Create note_highlighter_test.py

Author: heyronjmilton

Backend/note_highlighter_test.py

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+import easyocr
+import cv2
+
+# Load the image
+img = cv2.imread('img2.jpg')
+
+# Initialize the EasyOCR reader with English language
+reader = easyocr.Reader(['en'])
+
+# Perform OCR on the image and get the detail information including bounding boxes
+results = reader.readtext(img, detail=1)
+
+# Print all the detected words
+print("Detected Words:")
+for result in results:
+    text = result[1]
+    confidence = result[2]
+    print(f"Word: {text}, Confidence: {confidence}")
+
+# Create an overlay image as a copy of the original image
+overlay = img.copy()
+
+# Get the inputted string to search and highlight
+input_string = input("Enter the string to highlight: ")
+
+# Split the inputted string into individual words
+input_words = input_string.lower().split()
+
+# Iterate over the OCR results
+for result in results:
+    # Get the current detected word
+    detected_word = result[1].lower()
+
+    # Check if the current detected word matches any word in the inputted string
+    if any(word in detected_word for word in input_words):
+        # Get the bounding box coordinates
+        bbox = result[0]
+        x, y, w, h = bbox[0][0], bbox[0][1], bbox[2][0] - bbox[0][0], bbox[2][1] - bbox[0][1]
+
+        # Draw a filled rectangle around the detected word with the correct size and color
+        cv2.rectangle(overlay, (x, y), (x + w, y + h), (0, 0, 255), -1)
+
+# Blend the overlay image with the original image
+alpha = 0.4
+img_new = cv2.addWeighted(overlay, alpha, img, 1 - alpha, 0)
+
+# Calculate the aspect ratio for resizing
+aspect_ratio = img.shape[1] / img.shape[0]
+
+# Set the width for resizing and calculate the corresponding height
+width = 1000
+height = int(width / aspect_ratio)
+
+# Resize the resulting image
+resized = cv2.resize(img_new, (width, height), interpolation=cv2.INTER_AREA)
+
+# Display the resized image
+cv2.imshow('img', resized)
+cv2.waitKey(0)
+cv2.destroyAllWindows()