Update alpr_module.py

alpr_module.py

@@ -1,72 +1,74 @@
-import cv2
-import numpy as np
-import easyocr
-from inference_sdk import InferenceHTTPClient
-
-# تعريف العميل
-CLIENT = InferenceHTTPClient(
-    api_url="https://serverless.roboflow.com",
-    api_key="4m9tZRxBfEK8C4no7zsZ"
-)
-reader = easyocr.Reader(['en'])
-def detect_license_plate(image_path, model_id="license-plate-recognition-rxg4e/11"):
-    """إجراء التنبؤ باستخدام نموذج Roboflow"""
-    result = CLIENT.infer(image_path, model_id=model_id)
-    return result
-
-def extract_plate_from_image(image_path, predictions):
-    """استخلاص صورة اللوحة من الصورة الكاملة بناءً على التنبؤات"""
-    image = cv2.imread(image_path)
-    max_confidence = 0
-    best_coords = None
-
-    for prediction in predictions['predictions']:
-        confidence = prediction['confidence']
-        if confidence > max_confidence:
-            max_confidence = confidence
-            x = int(prediction['x'])
-            y = int(prediction['y'])
-            width = int(prediction['width'])
-            height = int(prediction['height'])
-            x1 = int(x - width / 2)
-            y1 = int(y - height / 2)
-            x2 = int(x + width / 2)
-            y2 = int(y + height / 2)
-            best_coords = (x1, y1, x2, y2)
-
-    if not best_coords:
-        return None  # لم يتم الكشف عن أي لوحة
-
-    x1, y1, x2, y2 = best_coords
-    polygon_points = np.array([
-        [x1, y1],
-        [x2, y1],
-        [x2, y2],
-        [x1, y2]
-    ], dtype=np.int32)
-
-    mask = np.zeros(image.shape[:2], dtype=np.uint8)
-    cv2.fillPoly(mask, [polygon_points], 255)
-
-    masked_image = cv2.bitwise_and(image, image, mask=mask)
-    x, y, w, h = cv2.boundingRect(polygon_points)
-    cropped_plate = masked_image[y:y+h, x:x+w]
-
-    return cropped_plate
-
-def enhance_image_for_ocr(image):
-    """تحسين الصورة لاستخلاص النصوص باستخدام EasyOCR"""
-    gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
-    return gray
-
-def extract_license_number(image):
-    """استخراج الأرقام من صورة اللوحة"""
-    result = reader.readtext(image)
-    plate_numbers = []
-
-    for detection in result:
-        text = detection[1]
-        numbers_only = ''.join(c for c in text if c.isdigit())
-        if numbers_only:
-            plate_numbers.append(numbers_only)
-    return plate_numbers
+import cv2
+import numpy as np
+import os
+os.makedirs('/app/.easyocr', exist_ok=True)
+
+from inference_sdk import InferenceHTTPClient
+
+# تعريف العميل
+CLIENT = InferenceHTTPClient(
+    api_url="https://serverless.roboflow.com",
+    api_key="4m9tZRxBfEK8C4no7zsZ"
+)
+reader = easyocr.Reader(['en'], model_storage_directory='/app/.easyocr')
+def detect_license_plate(image_path, model_id="license-plate-recognition-rxg4e/11"):
+    """إجراء التنبؤ باستخدام نموذج Roboflow"""
+    result = CLIENT.infer(image_path, model_id=model_id)
+    return result
+
+def extract_plate_from_image(image_path, predictions):
+    """استخلاص صورة اللوحة من الصورة الكاملة بناءً على التنبؤات"""
+    image = cv2.imread(image_path)
+    max_confidence = 0
+    best_coords = None
+
+    for prediction in predictions['predictions']:
+        confidence = prediction['confidence']
+        if confidence > max_confidence:
+            max_confidence = confidence
+            x = int(prediction['x'])
+            y = int(prediction['y'])
+            width = int(prediction['width'])
+            height = int(prediction['height'])
+            x1 = int(x - width / 2)
+            y1 = int(y - height / 2)
+            x2 = int(x + width / 2)
+            y2 = int(y + height / 2)
+            best_coords = (x1, y1, x2, y2)
+
+    if not best_coords:
+        return None  # لم يتم الكشف عن أي لوحة
+
+    x1, y1, x2, y2 = best_coords
+    polygon_points = np.array([
+        [x1, y1],
+        [x2, y1],
+        [x2, y2],
+        [x1, y2]
+    ], dtype=np.int32)
+
+    mask = np.zeros(image.shape[:2], dtype=np.uint8)
+    cv2.fillPoly(mask, [polygon_points], 255)
+
+    masked_image = cv2.bitwise_and(image, image, mask=mask)
+    x, y, w, h = cv2.boundingRect(polygon_points)
+    cropped_plate = masked_image[y:y+h, x:x+w]
+
+    return cropped_plate
+
+def enhance_image_for_ocr(image):
+    """تحسين الصورة لاستخلاص النصوص باستخدام EasyOCR"""
+    gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
+    return gray
+
+def extract_license_number(image):
+    """استخراج الأرقام من صورة اللوحة"""
+    result = reader.readtext(image)
+    plate_numbers = []
+
+    for detection in result:
+        text = detection[1]
+        numbers_only = ''.join(c for c in text if c.isdigit())
+        if numbers_only:
+            plate_numbers.append(numbers_only)
+    return plate_numbers