Build a generative image model in Python with PyTorch that creates ad banners or visuals for marketing campaigns, integrated with a predictive analytics component (e.g., using Prophet for time-series forecasting) to predict campaign performance based on historical data. Generate images conditioned on these predictions (e.g., vibrant designs for high-engagement forecasts). Provide full code, including data preprocessing, model fine-tuning, and examples for real-time use in a business app targeting surged demand in content personalization.
7b49638 verified | ```txt | |
| torch>=2.0.0 | |
| torchvision>=0.15.0 | |
| transformers>=4.30.0 | |
| diffusers>=0.19.0 | |
| prophet>=1.1.0 | |
| pandas>=1.5.0 | |
| numpy>=1.21.0 | |
| matplotlib>=3.5.0 | |
| pillow>=9.0.0 | |
| fastapi>=0.95.0 | |
| uvicorn>=0.21.0 | |
| python-multipart>=0.0.5 | |
| ``` |