liveBook · Manning

Imshow

As explained in Build Your Own Robot: Using Python, CRICKIT, and Raspberry Pi

OpenCV imshow displays an image in a named graphical window.

`cv2.imshow` displays an image in a named window. It provides the visible preview for camera-driven programs, so each captured or processed frame can be checked as the program runs. section 8.3.3

Call `imshow` after drawing any feedback onto the image. In a snapshot preview, temporary status text is added with `putText` before the frame is shown; the resulting window updates at the capture rate to form a live feed. section 8.3.3

Show a camera frame with a save message

Keep display code in a reusable function. When a message is queued, draw it on the current frame, then show that same frame in the `preview` window. ```python def show_image(frame, messages): if messages: cv2.putText(frame, messages.pop(), TEXT_POS, FONT, 1, BLUE) cv2.imshow('preview', frame) ``` section 8.3.3

A displayed image can also communicate vision results. After face detection draws a rectangle and center marker, `imshow` presents the marked photo. In a QR-code stream, it presents each newly received image after detected codes have been outlined and labeled. section 9.3.2 section 10.4.4

def show_image(frame, messages):
    if messages:
        cv2.putText(frame, messages.pop(), TEXT_POS, FONT, 1, BLUE)
    cv2.imshow('preview', frame)

Inspect the small display helper that overlays queued status text before opening the preview window. section 8.3.3

How Build Your Own Robot: Using Python, CRICKIT, and Raspberry Pi covers it

How deep it goes
Demonstrates direct calls inside reusable display loops but does not explain window internals.
Examples
Uses a 30-frame-per-second snapshot preview, a marked face photo, and a QR-code video stream.
What it assumes
Uses Python OpenCV code with camera frames or loaded images; no display-theory background is established.
What you can do after
Apply it via OpenCV to preview captured or processed images while testing interactive camera programs.
How it connects
Connects camera capture, waitKey, putText, face detection, and QR code detection through visible frame output.

Related concepts

This explainer was generated by Manning's knowledge graph from the text of Build Your Own Robot: Using Python, CRICKIT, and Raspberry Pi. The section links point to the parts of the book it draws on.