AV1-vs-HEVC/workflows/identify_possible_candidates.py
2024-01-12 20:33:08 +01:00

86 lines
3.8 KiB
Python

import copy
import os
from . import res
from pprint import pprint
def start_workflow():
res.bootstrap_folder_structure()
aggregated_metrics_av1_from_file = res.read_dict_from_json_file(
os.path.join(
res.get_path_results_aggregations(),
res.get_filename_results_aggregations_av1()
)
)
aggregated_metrics_hevc_from_file = res.read_dict_from_json_file(
os.path.join(
res.get_path_results_aggregations(),
res.get_filename_results_aggregations_hevc()
)
)
aggregated_metrics_hevc = {}
for preset, data_of_preset in aggregated_metrics_hevc_from_file.items():
for crf, data_of_crf in data_of_preset.items():
aggregated_metrics_hevc = copy.deepcopy(data_of_crf)
del aggregated_metrics_hevc['samples']
tolerance_filesize_in_percent = 20
hevc_filesize_percentage_mean = aggregated_metrics_hevc["filesize_percentage"]["mean"]
hevc_filesize_percentage_median = aggregated_metrics_hevc["filesize_percentage"]["median"]
hevc_filesize_percentage_mean_with_tolerance = aggregated_metrics_hevc["filesize_percentage"]["mean"] * (1 + tolerance_filesize_in_percent / 100)
hevc_filesize_percentage_median_with_tolerance = aggregated_metrics_hevc["filesize_percentage"]["median"] * (1 + tolerance_filesize_in_percent / 100)
hevc_vmaf_score_mean = aggregated_metrics_hevc["vmaf_score"]["mean"]
hevc_vmaf_score_median = aggregated_metrics_hevc["vmaf_score"]["median"]
possible_candidates = {}
possible_candidates_with_tolerance = {}
for preset, data_of_preset in aggregated_metrics_av1_from_file.items():
for crf, data_of_crf in data_of_preset.items():
viable_only_with_tolerance = False
av1_filesize_percentage_mean = data_of_crf["filesize_percentage"]["mean"]
av1_filesize_percentage_median = data_of_crf["filesize_percentage"]["median"]
av1_vmaf_score_mean = data_of_crf["vmaf_score"]["mean"]
av1_vmaf_score_median = data_of_crf["vmaf_score"]["median"]
if av1_filesize_percentage_mean > hevc_filesize_percentage_mean:
if av1_filesize_percentage_mean > hevc_filesize_percentage_mean_with_tolerance:
continue
viable_only_with_tolerance = True
if av1_filesize_percentage_median > hevc_filesize_percentage_median:
if av1_filesize_percentage_median > hevc_filesize_percentage_median_with_tolerance:
continue
viable_only_with_tolerance = True
if av1_vmaf_score_mean < hevc_vmaf_score_mean:
continue
if av1_vmaf_score_median < hevc_vmaf_score_median:
continue
if viable_only_with_tolerance:
if not preset in possible_candidates_with_tolerance.keys():
possible_candidates_with_tolerance[preset] = {}
possible_candidates_with_tolerance[preset][crf] = copy.deepcopy(data_of_crf)
del possible_candidates_with_tolerance[preset][crf]["samples"]
continue
if not preset in possible_candidates.keys():
possible_candidates[preset] = {}
possible_candidates[preset][crf] = copy.deepcopy(data_of_crf)
del possible_candidates[preset][crf]["samples"]
output_file = os.path.join(
res.get_path_results_candidates(),
res.get_filename_results_candidates_viable()
)
output_file_with_tolerance = os.path.join(
res.get_path_results_candidates(),
res.get_filename_results_candidates_viable_with_tolerance()
)
res.write_dict_to_json_file(output_file, possible_candidates)
res.write_dict_to_json_file(output_file_with_tolerance, possible_candidates_with_tolerance)