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I created a solution...with a pi 4 but it just doesn't seem to work very well. OCR is very finicky and while I was able to get pytesseract to pull the images off of a webcam, the numbers that get returned are very wrong. It looks like they only allow businesses to pull the powermeter data if I am reading this right: https://www.pge.com/en/save-energy-and-money/energy-saving-programs/smartmeter.html

My rate has increased 6 times this year, so power is very expensive here: 50c per KWH...on the lowest consumption rate. I need to figure out how to cut back or get solar panels. But I want to see in near real time how much energy we are using.

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[-] mesamunefire@lemmy.world 2 points 1 week ago
import cv2
import easyocr
import numpy as np
from PIL import Image
from collections import Counter

# Initialize the EasyOCR reader
reader = easyocr.Reader(['en'])

def preprocess_image(image):
    # Convert to PIL image for EasyOCR processing
    return Image.fromarray(cv2.cvtColor(image, cv2.COLOR_BGR2RGB))

def recognize_text(image):
    processed_image = preprocess_image(image)
    results = reader.readtext(np.array(processed_image), allowlist='0123456789')
    # Concatenate all recognized text results
    recognized_text = ''.join(result[1] for result in results)
    return recognized_text

def format_number(text, length=6):
    # Remove non-numeric characters and pad with zeros if necessary
    formatted = ''.join(filter(str.isdigit, text))
    return formatted.zfill(length)[-length:]

def most_common_number(numbers):
    # Find the most common number from the list of numbers
    counter = Counter(numbers)
    most_common = counter.most_common(1)
    return most_common[0][0] if most_common else ''

def main():
    cap = cv2.VideoCapture(2)

    if not cap.isOpened():
        print("Error: Could not open webcam.")
        return

    print("Press 'q' to quit.")
    frame_count = 0
    text_history = []

    while True:
        ret, frame = cap.read()
        if not ret:
            print("Error: Failed to capture image.")
            break

        # Recognize text from the current frame
        recognized_text = recognize_text(frame)
        formatted_number = format_number(recognized_text)

        # Update the history with the latest recognized number
        text_history.append(formatted_number)

        # Keep only the last 10 frames
        if len(text_history) > 20:
            text_history.pop(0)

        # Determine the most common number from the history
        most_common = most_common_number(text_history)
        print(f"Most common number from last 10 frames: {most_common}")

        # if cv2.waitKey(1) & 0xFF == ord('q'):
        #     break

    cap.release()

if __name__ == "__main__":
    main()

[-] mesamunefire@lemmy.world 1 points 1 week ago

the easyocr version somewhat works...but still having issues when its actually outside. Thought I would ask if anyone has figured out this issue before. Ill keep hacking away at it, but thought I would ask if the API is viable.

this post was submitted on 22 Dec 2024
17 points (100.0% liked)

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