[Python] How can I capture and process text flashing for 0.2 seconds on the screen?

I'm trying to build a Python script that can detect text that flashes on the screen for a very short period (around 0.2 seconds). I'm using mss for screen capturing and pytesseract for OCR. Below is the code I'm working with:

python
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import cv2
import pytesseract
import numpy as np
from mss import mss
import time
import threading

# Configure pytesseract path
pytesseract.pytesseract_cmd = "/opt/homebrew/bin/tesseract"

# Define the full-screen capture region
sct = mss()
monitor = sct.monitors[1] # Full screen (adjust for multiple monitors)

# Initialize variables
last_detected_text = ""
detected_text_lock = threading.Lock()

# Function to capture the screen and process OCR
def capture_and_process_text():
global last_detected_text
while True:
start_time = time.time()
# Capture the screen
screenshot = np.array(sct.grab(monitor))
# Skip grayscale or thresholding for speed
text = pytesseract.image_to_string(screenshot, lang="eng").strip()
# Normalize the text to reduce noise
normalized_text = " ".join(text.split())

# Only display new and non-empty text
with detected_text_lock:
if normalized_text and normalized_text != last_detected_text:
print(f"Detected Text: {normalized_text}")
last_detected_text = normalized_text

# Dynamically adjust loop timing
end_time = time.time()
print(f"Frame processed in {end_time - start_time:.5f} seconds")

# Run the optimized text capture loop
print("Starting full-screen text capture...")
capture_thread = threading.Thread(target=capture_and_process_text)
capture_thread.start()

try:
while True:
time.sleep(1) # Keep the main thread alive
except KeyboardInterrupt:
print("Text capture stopped.")


This works reasonably well for capturing and processing text on the screen, but I'm facing a few challenges:

Speed: Sometimes it seems like the script isn't fast enough to catch very brief flashes of text, while I'm aiming around 0.2 seconds. OCR Processing Overhead: pytesseract can be slow when dealing with full-screen images, and I’m wondering if there’s a way to make it faster. Capturing All Text: Since I don’t know where on the screen the text will appear, I have to capture the entire screen, which adds overhead. I’m looking for advice on how to optimize this code to make it faster and more reliable. Specifically:

Is there a way to make screen capturing faster while still processing the entire screen? Are there any faster alternatives to pytesseract that work well for real-time OCR? Any general tips for optimizing the capture-then-OCR workflow to handle such short flashes? I’d appreciate any guidance or suggestions on how to approach this problem. Thanks in advance!

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