CloudSoftwareHardware
Software Stack
DepthAI
OAK Apps
AI Models

ON THIS PAGE

  • Camera ROI-based exposure and focus
  • Demo
  • Setup
  • Pipeline
  • Source code

Camera ROI-based exposure and focus

This example lets user select a region of interest (ROI) on the frame (on the host computer), and after selection is complete, it will set the auto-exposure (AE) and auto-focus (AF) of the camera to the selected ROI.Similar application could be to set AF/AE based on object detection results, so the camera would automatically refocus and adjust exposure when a specific object is detected.

Demo

Setup

This example requires the DepthAI v3 API, see installation instructions.

Pipeline

React Flow

Source code

Python
C++

Python

Python
GitHub
1#!/usr/bin/env python3
2
3import cv2
4import depthai as dai
5
6# Create pipeline
7with dai.Pipeline() as pipeline:
8    # Define source and output
9    cam = pipeline.create(dai.node.Camera).build(dai.CameraBoardSocket.CAM_A)
10    cam_input_q = cam.inputControl.createInputQueue()
11    stream_q = cam.requestOutput((1920, 1080)).createOutputQueue()
12
13    cam_q_in = cam.inputControl.createInputQueue()
14
15    # Connect to device and start pipeline
16    pipeline.start()
17
18    # ROI selection variables
19    start_points = []
20    roi_rect = None
21    scale_factors = None
22    # Mouse callback function for ROI selection
23    def select_roi(event, x, y, flags, param):
24        global start_points, roi_rect
25        def set_roi_rect():
26            global roi_rect
27            x1, y1 = start_points
28            x2, y2 = (x, y)
29            roi_rect = (min(x1, x2), min(y1, y2), abs(x2-x1), abs(y2-y1))
30
31        if event == cv2.EVENT_LBUTTONDOWN:
32            roi_rect = None
33            start_points = (x, y)
34        elif event == cv2.EVENT_MOUSEMOVE and start_points:
35            set_roi_rect()
36        elif event == cv2.EVENT_LBUTTONUP and start_points:
37            set_roi_rect()
38            roi_rect_scaled = (
39                int(roi_rect[0] * scale_factors[0]),
40                int(roi_rect[1] * scale_factors[1]),
41                int(roi_rect[2] * scale_factors[0]),
42                int(roi_rect[3] * scale_factors[1])
43            )
44            print(f"ROI selected: {roi_rect}")
45            ctrl = dai.CameraControl()
46            print(f"Scaled ROI selected: {roi_rect_scaled}. Setting exposure and focus to this region.")
47            ctrl.setAutoExposureRegion(*roi_rect_scaled)
48            ctrl.setAutoFocusRegion(*roi_rect_scaled)
49            cam_q_in.send(ctrl)
50            start_points = None
51
52    # Create a window and set the mouse callback
53    cv2.namedWindow("video")
54    cv2.setMouseCallback("video", select_roi)
55
56    while pipeline.isRunning():
57        img_hd: dai.ImgFrame = stream_q.get()
58        if scale_factors is None:
59            print(img_hd.getTransformation().getSourceSize(), img_hd.getTransformation().getSize())
60            scale_factors = (img_hd.getTransformation().getSourceSize()[0] / img_hd.getTransformation().getSize()[0],
61                            img_hd.getTransformation().getSourceSize()[1] / img_hd.getTransformation().getSize()[1])
62        frame = img_hd.getCvFrame()
63
64        # Draw the ROI rectangle if it exists
65        if roi_rect is not None:
66            x, y, w, h = roi_rect
67            cv2.rectangle(frame, (x, y), (x+w, y+h), (0, 255, 0), 2)
68
69        cv2.imshow("video", frame)
70
71        key = cv2.waitKey(1)
72        if key == ord("q"):
73            break

Need assistance?

Head over to Discussion Forum for technical support or any other questions you might have.