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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"![img_grid_{scheduler_name}](/file=./{image_name})\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 | |