HI,
Sure, can we connect tomorrow around 11:30 am IST at Google meet. My Id is
"tareshchaudh...@gmail.com".
On Wednesday, 11 December 2024 at 18:53:17 UTC+5:30 mahmoud...@gmail.com
wrote:
> Hello I want make or generated with you a simple file trainddata by
> jtessboxeditor for Tesseract and test it can you inform me time to discuss
> The steps. Thanks
>
> في الثلاثاء، ٢٦ نوفمبر ٢٠٢٤، ٥:٠١ م Taresh Chaudhari <tareshc...@gmail.com>
> كتب:
>
>> Thanks Mahmoud for sharing. I did apply these techniques, but still
>> results are not good and still trying to solve this problem. Let me see how
>> does it proceed.
>>
>> On Tuesday, 26 November 2024 at 00:31:29 UTC+5:30 mahmoud...@gmail.com
>> wrote:
>>
>>> To improve the accuracy of text extraction, you can preprocess the image
>>> before passing it to the OCR engine. Preprocessing techniques like
>>> converting the image to grayscale, enhancing contrast, or applying filters
>>> can help reduce noise and improve readability. Additionally, tweaking the
>>> pytesseract settings like changing the --psm value may also improve the
>>> results.
>>>
>>> Here’s an updated version of your code with some preprocessing steps:
>>> import pytesseract
>>> from PIL import Image, ImageEnhance, ImageFilter
>>>
>>> pytesseract.pytesseract.tesseract_cmd =
>>> 'C:\\Users\\M562765\\AppData\\Local\\Programs\\Tesseract-OCR\\tesseract.exe'
>>>
>>> # Path to your image
>>> image_path = 'C:/Users/M562765/Downloads/Unable-images/Unable/crop1.jpg'
>>>
>>> def extract_text_from_image(image_path):
>>> # Open the image
>>> img = Image.open(image_path)
>>>
>>> # Convert the image to grayscale to improve text-background contrast
>>> img = img.convert('L') # Convert image to grayscale
>>> img = ImageEnhance.Contrast(img).enhance(2) # Increase contrast
>>> img = img.filter(ImageFilter.SHARPEN) # Sharpen the image
>>>
>>> # Use pytesseract to extract text
>>>
>>>
>>> extracted_text = pytesseract.image_to_string(img, config='--psm 6')
>>> # PSM 6 assumes a block of text
>>> return extracted_text.strip()
>>>
>>> # Extract and print text
>>> text = extract_text_from_image(image_path)
>>> print(f"Text extracted from {image_path}: {text}")
>>>
>>> في الاثنين، ٢٥ نوفمبر ٢٠٢٤، ٤:١٢ م Taresh Chaudhari <
>>> tareshc...@gmail.com> كتب:
>>>
>>>> Attaching a image for reference.
>>>>
>>>> On Monday, 25 November 2024 at 15:52:27 UTC+5:30 Taresh Chaudhari wrote:
>>>>
>>>>> Hi,
>>>>> I am trying to read the characters from the image, which has
>>>>> characters with black color in the background. Attaching the code which i
>>>>> used to extract, currently its giving the partial output. Can you help me
>>>>> to guide how to make it accurate?
>>>>>
>>>>>
>>>>> import pytesseract
>>>>> from PIL import Image
>>>>> pytesseract.pytesseract.tesseract_cmd =
>>>>> 'C:\\Users\\M562765\\AppData\\Local\\Programs\\Tesseract-OCR\\tesseract.exe'
>>>>> # Paths to your images
>>>>> image_paths = [
>>>>> 'C:/Users/M562765/Downloads/Unable-images/Unable/crop1.jpg']
>>>>>
>>>>> # Function to process an image and extract text
>>>>> def extract_text_from_image(image_path):
>>>>> # Open the image
>>>>> img = Image.open(image_path)
>>>>>
>>>>> # Use pytesseract to perform OCR
>>>>> extracted_text = pytesseract.image_to_string(img, config='--psm
>>>>> 6') # PSM 6 assumes a block of text
>>>>> return extracted_text.strip()
>>>>>
>>>>> # Process all images and print results
>>>>> for img_path in image_paths:
>>>>> text = extract_text_from_image(img_path)
>>>>> print(f"Text extracted from {img_path}: {text}")
>>>>>
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>>
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>>
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