EasyOCR-TextDetection/cameraToText.py at main · mrvbfo/EasyOCR-TextDetection · GitHub

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#EasyOCR ile kameradan alınan afişten yazı okunması
import cv2
import easyocr

def capture_image():
    cap = cv2.VideoCapture(0)

    # Kamera çözünürlüğünü artır
    cap.set(cv2.CAP_PROP_FPS, 50)
    cap.set(cv2.CAP_PROP_AUTOFOCUS, 1)
    cap.set(cv2.CAP_PROP_BRIGHTNESS, 150)
    cap.set(cv2.CAP_PROP_CONTRAST, 50)
    cap.set(cv2.CAP_PROP_SATURATION, 70)
    cap.set(cv2.CAP_PROP_AUTO_EXPOSURE, 0.75)
    cap.set(cv2.CAP_PROP_FOCUS, 50)

    while True:
        ret, frame = cap.read()

        cv2.imshow('Kamera (Space tuşu ile fotoğraf çekin, q ile çıkın)', frame)

        key = cv2.waitKey(1)
        if key == ord(' '):
            cv2.imwrite('captured_image.jpg', frame)
            break
        elif key == ord('q'):
            break

    cap.release()
    cv2.destroyAllWindows()
    return cv2.imread('captured_image.jpg')


def preprocess_image(image):
    gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)

    denoised = cv2.fastNlMeansDenoising(gray)

    clahe = cv2.createCLAHE(clipLimit=3.0, tileGridSize=(8, 8))
    enhanced = clahe.apply(denoised)

    blurred = cv2.GaussianBlur(enhanced, (5, 5), 1.5)
    sharpened = cv2.addWeighted(enhanced, 1.5, blurred, -0.5, 0)

    return sharpened


def detect_and_recognize_text(image, reader):
    # EasyOCR ile metin tanıma
    results = reader.readtext(image)

    text_boxes = []
    texts = []

    for (bbox, text, confidence) in results:
        if confidence > 0.4:
            (top_left, top_right, bottom_right, bottom_left) = bbox
            x_min, y_min = map(int, top_left)
            x_max, y_max = map(int, bottom_right)

            text_boxes.append((x_min, y_min, x_max - x_min, y_max - y_min))
            texts.append(text)

    return text_boxes, texts


def main():
    # EasyOCR okuyucu (Türkçe ve İngilizce destekli)
    reader = easyocr.Reader(['tr', 'en'])

    # Kameradan görüntü al
    image = capture_image()
    if image is None:
        print("Görüntü alınamadı!")
        return

    processed_image = preprocess_image(image)

    text_boxes, texts = detect_and_recognize_text(processed_image, reader)

    output = image.copy()
    for i, (box, text) in enumerate(zip(text_boxes, texts)):
        x, y, w, h = box

        cv2.rectangle(output, (x, y), (x + w, y + h), (0, 225, 0), 2)

        print(f"Tespit edilen metin {i + 1}: {text}")

        display_text = text[:20] + '...' if len(text) > 20 else text
        cv2.putText(output, display_text, (x, y - 5),
                    cv2.FONT_HERSHEY_SIMPLEX, 0.5, (255, 0, 0), 2)

    cv2.imshow('Tespit Edilen Metinler', output)
    cv2.waitKey(0)
    cv2.destroyAllWindows()


if __name__ == "__main__":
    main()