liveBook · Manning

putText

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

OpenCV putText renders text onto an image at a specified position using selected font and styling parameters.

putText renders text onto an OpenCV image at a chosen position, using a selected font, scale, and color. It adds labels to drawn images and camera frames. section 8.3.2 section 8.3.3

Render text on a drawn image

Create a 640×480 image, then draw the lowercase alphabet in red with FONT_HERSHEY_SIMPLEX at position (10, 380): cv2.putText(img, text, org=pos, fontFace=font, fontScale=1, color=RED). Display the result with imshow and wait for a key press. section 8.3.2

Display a temporary camera message

A snapshot application stores a message and overlays it on the live frame for ten frames: cv2.putText(frame, messages.pop(), TEXT_POS, FONT, 1, BLUE). This displays “saving photo...” after the spacebar triggers a snapshot. section 8.3.3

text = string.ascii_lowercase
font = cv2.FONT_HERSHEY_SIMPLEX
pos = (10, 380)
cv2.putText(img, text, org=pos, fontFace=font, fontScale=1, color=RED)

Inspect the complete text-rendering call with its alphabet, font, position, scale, and color values. section 8.3.2

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

Inspect the reusable show_image function that overlays queued messages before displaying camera frames. section 8.3.3

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

How deep it goes
Explains the basic call and reusable overlay pattern, but does not descend into font rendering internals.
Examples
Uses lowercase alphabet labeling and a temporary “saving photo...” message over live camera frames.
What it assumes
Assumes an OpenCV image or camera frame and introduces font, position, scale, and color arguments through runnable calls.
What you can do after
Apply it via OpenCV to label generated images and show time-limited feedback during camera-driven interactions.
How it connects
Connects OpenCV text rendering with image arrays, camera capture, keyboard input, previews, and snapshots.

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.