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cfg: don't duplicate fctm-related configurartion params
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cfgs/codec/fctm.yaml

Lines changed: 1 addition & 102 deletions
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@@ -4,105 +4,4 @@ experiment: "" # e.g. "_preset_medium" name experiment preceded by "_"
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output_dir: "${pipeline.output_dir_root}/${.type}${.experiment}/${dataset.datacatalog}/${dataset.config.dataset_name}/qp${codec.tools.inner_codec.enc_configs.qp}"
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bitstream_name: "${dataset.config.dataset_name}_qp${codec.tools.inner_codec.enc_configs.qp}"
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#============================== Configuration below are the same with fctm.yaml in FCTM v9 =========================================
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# NOTE: Configuration below can always be replaced with the latest fctm.yaml in FCTM if there are any incompatiable issues
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verbosity: 0
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coding_behaviour: "all"
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device:
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all: "cpu"
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enc: ${codec.device.all}
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dec: ${codec.device.all}
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mac_computation: False # multipy-accumulate computation
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fcm_sample_stream_wrapper_enabled: True
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enc_configs:
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qp: 27
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frame_rate: 30
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intra_period: 1
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n_bit: 10
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parallel_encoding: False # std inner codec parallel option
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max_subprocess_limit: null # null = implicit CPU count limit, value = explicit (integer) limit
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hash_check: 0 # md5 hash check
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tools:
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feature_scale: # Encoder only
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enabled: False
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feature_transform:
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enabled: False
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feature_importance_computation:
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enabled: False
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pre_computed: null
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feature_reduction: # reserved for restoration part as well
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nn_feature_inv_transform:
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name: 'light_fedrnet' # (m71247) 'light_fedrnet_with_nn_codec' (m73346)
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selective_learning_strategy: False # by default (m71203)
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split_ctx: "obj" # or "seg" # or "alt1" or "dn53"
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model_dir: "pretrained_weights"
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cttc_model: True
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channel_rearrangement:
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enabled: True
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channel_removal: # (m71203)
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enabled: True # by default
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period: ${codec.enc_configs.intra_period}
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# When nn_feature_inv_transform.selective_learning_strategy or channel_rearrangement.enabled is equal to True
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# channel_removal_indication should also be inferred to be True in S/W
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channel_restoration_indication: False # test all configs
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use_lcr: True # (m74096)
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temporal_resampling_enabled: False # (m67615)
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# To properly enable Temporal resampling ,
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# temporal_resampling_enabled = True and
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# "cfgs/codec/vtm-23.3/encoder_lowdelay_vtm_gop4.cfg" must be used
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refinements: # (m68664)
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on_restored_ftensor: # (m68391)
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enabled: True
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period: ${codec.enc_configs.intra_period}
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on_reduced_ftensor:
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enabled: True
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period: ${codec.enc_configs.intra_period}
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conversion:
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type: 'tensor_packing' # or 'bypass'
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n_bit: ${codec.enc_configs.n_bit}
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resized_channel_packing: # (m71931)
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enabled: True
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period: ${codec.enc_configs.intra_period}
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use_lcr: True # (m74096)
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inner_codec:
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type: 'vtm'
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stash_outputs: True
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inner_coding_max_chroma_format: 0 # 4:0:0 only
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inner_coding_max_pred_constraint: 1 # Intra + uni-prediction (I, P slices)
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enc_configs: ${codec.enc_configs}
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split_ctx: ${codec.tools.feature_reduction.nn_feature_inv_transform.split_ctx}
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codec_paths:
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_root: "/path/to/vtm" # of HM, JM...
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enc_exe: "${._root}/bin/EncoderAppStatic" # or TappEncoderStatic, lencod...
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dec_exe: "${._root}/bin/DecoderAppStatic" # or TappDecoderStatic, ldecod...
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merge_exe: "${._root}/bin/parcatStatic"
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cfg_file: "${._root}/cfg/encoder_intra_vtm.cfg"
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default_cfg_file: "${._root}/cfg/encoder.cfg"
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# two variables below are needed when type is "nn_inner_codec"
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enc_weight: "pretrained_weights/path/to/inner_encoder_weight"
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dec_weight: "pretrained_weights/path/to/inner_encoder_weight"
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sei_messages:
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vision_model_info:
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enabled: True
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vision_model_cfg:
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enabled: False
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update: False
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conf_thres: 0.05
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max_dets: 100
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# configuration parameters can be retrieved / copied from the config file at cfgs/codec/compressai_vision_fctm.cfg within the FCTM directory

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