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This is my AI project made using hugging face which analyses a image and provides a summary of the image about the counts of objects in it and also Predicts the possible scene of image

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InsightVision: Detect, Analyze, Summarize 🚀

InsightVision is a powerful AI-powered application designed to detect objects within images, analyze the scene, and generate a summary with object counts. Additionally, it provides a scene description based on the detected objects. This tool is perfect for understanding complex images and gaining valuable insights from them.

🔧 Built Using:

  • YOLOv5: A cutting-edge object detection model for identifying objects in images.
  • Gradio: For creating a user-friendly web interface.
  • OpenCV: For image processing and manipulation.
  • Torch: For deep learning model handling.
  • Python: The primary programming language used to implement the application.
  • PIL (Python Imaging Library): For image processing and displaying images.

🌟 Key Features:

  1. Object Detection:

    • Automatically detects objects in uploaded images using YOLOv5.
    • Supports common objects like people, vehicles, animals, and more.
  2. Scene Summarization:

    • Provides a textual summary of the detected objects along with their counts.
    • Offers insights into the scene based on the object count and types.
  3. Scene Description:

    • Automatically generates a scene description based on the detected objects, helping users understand the context of the image.
  4. Image Download Option:

    • After processing, users can download the annotated image with all detected objects marked.
  5. Share Feature:

    • Users can generate a shareable link to share their results with others directly.
  6. Interactive Web Interface:

    • Easy-to-use web interface built with Gradio.
    • Upload images, capture from a webcam, or paste from the clipboard to get results instantly.
  7. Object Count:

    • Displays the count of detected objects, making it easier to analyze object distribution within the image.
  8. Animated Gradient Background:

    • Features an aesthetically pleasing animated gradient background that enhances the user experience.

📸 Image Upload Options:

InsightVision allows three ways to provide images:

  • Upload from File: You can upload an image directly from your device.
  • Capture from Webcam: Capture a live image using your device's webcam.
  • Paste from Clipboard: Paste an image directly from your clipboard into the app.

🚀 Deployment Guide:

Follow these steps to deploy the InsightVision app:

  1. Create a Space on Hugging Face:

    • Log in to Hugging Face and create a new Space for the application.
  2. Upload Files:

    • Upload the following files to the Hugging Face Space:
      • app.py (Main application file)
      • requirements.txt (Dependencies file)
  3. Set Up Requirements:

    • Add the following dependencies to requirements.txt:
      gradio
      torch
      opencv-python-headless
      numpy
      pillow
  4. Store API Keys (Optional):

    • If your app requires API keys for additional functionality, store them securely in the Secrets section of Hugging Face.
  5. Launch the Space:

    • Once the files are uploaded and dependencies are set up, launch your Space, and the application will be live!

💡 Contribution Guide:

We welcome contributions to enhance the InsightVision project! Here are some ideas to get started:

  • Improve Object Detection: Support for additional objects or models.
  • Refine Scene Descriptions: Enhance the scene description generation for more diverse contexts.
  • UI Enhancements: Add more interactive elements or improve the UI/UX.

Feel free to fork the repository, submit pull requests, or open issues for suggestions!

🌍 Join the Community:

This project is powered by a community of developers and AI enthusiasts. Let’s collaborate and make this tool even more powerful!

🎉 Start your journey with InsightVision now!

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This is my AI project made using hugging face which analyses a image and provides a summary of the image about the counts of objects in it and also Predicts the possible scene of image

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