barely inited text_area_detection

dev_tools/dx_test.py

@@ -0,0 +1,51 @@
+import cv2
+import numpy as np
+
+
+"""Find text rect
+"""
+
+
+class DetectText:
+
+    @classmethod
+    def detect_text_areas(cls, image_path):
+        image = cv2.imread(image_path, cv2.IMREAD_GRAYSCALE)
+        blurred = cv2.GaussianBlur(image, (9, 9), 0)
+        subtracted = cv2.subtract(image, blurred)
+
+        _, binary = cv2.threshold(
+            subtracted, 0, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU
+        )
+
+        kernel = np.ones((9, 9), np.uint8)
+        closed = cv2.morphologyEx(binary, cv2.MORPH_CLOSE, kernel)
+
+        dilated = cv2.dilate(closed, kernel, iterations=1)
+
+        # cv2.RETR_EXTERNAL
+        contours, _ = cv2.findContours(dilated, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
+
+        text_areas = []
+        output_image = cv2.cvtColor(image, cv2.COLOR_GRAY2BGR)
+        for contour in contours:
+            x, y, w, h = cv2.boundingRect(contour)
+            # 过滤掉太小的区域
+            if w > 5 and h > 13:
+                text_areas.append((x, y, w, h))
+                cv2.rectangle(output_image, (x, y), (x + w, y + h), (0, 255, 0), 2)
+
+        # text_areas, weights = cv2.groupRectangles(text_areas, groupThreshold=1, eps=0.5)
+        # for x, y, w, h in text_areas:
+        #     cv2.rectangle(output_image, (x, y), (x + w, y + h), (0, 255, 0), 2)
+
+        cv2.imshow("Detected Text Areas", output_image)
+        cv2.waitKey(0)
+        cv2.destroyAllWindows()
+
+        return text_areas
+
+
+if __name__ == "__main__":
+    image_path = ".\dev_tools\MuMu12-20240709-005243.png"
+    DetectText.detect_text_areas(image_path)