52 lines
1.9 KiB
Python
52 lines
1.9 KiB
Python
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import os
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from . import res
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def get_encoding_time_percentage(filename, encoding_times_av1):
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encoding_times_hevc = res.get_encoding_time_hevc(filename)
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return round(
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encoding_times_av1 / (encoding_times_hevc / 100),
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2
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)
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def start_workflow():
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res.bootstrap_folder_structure()
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aggregated_metrics = {}
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output_file = os.path.join(
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res.get_path_results_aggregations(),
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res.get_filename_results_aggregations_av1()
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)
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for f in res.get_all_encoded_files_av1():
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filename = os.path.splitext(os.path.basename(f))[0]
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sampleNumber = res.get_sample_number_from_filename(filename)
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preset = res.get_preset_from_encode_filename(filename)
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crf = res.get_crf_from_encode_filename(filename)
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if not preset in aggregated_metrics.keys():
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aggregated_metrics[preset] = {}
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if not crf in aggregated_metrics[preset].keys():
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aggregated_metrics[preset][crf] = {}
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if not "samples" in aggregated_metrics[preset][crf].keys():
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aggregated_metrics[preset][crf]["samples"] = {}
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aggregated_metrics[preset][crf]["samples"][sampleNumber] = {
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"encoding_time": res.get_encoding_time_av1(filename),
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"filesize_percentage": res.get_filesize_percentage(f),
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"vmaf_score": res.get_vmaf_score_of_encode(filename)
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}
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aggregated_metrics[preset][crf]["samples"][sampleNumber]["encoding_time_percentage"] = get_encoding_time_percentage(
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filename,
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aggregated_metrics[preset][crf]["samples"][sampleNumber]["encoding_time"]
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)
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for preset in aggregated_metrics.keys():
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for crf in aggregated_metrics[preset].keys():
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aggregated_metrics[preset][crf] = res.aggregated_metrics(
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aggregated_metrics[preset][crf]
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)
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res.write_dict_to_json_file(output_file, aggregated_metrics)
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