Project that will use the AZURE AI service to detect objects in an image
This Python script leverages Azure Computer Vision to analyze images and detect objects within them.
Prerequisites:
Azure Account: You'll need an active Azure account. Azure Computer Vision Subscription: Create an Azure Computer Vision resource in the Azure portal. Python: Ensure Python is installed on your system. Packages: Install the required dependencies using pip install -r requirements.txt. Setup:
Create an Azure Computer Vision resource:
Log in to the Azure portal. Create a new resource and search for "Computer Vision". Follow the instructions to create the resource and obtain the access keys. Create a .env file:
Create a file named .env in the same directory as the script. Add the following lines, replacing your_endpoint and your_key with the values obtained from your Azure Computer Vision resource: ENDPOINT=your_endpoint KEY=your_key Example:
ENDPOINT=https://your-resource.cognitiveservices.azure.com/ KEY=your_access_key Run the script:
Open a terminal and navigate to the directory containing the script. Execute the script: python object-detector.py Additional options:
Specify an image: Provide a path to an image as an argument when running the script: python object-detector.py images/my_image.jpg Customize detection: Modify the visual_features list in the AnalyzeImage function to tailor the detection to your specific needs. Code explanation:
load_dotenv(): Loads environment variables from the .env file. ImageAnalysisClient: Creates a client to interact with the Azure Computer Vision service. analyze_image_in_stream: Sends the image to the service for analysis. ImageCaptions, ImageTags, ImageObjects: Functions to process the analysis results and display captions, tags, and detected objects.
