 2> | array<int, 4>>
  The end point of the swipe. Optional, default is true. The values are the same as Click.target.
  💡 v4.5.x version adds support for list, which can be used to add swipe waypoints! Unlike multiple swipes, multiple ends will not lift between them, i.e., a single polyline swipe.

• end_offset: array<int, 4> | list<array<int, 4>>
  Additional movement from the end before swiping, where the four values are added together. Optional, default is [0, 0, 0, 0].

• duration: uint | list<uint,>
  Duration of the swipe in milliseconds. Optional, default is 200.

• end_hold: uint | list<uint,>
  After swiping to the end point, wait for an additional time before lifting, in ms. Optional, default 0.

• only_hover: bool
  Only move the mouse cursor, no press/release action. Optional, default false.

• contact: uint 💡 v5.0
  Contact id used to distinguish different touch points. Optional, default 0.

  • Adb Controller: Finger id (0 for first finger, 1 for second finger, etc., maximum is 10)
  • Win32 Controller: Mouse button id (0 for left, 1 for right, 2 for middle, 3 for XBUTTON1, 4 for XBUTTON2)

• pressure: int 💡 v5.0
  Touch pressure. Optional, default 1.

MultiSwipe

Multi-finger linear swipe.

Additional properties for this action:

• swipes: list<object,>
  Multi swipe array. Required.
  The order of the array elements has no effect, only based on starting.

  • starting: uint
    Swipe start time, in milliseconds. Optional, default 0.
    MultiSwipe additional field, the swipe will start pressing at the starting millisecond in this action.

  • begin: true | string | array<int, 2> | array<int, 4>
    The starting point of the swipe. Optional, default is true. The values are the same as Click.target.

  • begin_offset: array<int, 4>
    Additional movement from the begin before swiping, where the four values are added together. Optional, default is [0, 0, 0, 0].

  • end: true | string | array<int, 2> | array<int, 4> | list<true | string | array<int, 2> | array<int, 4>>
    The end point of the swipe. Optional, default is true. The values are the same as Click.target.
    💡 v4.5.x version adds support for list, which can be used to add swipe waypoints! Unlike multiple swipes, multiple ends will not lift between them, i.e., a single polyline swipe.

  • end_offset: array<int, 4> | list<array<int, 4>>
    Additional movement from the end before swiping, where the four values are added together. Optional, default is [0, 0, 0, 0].

  • duration: uint | list<uint,>
    Duration of the swipe in milliseconds. Optional, default is 200.

  • end_hold: uint | list<uint,>
    After swiping to the end point, wait for an additional time before lifting, in ms. Optional, default 0.

  • only_hover: bool
    Only move the mouse cursor, no press/release action. Optional, default false.

  • contact: uint 💡 v5.0
    Contact id used to distinguish different touch points. Optional, default uses the index of the swipe in the array as the contact id (starting from 0).

    • Adb Controller: Finger id (0 for first finger, 1 for second finger, etc., maximum is 10)
    • Win32 Controller: Mouse button id (0 for left, 1 for right, 2 for middle, 3 for XBUTTON1, 4 for XBUTTON2)

  • pressure: int 💡 v5.0
    Touch pressure. Optional, default 1.

For example:

{
    "A": {
        "action": "MultiSwipe",
        "swipes": [
            {
                "begin": [],
                "end": []
            },
            {
                "starting": 500,
                "begin": [],
                "end": []
            }
        ]
    }
}

TouchDown

💡 v5.0
Press a touch contact.

Additional properties for this action:

• contact: uint 💡 v5.0
  Contact id used to distinguish different touch points. Optional, default 0.

  • Adb Controller: Finger id (0 for first finger, 1 for second finger, etc., maximum is 10)
  • Win32 Controller: Mouse button id (0 for left, 1 for right, 2 for middle, 3 for XBUTTON1, 4 for XBUTTON2)

• target: true | string | array<int, 4> | array<int, 2>
  Touch target position. Optional, default true. Same semantics as Click.target.

• target_offset: array<int, 4>
  Offset applied on top of target. Optional, default [0, 0, 0, 0].

• pressure: int 💡 v5.0
  Touch pressure. Optional, default 0. The actual range depends on the controller implementation.

TouchMove

💡 v5.0
Move an existing touch contact. Fields are identical to TouchDown and update the contact position.

TouchUp

💡 v5.0
Release a touch contact.

• contact: uint 💡 v5.0
  Contact id used to distinguish different touch points. Optional, default 0.
  • Adb Controller: Finger id (0 for first finger, 1 for second finger, etc., maximum is 10)
  • Win32 Controller: Mouse button id (0 for left, 1 for right, 2 for middle, 3 for XBUTTON1, 4 for XBUTTON2)

Scroll

💡 v5.1
Mouse wheel scroll.

Additional properties for this action:

• target: true | string | array<int, 2> | array<int, 4> 💡 v5.5
  Position of the scroll target. The mouse will first move to this position before scrolling. Optional, default is true.

  • true: Target is the position just recognized in this node (i.e., itself).
  • string: Fill in a node name; the target is the position recognized by a previously executed node. Also supports [Anchor]AnchorName format to reference the node corresponding to an anchor 💡 v5.9. If the referenced pre-task or anchor has no recognition result, the action is treated as failed.
  • array<int, 2>: Fixed coordinate point [x, y].
  • array<int, 4>: Fixed coordinate area [x, y, w, h], a random point will be selected within the rectangle (with higher probability towards the center and lower probability at the edges). Use [0, 0, 0, 0] for full screen.

• target_offset: array<int, 4> 💡 v5.5
  Additional offset applied to target for the scroll position, each of the four values is added respectively. Optional, default is [0, 0, 0, 0].

• dx: int
  Horizontal scroll distance, positive values scroll right, negative values scroll left. Optional, default is 0.

• dy: int
  Vertical scroll distance, positive values scroll up, negative values scroll down. Optional, default is 0.

NOTE

• Win32 controllers and custom controllers that implement scroll support scroll operations.
• Posting a Scroll action to a controller that does not implement scroll will cause the action to fail.
• The dx/dy values are sent directly as scroll increments. The Windows standard wheel increment is 120 (WHEEL_DELTA) per notch. Using multiples of 120 is recommended for best compatibility.

ClickKey

Click a key.

Additional properties for this action:

• key: int | list<int, >
  The key(s) to click, supporting only virtual key code of corresponding controller. Required.

  • Adb Controller
  • Win32 Controller
  • WlRoots Controller

NOTE

PlayCover Controller does not support key operations.

LongPressKey

Long Press a key.

Additional properties for this action:

• key: int | list<int, >
  The key to press, supporting only virtual key code of corresponding controller. Required.

• duration: uint
  Duration of the long press in milliseconds. Optional, default is 1000.

KeyDown

💡 v5.0
Press a key without releasing. Combine with KeyUp to customize key sequences.

Additional properties for this action:

• key: int
  The key to press, supporting only virtual key code of corresponding controller. Required.

KeyUp

💡 v5.0
Release a key. Typically follows a KeyDown to end the key press state.

Additional properties for this action:

• key: int
  The key to release, supporting only virtual key code of corresponding controller. Required.

InputText

Inputs text.

Additional properties for this action:

• input_text: string
  The text to input; some controllers only support ASCII. Required.

NOTE

PlayCover Controller does not support text input.

StartApp

Starts an app.

Additional properties for this action:

• package: string
  Launch entry. Required.
  You need to enter the package name or activity, for example, com.hypergryph.arknights or com.hypergryph.arknights/com.u8.sdk.U8UnityContext.

NOTE

PlayCover Controller does not support starting apps. You need to manually start the app in PlayCover.

StopApp

Closes an app.

Additional properties for this action:

• package: string
  The app to close. Required.
  You need to enter the package name, for example, com.hypergryph.arknights.

StopTask

Stops the current task chain (the individual task chain passed to MaaTaskerPostTask).

Command

Execute a command.

This action attribute requires additional fields:

• exec: string
  The path of the program to be executed. Required.

• args: list<string,>
  The arguments to be executed. Optional.
  supports runtime parameters replacement:

  • {ENTRY}: Entry name.
  • {NODE}: Node name.
  • {IMAGE}: The path to the file where the screenshot is saved. The file is deleted before the process exits. Please copy it by yourself if you want to save it permanently.
  • {BOX}: Identify the hit target, the format is [x, y, w, h].
  • {RESOURCE_DIR}: The path of the resource folder loaded last time.
  • {LIBRARY_DIR}: The path of the folder where the MaaFW library is located.

• detach: bool
  Detach the child process, that is, do not wait for the child process to complete, and continue directly to the next task. Optional, default false.

Example:

{
    "NodeA": {
        "action": "Command",
        "exec": "Python",
        "args": [
            "{RESOURCE_DIR}/my_script/test.py"
            "Haha",
            "{IMAGE}",
            "{NODE}",
            "{BOX}"
        ]
    },
    "NodeB": {
        "action": "Command",
        "exec": "{RESOURCE_DIR}/my_exec/my_exec.exe"
    }
}

The actual command is:

# NodeA
Python C:/MaaXXX/resource/my_script/test.py Haha C:/temp/123.png NodeA [0,0,0,0]

# NodeB
C:/MaaXXX/resource/my_exec/my_exec.exe

Shell

💡 v5.3
Executes a shell command on an ADB device.

Additional properties for this action:

• cmd: string
  The shell command to execute. Required.
  For example, getprop ro.build.version.sdk or settings put global animator_duration_scale 0.

• shell_timeout: int 💡 v5.8
  Command execution timeout in milliseconds. Optional, default is 20000 (20 seconds).
  Set to -1 to wait indefinitely without timeout.

Note: This action is only valid for ADB controllers. The command output can be retrieved via MaaTaskerGetActionDetail in the action detail.

Screencap

Save the current screencap to a file. Screencaps are saved in the log_dir/screencap/ directory.

Additional properties for this action:

• filename: string
  Filename for the saved screencap (without extension). Optional, defaults to timestamp_nodename format.

• format: string
  Image format. Optional, default is "png" (lossless).
  Possible values: "png" | "jpg" | "jpeg"

• quality: int
  Image quality (0-100), only effective for jpg / jpeg format. Optional, default is 100.
  png format always uses lossless compression and this field has no effect.

The screencap file path can be retrieved via MaaTaskerGetActionDetail in the filepath field of the action detail.

Custom

Execute the action handle passed in through the MaaResourceRegisterCustomAction interface

This action attribute requires additional fields:

• custom_action: string
  Action name, same as the one passed in through the registration interface. It will also be passed through MaaCustomActionCallback.custom_action_name. Required.

• custom_action_param: any
  Action parameter, any type, will be passed through MaaCustomActionCallback.custom_action_param. Optional, default null.

• target: true | string | array<int, 2> | array<int, 4>
  The position of the target, which will be passed through MaaCustomActionCallback.box. Optional, default true. Same as Click.target.

• target_offset: array<int, 4>
  Same as Click.target_offset.

Node Attributes

💡 v5.1
Node Attributes allow you to specify additional behavioral control parameters for each node in next and on_error lists. Since v5.1, node attributes can be set using two syntax forms.

Basic Syntax

By default, node lists contain only node names:

{
    "A": {
        "next": [
            "B",
            "C",
            "D"
        ]
    }
}

Attribute Setting Methods

Object Form

Use a NodeAttr object to explicitly specify the node name and attributes:

{
    "A": {
        "next": [
            "B",
            {
                "name": "C",
                "jump_back": true
            },
            "D"
        ]
    }
}

Prefix Form

Use square bracket prefixes to specify attributes directly before the node name:

{
    "A": {
        "next": [
            "B",
            "[JumpBack]C",
            "D"
        ]
    }
}

Both forms are functionally equivalent. You can choose based on your preference. The two forms can be mixed within an array, creating a heterogeneous array.

Available Attributes

jump_back / [JumpBack]

Type: boolean
Default: false
Description: Enables jump-back mechanism. When this node is recognized and matched, after all subsequent nodes in its chain have completed execution, the system will return to the parent node and continue attempting to recognize the parent node's next list.

Execution Flow:

1. The parent node recognizes nodes in the next list sequentially
2. If a node with jump_back attribute is recognized and matched, execute that node and its subsequent node chain
3. After the node chain completes execution, return to the parent node
4. The parent node continues recognition from the beginning of the next list

Example:

{
    "A": {
        "next": [
            "B",
            "C",
            "[JumpBack]D",
            "E"
        ]
    }
}

Execution flow:

• Node A attempts to recognize B, C, D, E in sequence
• If D is recognized and matched (assuming B and C are not), execute D and its subsequent node chain
• After D's node chain completes, return to node A
• Node A restarts recognition from B, continuing to attempt B, C, D, E

Use Cases:
Suitable for exception handling scenarios, such as recognizing and handling network disconnection prompts, permission request dialogs, and other temporary interfaces. After handling, the original flow continues.

Compatibility Note:
Similar to the deprecated is_sub field, but jump_back only applies to specific nodes in the current next list, rather than the entire node definition.

anchor / [Anchor]

Type: boolean
Default: false
Description: Enables anchor reference. When this attribute is true, the name field is treated as an anchor name rather than a node name, and resolves at runtime to the last node that set this anchor.

Usage:

1. First, set an anchor name in a node using the anchor field
2. Then, reference this anchor in next or on_error using [Anchor] or anchor

Basic Example:

{
    "A": {
        "anchor": "X",  // Set anchor X to the current node A
        "next": ["C"]
    },
    "B": {
        "anchor": "X",  // Reset anchor X to the current node B (overwriting the previous setting)
        "next": ["C"]
    },
    "C": {
        "next": [
            "D",
            "[Anchor]X"  // Reference anchor X, jumps to the last node that set this anchor (B)
        ]
    }
}

Equivalent object form:

{
    "C": {
        "next": [
            "D",
            { "name": "X", "anchor": true }
        ]
    }
}

Advanced Example: Specifying Anchor Target Node

Using the object format, you can set an anchor to a different node, or clear an anchor:

{
    "A": {
        "anchor": {"X": "TargetNode"},  // Set anchor X to TargetNode
        "next": ["B"]
    },
    "B": {
        "next": ["[Anchor]X"]  // Reference anchor X, jumps to TargetNode
    },
    "TargetNode": {
        // ...
    }
}

Support for setting multiple anchors simultaneously:

{
    "A": {
        "anchor": {
            "X": "TargetX",  // Anchor X -> TargetX
            "Y": "",         // Clear anchor Y (empty string means clear the anchor)
            "Z": "TargetZ"   // Anchor Z -> TargetZ
        },
        "next": ["B"]
    }
}

Use Cases:

• Basic usage: Suitable for scenarios requiring dynamic node references, such as when multiple nodes may handle the same type of event and you need to return to "the last node that handled this event" to continue execution.
• Advanced usage: Allows mapping anchors to specific target nodes, or clearing anchors with empty strings, providing more flexible flow control capabilities, similar to introducing a variable mechanism to the pipeline.

Future Extensions

More node attributes are planned and will be introduced in future versions.

Result Sorting Methods

Recognition algorithms may return multiple results. Use the order_by field to specify the sorting method, combined with the index field to select a specific result.

Horizontal

Sort horizontally (left to right, then top to bottom for same column).
Sorting rule: Sort by x coordinate ascending first, then by y coordinate ascending when x is equal.

| 1 3 5 7 |
| 2 4 6 8 |

Vertical

Sort vertically (top to bottom, then left to right for same row).
Sorting rule: Sort by y coordinate ascending first, then by x coordinate ascending when y is equal.

| 1 2 3 4 |
| 5 6 7 8 |

Score

Sort by matching score in descending order. Higher scores are ranked first.
Suitable for scenarios where you want to prioritize the highest confidence result.

Area

Sort by bounding box area in descending order. Larger areas are ranked first.
Applicable to FeatureMatch, ColorMatch, OCR, and NeuralNetworkDetect algorithms.

Length

Sort by recognized text length. Only applicable to OCR algorithm.
Longer text results are ranked first.

Random

Randomly shuffle the result order.
Suitable for scenarios requiring random selection.

Expected

💡 v5.1
Sort by the order specified in the expected field.
For OCR, sort by the order of regex patterns in the expected list; results matching earlier patterns are ranked first.
For NeuralNetworkClassify and NeuralNetworkDetect, sort by the order of class indices in the expected list.
Results not matching any expected value are ranked last.

Waiting for the Screen to Stabilize

Waits for the screen to stabilize. It exits the action only when there is no significant change in the screen for a certain continuous time.

The field value can be a uint or an object. For example:

{
    "NodeA": {
        "pre_wait_freezes": 500
    },
    "NodeB": {
        "post_wait_freezes": {
            // more properties ...
        }
    }
}

If the value is an object, you can set additional fields:

• time: uint
  It exits the action only when there has been no significant change in the screen for "time" milliseconds in a row. Optional, default is 1.

• target: true | string | array<int, 2> | array<int, 4>
  The position of the target to wait for. Optional, default is true. The values are the same as Click.target.

• target_offset: array<int, 4>
  Additional movement from the target to be used as the waiting target, where the four values are added together. Optional, default is [0, 0, 0, 0].

• threshold: double
  The template matching threshold to determine "no significant change." Optional, default is 0.95.

• method: int
  The template matching algorithm to determine "no significant change," i.e., cv::TemplateMatchModes. Optional, default is 5. The same as TemplateMatch.method.

• rate_limit: uint
  Identification rate limit, in milliseconds. Optional, default 1000.
  Each identification consumes at least rate_limit milliseconds, and sleep will be executed if the time is less than that.

• timeout: int
  Timeout for recognizing, in milliseconds. Optional, default is 20 * 1000 milliseconds (20 seconds).
  Set to -1 to wait indefinitely without timeout.

Node Notifications

NOTE

Node notifications depend on the upper-layer implementation and are not natively supported by MaaFramework.
Please refer to the general UI documentation or code you are using to confirm if this feature is supported.

By configuring the focus field, you can have the UI display custom messages to users at specific stages of node execution. Please refer to Project Interface Protocol.