[Python] How to Increase Accuracy of Text Read in Images Using Microsoft Azure Computer Vision...

I'm new to Microsoft Azure AI Computer Vision. I am using Cognitive Services and the Computer Vision Client in a Python Program to do two things:

1. Extract text from a JPG Image using Optical Character Recognition (OCR)
2. Use Cognitive Services to provide a Description of the Image

After lots of configuration issues (and PIP installs!), I have achieved SOME results

The Code for extracting the text from the image is:

#Create A ComputerVision Client
client = ComputerVisionClient(ENDPOINT, CognitiveServicesCredentials(API_KEY))

image_path = '/Users/Owner/Documents/Bills Stuff/eBay/Images/Document_20240914_0008.jpg'

#Use Azure AI Cognitive Services to Get the Title and Description of Image
#For the TITLE, Use Optical Character Recognition (OCR) to Read the Text (Caption) on the Image
with open(image_path, "rb") as image_stream:
ocr_results=client.recognize_printed_text_in_stream(image_stream)

if ocr_results.regions:
for region in ocr_results.regions:
for line in region.lines:
print(f" Title: {' '.join([word.text for word in line.words])}")


My second Point - the Description is working great, BUT the code above is not extracting the Text from the Image accurately at all.

It's CLOSE, but the actual text is: "Scenic View of Horseshoe Curve on Pennsylvania Railroad"

The Code I presented above, returns: "Inside of Horseshoe Curve on Cina Railroad"

Is there a way to improve my code to make this result more accurate?

Adding: If I decrease/increase the size of my image, the code picks upmore or fewer words - maybe I need to somehow give the code more time to process the image??

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