computer-vision-demo

Here's a small taste of what you create with Cloudinary's vast analysis capabilities. The possibilities are endless!

In this demo, you'll be asked upload up to 3 images. Cloudinary will analyze those assets and return the images automatically transformed accordingly along with a description.

Setup instructions (after cloning from GitHub)

1. Enable required add-ons Go to the Add-ons page of the Console Settings and enable:

   • Google Auto Tagging
   • OCR Text Detection and Extraction
   • Amazon Rekognition AI Moderation

2. Create a virtual environment

   python3 -m venv venv
   

3. Activate your virtual environment

   source venv/bin/activate
   

4. Install dependencies

   pip install -r requirements.txt
   

5. Create a .env file Add the following environment variable:

   CLOUDINARY_URL=cloudinary://<api_key>:<api_secret>@<cloud_name>
   

6. Replace placeholders Update the .env file with your Cloudinary credentials, which you can find in the API Keys page of the Console Settings.

7. Update the cloudName value In index.html, replace the value for cloudName with your Cloudinary cloud name.

8. (First-time only) Create the upload preset In demo.py, uncomment the following block inside the index() route the first time you run the app:

     # Create the upload preset only once:
     cloudinary.api.create_upload_preset(
       name = "docs_computer_vision_demo",
       unsigned = True,  
       use_filename=True,
       folder="docs/computer_vision_demo",
       tags="computer_vision_demo",
       colors= True,
       faces= True,
       categorization = "google_tagging", auto_tagging = 0.7,
       ocr = "adv_ocr",
       moderation = "aws_rek"
     )
   

   {note} Remember to replace the comments after the first run. {/note}

9. Run the Flask app

   python demo.py