vision_detect · Object, QR, hand and pose recognition

Detects objects, QR codes, poses, hand gestures and markers.

Class: putTextPIL() Detect

openpibo.vision_detect.putTextPIL(img, text, points, size=30, colors=(255, 255, 255))

Writes text on an image. (Korean/English supported - uses pillow)- COPY

Parameters:

• img (numpy.ndarray) – Image object

• text (str) – Text to display

• points (tuple(int, int)) – Top-left coordinates of the text block (x, y)

• size (int) – Font size of the text

• colors (tuple(int, int, int)) – Text color BGR value (b, g, r) or hex value ‘#rrggbb’

class openpibo.vision_detect.Detect

Bases: object

Functions: load_hand_gesture_model() detect_object() detect_qr() detect_pose() analyze_pose() classify_image() object_tracker_init() track_object() detect_marker() detect_marker_vis()

A class that provides various detection functions.

• Object detection among 80 classes (YOLO11s, onnxruntime)

• QR/barcode detection (pyzbar)

• Pose detection

• Image classification

example:

from openpibo.vision_detect import Detect

detect = Detect()
# 아래의 모든 예제 이전에 위 코드를 먼저 사용합니다.

load_hand_gesture_model(modelpath='/home/pi/.model/hand/gesture_recognizer.task')

Loads a hand gesture recognition model.

Parameters:

modelpath (str) – Path of the hand gesture recognition model

recognize_hand_gesture(image)

Recognizes hand gestures.

Parameters:

img (numpy.ndarray) – Image object

Returns:

Hand gesture recognition result depending on the model

recognize_hand_gesture_vis(img, items)

Displays the hand gesture recognition result.

Parameters:

• img (numpy.ndarray) – Image object

• items (array) – Hand gesture recognition result

load_object_model(modelpath='/home/pi/.model/object/yolo11s.onnx')

Loads a detection model.

Parameters:

modelpath (str) – Path of the object detection model

detect_object(img)

Displays the object detection result.

Parameters:

• img (numpy.ndarray) – Image object

• items (array) – Object detection result

detect_object_vis(img, items)

Displays the object detection result.

Parameters:

• img (numpy.ndarray) – Image object

• items (array) – Object detection result

detect_qr(img)

Detects QR codes and barcodes in an image.

example:

img = camera.read()
detect.detect_qr(img)

Parameters:

img (numpy.ndarray) – Image object

Returns:

{"data": content, "type": barcode / QR code, "position":(startX,startY,endX,endY)}

detect_qr_vis(img, items)

Displays the QR/barcode result.

Parameters:

• img (numpy.ndarray) – Image object

• items (array) – QR detection result

detect_pose(img)

Detects poses in an image.

example:

img = camera.read()
detect.detect_pose(img)

Parameters:

img (numpy.ndarray) – Image object

Returns:

detection result

detect_pose_vis(img, items)

Displays the pose.

Parameters:

• img (numpy.ndarray) – Image object

• items (array) – Pose data

analyze_pose(data)

Analyzes the result of the detect_pose function.

example:

img = camera.read()
result = detect.detect_pose(img)
detect.analyze_pose(result)

Parameters:

data (dict) – Image object

Returns:

list of detected poses ['left_hand_up', 'right_hand_up', 'clap']

object_tracker_init(img, p)

Sets up an object tracker in an image.

example:

img = camera.read()
detect.object_tracker_init(img)

Parameters:

img (numpy.ndarray) – Image object

track_object(img)

Updates the object tracker in an image.

example:

img = camera.read()
detect.object_tracker_init(img, (10,10,100,100))
position = detect.track_object(img)

Parameters:

img (numpy.ndarray) – Image object

Returns:

x1,y1,x2,y2 updated object position

track_object_vis(img, item)

Displays the marker result.

Parameters:

• img (numpy.ndarray) – Image object

• items (array) – Marker result

detect_marker(img, marker_length=2)

Detects markers in an image. # cv2.aruco.DICT_4X4_50

example:

img = camera.read()
result = detect.detect_marker(img)

Parameters:

img (numpy.ndarray) – Image object

Returns:

[{"id": marker number, "center":  }, ...]

detect_marker_vis(img, items)

Displays the marker result.

Parameters:

• img (numpy.ndarray) – Image object

• items (array) – Marker result