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import gradio as gr |
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import pytesseract |
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from PIL import Image |
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import fitz |
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import io |
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import cv2 |
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import numpy as np |
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import os |
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pytesseract.pytesseract.tesseract_cmd = "tesseract" |
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def preprocess_image_for_ocr(image): |
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gray = cv2.cvtColor(np.array(image), cv2.COLOR_RGB2GRAY) |
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clahe = cv2.createCLAHE(clipLimit=2.0, tileGridSize=(8, 8)) |
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gray = clahe.apply(gray) |
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blurred = cv2.bilateralFilter(gray, 9, 75, 75) |
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sharp = cv2.addWeighted(blurred, 1.5, cv2.GaussianBlur(blurred, (0, 0), 5), -0.5, 0) |
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denoised = cv2.fastNlMeansDenoising(sharp, h=20) |
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adaptive = cv2.adaptiveThreshold(denoised, 255, cv2.ADAPTIVE_THRESH_GAUSSIAN_C, |
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cv2.THRESH_BINARY, 35, 11) |
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_, otsu = cv2.threshold(denoised, 0, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU) |
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binary = cv2.bitwise_and(adaptive, otsu) |
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opened = cv2.morphologyEx(binary, cv2.MORPH_OPEN, np.ones((1, 1), np.uint8)) |
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h, w = opened.shape |
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opened = cv2.resize(opened, (w * 2, h * 2), interpolation=cv2.INTER_CUBIC) |
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return Image.fromarray(opened) |
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def ocr_from_file(file): |
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ext = os.path.splitext(file.name)[1].lower() |
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result_text = "" |
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try: |
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if ext in ['.png', '.jpg', '.jpeg', '.bmp', '.tiff']: |
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image = Image.open(file) |
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processed = preprocess_image_for_ocr(image) |
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result_text = pytesseract.image_to_string(processed, lang="jpn+eng") |
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elif ext == '.pdf': |
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doc = fitz.open(file.name) |
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for page_num in range(min(len(doc), 3)): |
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page = doc.load_page(page_num) |
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pix = page.get_pixmap(matrix=fitz.Matrix(4, 4)) |
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img = Image.open(io.BytesIO(pix.tobytes())) |
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processed = preprocess_image_for_ocr(img) |
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result_text += pytesseract.image_to_string(processed, lang="jpn+eng") + "\n" |
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else: |
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return "非対応形式です。" |
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except Exception as e: |
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return f"OCRエラー: {e}" |
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return result_text.strip() |
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gr.Interface( |
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fn=ocr_from_file, |
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inputs=gr.File(label="画像またはPDFをアップロード"), |
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outputs=gr.Textbox(label="OCR結果"), |
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title="🚀 高精度OCR Lite", |
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description="日本語・英語対応の高精度OCRツール（Lite体験版）" |
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).launch() |
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