Merge pull request #360 from DongXu-Zhang/master

feat: add a function which extract txt information from image.

tests/test_agentuniverse/unit/agent/action/tool/test_arxiv_tool.py

@@ -45,4 +45,4 @@ class ArxivToolTest(unittest.TestCase):
 
 
 if __name__ == '__main__':
-    unittest.main()
+    unittest.main()

tests/test_agentuniverse/unit/agent/action/tool/test_readimage_tool.py

@@ -0,0 +1,66 @@
+# !/usr/bin/env python3
+# -*- coding:utf-8 -*-
+
+# @Time    : 2025/03/27 21:38
+# @Author  : zhangdongxu
+# @Email   : zhangdongxu0852@163.com
+# @FileName: test_readimage_tool.py
+import os
+import cv2
+import numpy as np
+import unittest
+from readimage_tool import (enhance_image, detect_text_regions, ocr_on_regions,
+                            clean_extracted_text, save_text_to_file, extract_text_from_image)
+
+class TestReadImageTool(unittest.TestCase):
+    def setUp(self):
+        # Create a simple color test image (100x100 pixels, random content)
+        self.test_image = np.random.randint(0, 256, (100, 100, 3), dtype=np.uint8)
+        # Create an image with black text on a white background for OCR testing
+        self.test_ocr_image = np.full((100, 300, 3), 255, dtype=np.uint8)
+        cv2.putText(self.test_ocr_image, 'Test', (5, 50), cv2.FONT_HERSHEY_SIMPLEX, 1, (0,0,0), 2)
+
+    def test_enhance_image(self):
+        enhanced = enhance_image(self.test_image)
+        # The enhanced image is a grayscale image, and the shape should be two-dimensional
+        self.assertEqual(len(enhanced.shape), 2)
+
+    def test_clean_extracted_text(self):
+        dirty_text = "This   is   a   test.\nNew    line."
+        clean_text = clean_extracted_text(dirty_text)
+        self.assertNotIn("\n", clean_text)
+        self.assertNotIn("  ", clean_text)
+        self.assertEqual(clean_text, "This is a test. New line.")
+
+    def test_save_text_to_file(self):
+        test_text = "Sample text for testing."
+        test_filename = "test_extracted_text.txt"
+        save_text_to_file(test_text, test_filename)
+        self.assertTrue(os.path.exists(test_filename))
+        with open(test_filename, 'r', encoding='utf-8') as f:
+            content = f.read()
+        self.assertEqual(content, test_text)
+        os.remove(test_filename)
+
+    def test_extract_text_from_image_without_east(self):
+        # Save the test OCR image as a temporary file
+        temp_image = "temp_test_ocr.png"
+        cv2.imwrite(temp_image, self.test_ocr_image)
+        try:
+            # Use simple OCR, no EAST detection
+            text = extract_text_from_image(temp_image, use_east=False, lang='eng')
+            self.assertIsInstance(text, str)
+            self.assertGreater(len(text), 0)
+        finally:
+            if os.path.exists(temp_image):
+                os.remove(temp_image)
+
+    def test_detect_text_regions_no_text(self):
+        # Text areas are usually not detected using random images
+        regions = detect_text_regions(self.test_image)
+        # The test result may be an empty list
+        self.assertIsInstance(regions, list)
+
+if __name__ == '__main__':
+    unittest.main()
+