From b7f6cc3e7483acfdf7a2dbab90d56c5c02b0c148 Mon Sep 17 00:00:00 2001
From: itqop <leonkl32@gmail.com>
Date: Thu, 28 Nov 2024 20:44:26 +0300
Subject: [PATCH] 1

---
 car-yolo-test.py | 31 ++++++++++++++++++++++++
 kalentev.py      | 63 ++++++++++++++++++++++++++++++++++++++++++++++++
 2 files changed, 94 insertions(+)
 create mode 100644 car-yolo-test.py
 create mode 100644 kalentev.py

diff --git a/car-yolo-test.py b/car-yolo-test.py
new file mode 100644
index 0000000..ea011c6
--- /dev/null
+++ b/car-yolo-test.py
@@ -0,0 +1,31 @@
+import easyocr
+import cv2
+
+def ocr_image(img_path):
+    """
+    Выполняет OCR для изображения с номером.
+    
+    :param img_path: Путь к изображению.
+    :return: Распознанный текст.
+    """
+    reader = easyocr.Reader(['en'], gpu=True)  # Инициализация easyOCR
+    img = cv2.imread(img_path)  # Загрузка изображения
+    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)  # Конвертация в оттенки серого
+    
+    # Запуск OCR
+    results = reader.readtext(gray)
+    print(results)
+    text = ""
+    for res in results:
+        if len(results) == 1:
+            text = res[1]
+        if len(results) > 1 and len(res[1]) > 6 and res[2] > 0.2:  # Фильтрация текста
+            text = res[1]
+    
+    return text
+
+# Использование
+if __name__ == "__main__":
+    img_path = "result.png"  # Путь к изображению с номером
+    recognized_text = ocr_image(img_path)
+    print(f"Распознанный текст: {recognized_text}")
diff --git a/kalentev.py b/kalentev.py
new file mode 100644
index 0000000..7cde18d
--- /dev/null
+++ b/kalentev.py
@@ -0,0 +1,63 @@
+import numpy as np
+import cv2
+from matplotlib import pyplot as plt
+
+images = ['img/1.jpg', 'img/2.jpg', 'img/3.jpg', 'img/26417135.jpg', 'img/ru4018185.jpg']
+
+processed_plates = []
+
+for img_path in images:
+    image = cv2.imread(img_path)
+
+    img_gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
+    ret, thresh = cv2.threshold(img_gray, 100, 200, cv2.THRESH_TOZERO_INV)
+    contours, hierarchy = cv2.findContours(thresh, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
+
+    for i in range(len(contours)):
+        x, y, w, h = cv2.boundingRect(contours[i])
+        a = w * h
+        aspectRatio = float(w) / h
+        if aspectRatio >= 3 and a > 600:
+            approx = cv2.approxPolyDP(contours[i], 0.05 * cv2.arcLength(contours[i], True), True)
+            if len(approx) <= 4 and x > 15:
+                width = w
+                height = h
+                start_x = x
+                start_y = y
+                end_x = start_x + width
+                end_y = start_y + height
+                break
+
+    plate = image[start_y:end_y, start_x:end_x]
+
+    gray = cv2.cvtColor(plate, cv2.COLOR_BGR2GRAY)
+    _, thresh = cv2.threshold(gray, 150, 255, cv2.THRESH_BINARY)
+    contours, _ = cv2.findContours(thresh, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
+
+    largest_contour = max(contours, key=cv2.contourArea)
+    rect = cv2.minAreaRect(largest_contour)
+    box = cv2.boxPoints(rect)
+    box = np.intp(box)
+    angle = rect[-1]
+
+    if angle < -45:
+        angle += 90
+    if angle < 90:
+        (h, w) = plate.shape[:2]
+        center = (w // 2, h // 2)
+        M = cv2.getRotationMatrix2D(center, angle, 1.0)
+        rotated = cv2.warpAffine(plate, M, (w, h))
+    else:
+        angle = 0.5
+        (h, w) = plate.shape[:2]
+        center = (w // 2, h // 2)
+        M = cv2.getRotationMatrix2D(center, angle, 1.0)
+        rotated = cv2.warpAffine(plate, M, (w, h))
+
+    processed_plates.append(rotated)
+
+for i, rotated_plate in enumerate(processed_plates):
+    cv2.imshow(f'Номер {i+1}', rotated_plate)
+
+cv2.waitKey(0)
+cv2.destroyAllWindows()