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Ai_Image_Captioner

Turning images into captions/stories

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Project: AI-Powered Image Captioning Tool Description: An AI-powered image captioning tool using Python, which will generate human-like captions for images uploaded by users.

Features:

1	Image uploading: Allow users to upload images (JPEG, PNG, etc.) to the application. Implement proper file validation 
    and size limits to ensure security.
2	Image preprocessing: Preprocess the uploaded images to make them suitable for analysis by the AI model. 
    You can use libraries like OpenCV, Pillow, or scikit-image for this purpose.
3	AI model: Train a deep learning model using a pre-trained neural network (e.g., VGG16, ResNet, Inception, etc.) 
    and a recurrent neural network (RNN) or transformer model for generating captions. You can use TensorFlow or PyTorch
    for implementing the AI model.
4	Caption generation: Integrate the trained AI model with your web application to generate captions for the uploaded images.
5	User interface: Develop a user-friendly and responsive web interface for the application. 
    You can use HTML, CSS, and JavaScript along with a front-end framework like Bootstrap or Material-UI.
6	REST API: Create a REST API to enable other developers to use your image captioning service in their applications.



•	Consider using pre-trained models and fine-tuning them on a dataset like MS COCO for better results.
•	Use libraries like TensorFlow or PyTorch for training and deploying the AI model.
•	Study and follow best practices for web application security, such as OWASP guidelines.

Django will be used

Look into MS COCO dataset

Lets start with the most difficult part, the AI model

Next will be the image preprocessing

Then the image uploading

Then the user interface/webservice using django

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