Author : Robert (robert@dfrobot.com)
Version : 0.1
Date : 08/04/2020
Github : Github
USB Connection (Mac/Windows/Linux -> Huskylens)
pip3 install pyserial pypng
- Place the huskylib.py file within your projects folder
from huskylib import HuskyLensLibrary
hl = HuskyLensLibrary("SERIAL", "/dev/ttyUSB0")
print(h1.knock()
Raspberry Pi (I2C -> Huskylens)
- Please refer to our full guide here:
You can test out all the functions in our provided example script. Simply run
exampleHL.py
after changing the the connection settings in the beginning of the file. You will need a terminal / IDE to interact with the script.
- function_name(ARG1,ARG2,…)
- Description:
- Short description of functions overall inputs and its corresponding functionality
- Arguments:
- Arg1 : (Variable Type) Description
- Arg2 : (Variable Type) Description
- Returns:
- Short description the return value of the function, NONE if the function does not return
- HuskyLensLibrary(“COM_PROTOCOL”, “COM_PORT”, channel, address)
-
Description: Instantiate the HuskyLens class and automatically connect to your HuskyLens. This return the main object that you will run all functions on.
-
- Arguments:
"COM_PROTOCOL"
: (String) Either"SERIAL"
for USB connections or"I2C"
for Raspberry Pi I2C."COM_PORT"
: (String) COM Port of the HuskyLens. Not needed for"I2C"
connections."i2c_channel"
: (Integer) I2C Channel, refer to Raspberry Pi Guide. Not needed for"SERIAL"
."i2c_channel"
: (Integer) I2C Channel, refer to Raspberry Pi Guide. Not needed for"SERIAL"
.
-
Returns: Returns
HuskyLens
object -
- Examples:
hl = HuskyLensLibrary("SERIAL", "/dev/ttyUSB0")
hl = HuskyLensLibrary("I2C","", address=0x32, channel=0)
- knock()
-
Description: Send a simple knock to the HuskyLens to ensure that you are connected and can communicate.
-
Returns: Returns “Knock Received” on success
- frameNumber( )
-
Description: Get the number of frame HUSKYLENS have processed.
-
Returns: Frame Count
- count( )
-
Description: Get the number of learned and unlearned objects on the screen.
-
Returns: Number of Ojbects on the Screen
- learnedObjCount( )
-
Description: Get the total number of learned objects for the current running algorithm, objects do not need to be present on screen.
-
Returns: Number of learned objects
Data Format
Data corresponds to either
block
information for all algorithms except Line Tracking, which instead will returnarrow
information. These directly reflect the blocks/arrows you see on the HusyLens UI.class Block: Members: x => (Integer) x coordinate of the center of the square y => (Integer) y coordinate of the center of the square width => (Integer) width of the square height => (Integer) height of the square ID => (Integer) Objects ID (if not learned, ID is 0) learned => (Boolean) True if the object is learned type => "BLOCK" class Arrow: Members: xTail => (Integer) x coordinate of the tail of the arrow yTail => (Integer) y coordinate of the tail of the arrow xHead => (Integer) x coordinate of the head of the arrow yHead => (Integer) y coordinate of the head of the arrow ID => (Integer) Objects ID (if not learned, ID is 0) learned => (Boolean) True if the object is learned type => "ARROW"
Returned data will be an array of either block or arrow information.:
**[block1 , block2, ... blockN]
or[arrow1 , arrow2, ... arrowN]
- requestAll( )
- Description: Request all block or arrow data from HuskyLens. This will return block/arrow data for all learned and unlearned objects that are visible on the screen.
- Returns: Returns data array
[block1 , block2, ... blockN]
or[arrow1 , arrow2, ... arrowN]
- blocks()
- Description: Request all block data from HuskyLens. This will return block data for all learned and unlearned objects that are visible on the screen.
- Returns: Returns data array
[block1 , block2, ... blockN]
- arrows()
- Description: Request all arrow data from HuskyLens. This will return block data for all learned and unlearned objects that are visible on the screen.
- Note this should be used on the Line Tracking algorithm
- Returns: Returns data array
[arrow1 , arrow2, ... arrowN]
- learned( )
- Description: Request all block or arrow data from HuskyLens . This will return block/arrow data for all learned objects that are visible on the screen, unlearned objects are ignored.
- Returns: Returns data array
[block1 , block2, ... blockN]
or[arrow1 , arrow2, ... arrowN]
- learnedBlocks( )
- Description: Request all block data from HuskyLens . This will return block data for all learned objects that are visible on the screen, unlearned objects are ignored.
- Returns: Returns data array
[block1 , block2, ... blockN]
- learnedArrows( )
- Description: Request all arrow data from HuskyLens . This will return arrow data for all learned objects that are visible on the screen, unlearned objects are ignored.
- Note this should be used on the Line Tracking algorithm
- Returns: Returns data array
[arrow1 , arrow2, ... arrowN]
- getObjectByID( ID )
- Description: Request all block or arrow data from HuskyLens that have a designated ID and are visible on screen.
-
- Arguments:
ID
: (Integer) The desiredID
of the object
- Returns: Returns data array
[block1 , block2, ... blockN]
or[arrow1 , arrow2, ... arrowN]
- getBlocksByID( ID )
- Description: Request all block data from HuskyLens that have a designated ID and are visible on screen.
-
- Arguments:
ID
: (Integer) The desiredID
of the object
- Returns: Returns data array
[block1 , block2, ... blockN]
- getArrowsByID( ID )
- Description: Request all arrow data from HuskyLens that have a designated ID and are visible on screen.
- Note this should be used on the Line Tracking algorithm
-
- Arguments:
ID
: (Integer) The desiredID
of the object
- Returns: Returns data array
[arrow1 , arrow2, ... arrowN]
- algorthim( algorithmName)
-
Description: Switch the HuskyLens to a specific algorithm.
-
- Arguments:
-
algorithmName
: (String) The desired algorithm to switch to.-
“ALGORITHM_OBJECT_TRACKING”
“ALGORITHM_FACE_RECOGNITION”
“ALGORITHM_OBJECT_RECOGNITION”
“ALGORITHM_LINE_TRACKING”
“ALGORITHM_COLOR_RECOGNITION”
“ALGORITHM_TAG_RECOGNITION”
“ALGORITHM_OBJECT_CLASSIFICATION”
-
Returns: Returns “Knock Received” on success.
- learn( ID )
-
Description: Learn the current recognized object on screen with a chosen ID
-
- Arguments:
ID
: (Integer) The desiredID
of the object (1-1023 range)
-
Returns: Returns “Knock Received” on success.
- forget( )
-
Description: Forget learned objects for the current running algorithm.
-
Returns: Returns “Knock Received” on success.
- setCustomName(“Name_Value”, objectID)
- Description: Set a custom name for a learned object with a specified ID. For example, if you have learned your face with an ID of 1, you can use huskylens.setCustomName(“Robert”,1) to rename the learned face to “Robert”.
-
- Arguments:
"Name_Value"
: (String) value for the desired nameobjectID
: (Interger) value for the learned object ID you wish to change
- Returns: Returns “Knock Received” on success
- customText(“Text_Value”, X, Y)
- Description:
-
Place a string of text (less than 20 characters) on top of the HuskyLens UI. The position of the texts (X,Y) coordinate is the top left of the text box.
-
You can have at most 10 custom texts on the UI at once, and if you continue adding texts you will replace previous texts in a circular fashion. For example, if you enter 10 texts you will fill the text buffer. If you then insert a new text object, you will overwrite the first text position (textBuffer[0]). Inserting another new text object will overwrite the second text position (textBuffer[1]).
-
Each text is uniquely identified by its (X,Y) coordinate, so you can replace the text string at a (X,Y) coordinate instead of adding a new text object. For example, if you insert “TEST_1” at (120,120) and then later submit “TEST_2” at (120,120), you will replace the string “TEST_1” with “TEST_2” and maintain an overall text count of 1.
-
-
- Arguments:
"Text_Value"
: (String) value for the desired textX
: (Integer) The X coordinate for the UI Object (0-320)Y
: (Integer) The Y coordinate for the UI Object (0-240)
- Returns: Returns “Knock Received” on success
- clearText()
- Description: Clear and delete all custom UI texts from the screen.
- Returns: Returns “Knock Received” on success
- saveModelToSDCard( fileNum )
- Description: Save the current algorithms model file (its learned object data) to the SD Card. The file will be the in the format “AlgorithimName_Backup_FileNum.conf”
-
- Arguments:
fileNum
: (Integer) The specified file number to be used in the name for the file
- Returns: Returns “Knock Received” on success. If there is no SD Card inserted or an SD Card Error, there will be a UI popup on the HuskyLens outlining the issue.
- loadModelFromSDCard( fileNum )
- Description: Load a model file from the SD Card to the current algorithm and refresh the algorithm. The loaded file will be the following format “AlgorithimName_Backup_FileNum.conf”
-
- Arguments:
fileNum
: (Integer) The specified file number to be used in the name for the file
- Returns: Returns “Knock Received” on success. If there is no SD Card inserted or an SD Card Error, there will be a UI popup on the HuskyLens outlining the issue.
- savePictureToSDCard( )
- Description: Save a photo from the HuskyLens camera onto the SD Card.
- Returns: Returns “Knock Received” on success. If there is no SD Card inserted or an SD Card Error, there will be a UI popup on the HuskyLens outlining the issue.
- saveScreenshotToSDCard( )
- Description: Save a screenshot of the HuskyLens UI onto the SD Card.
- Returns: Returns “Knock Received” on success. If there is no SD Card inserted or an SD Card Error, there will be a UI popup on the HuskyLens outlining the issue.