It is the sample script for searching sample from certain image generated by ChatGPT.
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import cv2
import pytesseract
def search_and_count_sample(image_path, search_text):
# Load the image using OpenCV
image = cv2.imread(image_path)
# Convert the image to grayscale
gray_image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
# Apply image preprocessing (you can adjust these parameters based on your image quality)
preprocessed_image = cv2.GaussianBlur(gray_image, (5, 5), 0)
# Perform OCR using Tesseract
extracted_text = pytesseract.image_to_string(preprocessed_image)
# Count the occurrences of the search text
sample_count = extracted_text.lower().count(search_text.lower())
return sample_count
if __name__ == “__main__”:
image_path = “path/to/your/image.jpg” # Replace with the actual image path
search_text = “sample” # Replace with the text you want to search for
Yi at Jeju Island (NIMS, Korea) 
It is the sample script for searching sample from certain image generated by ChatGPT.
———————————
import cv2
import pytesseract
def search_and_count_sample(image_path, search_text):
# Load the image using OpenCV
image = cv2.imread(image_path)
# Convert the image to grayscale
gray_image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
# Apply image preprocessing (you can adjust these parameters based on your image quality)
preprocessed_image = cv2.GaussianBlur(gray_image, (5, 5), 0)
# Perform OCR using Tesseract
extracted_text = pytesseract.image_to_string(preprocessed_image)
# Count the occurrences of the search text
sample_count = extracted_text.lower().count(search_text.lower())
return sample_count
if __name__ == “__main__”:
image_path = “path/to/your/image.jpg” # Replace with the actual image path
search_text = “sample” # Replace with the text you want to search for
sample_count = search_and_count_sample(image_path, search_text)
print(f”Number of occurrences of ‘{search_text}’ in the image: {sample_count}”)