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| import json | |
| from typing import Dict | |
| def prepare_report(scheduler_name: str, results: dict): | |
| image_grid = results["images"] | |
| scores = results["scores"] | |
| img_str = "" | |
| image_name = f"{scheduler_name}_images.png" | |
| image_grid.save(image_name) | |
| img_str = img_str = f"\n" | |
| report_str = f""" | |
| \n\n## {scheduler_name} | |
| ### Sample images | |
| {img_str} | |
| ### Scores | |
| {scores} | |
| \n\n | |
| """ | |
| return report_str | |
| def add_psnr_ssim_to_report( | |
| original_scheduler_name: str, ssim_scores: Dict = None, psnr_scores: Dict = None | |
| ) -> str: | |
| current_str = "" | |
| if ssim_scores is not None: | |
| current_str += f""" | |
| \n\n | |
| ## SSIM | |
| SSIM computed w.r.t the images generated with {original_scheduler_name}:\n\n {json.dumps(ssim_scores, indent=6)} | |
| """ | |
| if psnr_scores is not None: | |
| current_str += f""" | |
| \n\n | |
| ## PSNR | |
| PSNR computed w.r.t the images generated with {original_scheduler_name}:\n\n {json.dumps(psnr_scores, indent=6)} | |
| """ | |
| return current_str | |