Question: Develop an experimentation pipeline in Google Colab for generating a 2 0 4 8 x 2 0 4 8 image from a text prompt describing
Develop an experimentation pipeline in Google Colab for generating a x image from a text prompt describing a person and their background, emphasizing photorealism, steerability, and resourcetime efficiency.
Core Requirements: Platform: Google ColabKaggleLocal Setup. Programming Language: Python. Models: Explore AIML modelscomponents for image generation and manipulation. Automatic Workflow: Ensure the process requires no manual intervention.Tasks: Image Generation from Text Prompt: Input: A text prompt describing a person and a background. Process: Experiment with different models or combinations thereof to generate an image that matches the prompt. Output: A x photorealistic image of the described scene.Implementation Guidelines: Explore various Al models, including communityfinetuned checkpoints, custom models, Mixture of models, LoRAs or whatever you can research to be a great direction for enhanced results. Prioritize photorealism, steerabilitythe ability to control image details according to possible different complex prompts and optimization of processing time and resources. You'd need to upscale the image from base quality.Experimentation and Reporting: Document the experimentation process, including different models and methods tested and corresponding resultant images, with a focus on photorealism, steerability, and efficiency. Report should detail the approach, experiments, observations, and inferences about the most effective pipeline for the task. Encourage comprehensive documentation of both successes and limitations with corresponding examples.Submission: Google Colab notebook with code. Detailed report on experimentation and findings.Evaluation Criteria: Effectiveness in achieving photorealism Prompt Steerability Creativity and efficiency of the solution. Comprehensive and clear documentation and reporting for narrowing down the right expereimentation direction. Stepwise Evaluation will be done. Add a brief about your familiarity of Diffusion space before the assignment at the top
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