Відео

Hi, I haven't done this before, but you should be able to use a notebook on Google Colab instead of Jupyter notebook on a local pc. Try this: Create a service account in Google Cloud Vision API. Download the service account key file as a JSON file. download the json file, then upload the file to the colab environment Reference: cloud.google.com/vision/product-search/docs/auth

Hi, I haven't used Vision API for barcode reading. Even though it is a general model, it should do okay. For the highest accuracy, it is usually better to either retrain a general model or find a focused model that is already trained for your specific use. You will get better results on a model that is specific and not general. For automation, you would need to build an app that can take an image of the barcode, send it to the API, then post the results into the excel file.

There used to be a free trial where they give you some credit. Once that credit was used up, you would need to pay to use. I don't see that option on their website any longer. Currently they have a prepayment method, in $5 increments.

If you are using vscode as your editor, you can follow this video for general instructions on how to get these working together: ua-cam.com/video/lGRwEcCHNtA/v-deo.html google-cloud-vision is the main package for connecting python to google cloud

You can, and Google Vision should work okay as a barcode reader. However, there are other tools that might be more useful and accurate as they were built specifically for this purpose. ML Kit and Android Google Mobile Vision Library are a few. I haven't used either of these.

Thanks for pointing this out - AWS made some changes to IPv4 costs in February of this year (2024).

Hi, textractor is a specialized package used only for connecting to the AWS Textract service, whereas boto3 is a general purpose library, it can be used for many different AWS API services. If you were just working with AWS Textract, the Textractor package would be easier to use.

creating a text document from a scanned book would be possible, but the accuracy may not be 100%. You would need to edit and correct the mistakes in the output after the OCR is finished. Creating the images would be more difficult.

@@TechExpertTutorials that's fine, but I'm looking a way to do it in one step, ocr and image recognition to a doc file, then, rearrange and correct it.

Hi, Google does not have an API designed for fingerprint recognition. You can check out the WebAuthn API, although I have never used it.

Thanks! To handle multiple images effectively, you could use the Azure OpenAI GPT4 service and include the BYOD "add your data" option, which can include extracting text from files/images. Then you can ask any questions about any of the files/images. The process would look through the data on all of the files and find the most relevant information. FYI, I plan to have a video out soon that will cover how to set this up.

yes, you can, i did it this way: content = [{"type": "text", "text": prompt}] for filename in os.listdir(images_folder_path): if filename.lower().endswith(('.png', '.jpg', '.jpeg', '.gif', '.bmp')): filepath = os.path.join(images_folder_path, filename) content.append({"type": "image_url", "image_url": {"url": f"data:image/png;base64,{encode_image(filepath)}"}}) response = client.chat.completions.create( model='gpt-4o', messages=[{"role": "user", "content": content}], max_tokens=500, )

i don't know if that's what you really need but i hope it works for you

You should be able to take the extracted text from Gemini AI and add that information to a web or text-based form. I don't know if there are any 3rd party tools that would simplify this, but it could be done.

I was able to use this with a free Google Cloud account previously. Google gives you $300 in free credits to use for testing and evaluation. Here are some more details: cloud.google.com/vision/docs/drag-and-drop

​@@TechExpertTutorials thanx 🤗