.venv deleted

ocr ready to test

ocr-service/imgproc.py

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+import cv2
+import numpy as np
+import logging
+
+logger = logging.getLogger(__name__)
+
+def order_points(pts):
+    rect = np.zeros((4, 2), dtype="float32")
+    s = pts.sum(axis=1)
+    rect[0] = pts[np.argmin(s)]
+    rect[2] = pts[np.argmax(s)]
+    diff = np.diff(pts, axis=1)
+    rect[1] = pts[np.argmin(diff)]
+    rect[3] = pts[np.argmax(diff)]
+    return rect
+
+def four_point_transform(image, pts):
+    rect = order_points(pts)
+    (tl, tr, br, bl) = rect
+
+    widthA = np.sqrt(((br[0] - bl[0]) ** 2) + ((br[1] - bl[1]) ** 2))
+    widthB = np.sqrt(((tr[0] - tl[0]) ** 2) + ((tr[1] - tl[1]) ** 2))
+    maxWidth = max(int(widthA), int(widthB))
+
+    heightA = np.sqrt(((tr[0] - br[0]) ** 2) + ((tr[1] - br[1]) ** 2))
+    heightB = np.sqrt(((tl[0] - bl[0]) ** 2) + ((tl[1] - bl[1]) ** 2))
+    maxHeight = max(int(heightA), int(heightB))
+
+    dst = np.array([
+        [0, 0],
+        [maxWidth - 1, 0],
+        [maxWidth - 1, maxHeight - 1],
+        [0, maxHeight - 1]], dtype="float32")
+
+    M = cv2.getPerspectiveTransform(rect, dst)
+    warped = cv2.warpPerspective(image, M, (maxWidth, maxHeight))
+    return warped
+
+def preprocess_image(image_bytes: bytes) -> np.ndarray:
+    """
+    Возвращает БИНАРНОЕ (Ч/Б) изображение для Tesseract.
+    """
+    nparr = np.frombuffer(image_bytes, np.uint8)
+    image = cv2.imdecode(nparr, cv2.IMREAD_COLOR)
+    
+    if image is None:
+        raise ValueError("Could not decode image")
+
+    # Ресайз для поиска контуров
+    ratio = image.shape[0] / 500.0
+    orig = image.copy()
+    image_small = cv2.resize(image, (int(image.shape[1] / ratio), 500))
+
+    gray = cv2.cvtColor(image_small, cv2.COLOR_BGR2GRAY)
+    gray = cv2.GaussianBlur(gray, (5, 5), 0)
+    edged = cv2.Canny(gray, 75, 200)
+
+    cnts, _ = cv2.findContours(edged.copy(), cv2.RETR_LIST, cv2.CHAIN_APPROX_SIMPLE)
+    cnts = sorted(cnts, key=cv2.contourArea, reverse=True)[:5]
+
+    screenCnt = None
+    found = False
+
+    for c in cnts:
+        peri = cv2.arcLength(c, True)
+        approx = cv2.approxPolyDP(c, 0.02 * peri, True)
+        if len(approx) == 4:
+            screenCnt = approx
+            found = True
+            break
+
+    # Изображение, с которым будем работать дальше
+    target_img = None
+
+    if found:
+        logger.info("Receipt contour found (Tesseract mode).")
+        target_img = four_point_transform(orig, screenCnt.reshape(4, 2) * ratio)
+    else:
+        logger.warning("Receipt contour NOT found. Using full image.")
+        target_img = orig
+
+    # --- Подготовка для Tesseract (Бинаризация) ---
+    # Переводим в Gray
+    gray_final = cv2.cvtColor(target_img, cv2.COLOR_BGR2GRAY)
+    
+    # Адаптивный порог (превращаем в чисто черное и белое)
+    # block_size=11, C=2 - классические параметры для текста
+    thresh = cv2.adaptiveThreshold(
+        gray_final, 255, 
+        cv2.ADAPTIVE_THRESH_GAUSSIAN_C, 
+        cv2.THRESH_BINARY, 11, 2
+    )
+    
+    # Немного убираем шум
+    # thresh = cv2.medianBlur(thresh, 3) 
+    
+    return thresh