Inspiration
- With the rise of AI, it becomes easier for artists to express themselves without having to go through the process of creating an artwork.
- Artificial intelligence has the ability to consistently learn from past experiences and adapt to changes, making it the perfect candidate for eventually generating meaningful captions.
What it does
- A single line of text can be used to generate art. The model will generate the art based on the text provided.
- The AI-based caption generator can generate captions for your images within seconds.
How we built it
- The AI art generator was created using Generative adversarial network and Imagenet 16384.
- The AI caption generator was developed using LSTM and was trained on the flickr dataset.
- HTML, CSS, and Bootstrap were used to create the user interface.
- We used Django as our backend to integrate our Deep learning model with the UI.
Challenges we ran into
- Deep learning model training required a significant amount of time and computation power.
- It was difficult to integrate our deep learning model with the user interface.
- Improving the model's accuracy was an aesthetic taste.
Accomplishments that we're proud of
- We were able to create an amazing model that can generate art and captions for images.
- Possibly developing a web application and incorporating this model was incredible.
What we learned
We discovered a lot about Deep Learning models and their applications. We got some knowledge on MLOps. We most likely learned more about GANs and LSTM.
What's next for Artist Asylum
- Should try to reduce the process time for each request.
- Improve the AI art generator with more options which can make the art generation flexible.
- Working on to improve the accuracy of the models.
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