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add modelzoo model configs from DeepLabCut
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‎dlclive/modelzoo/model_configs/dlcrnet.yaml‎

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# Project definitions (do not edit)
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Task:
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scorer:
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date:
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multianimalproject:
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identity:
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# Project path (change when moving around)
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project_path:
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# Annotation data set configuration (and individual video cropping parameters)
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video_sets:
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bodyparts:
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# Fraction of video to start/stop when extracting frames for labeling/refinement
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start:
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stop:
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numframes2pick:
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# Plotting configuration
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skeleton: []
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skeleton_color: black
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pcutoff:
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dotsize:
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alphavalue:
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colormap:
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# Training,Evaluation and Analysis configuration
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TrainingFraction:
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iteration:
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default_net_type:
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default_augmenter:
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snapshotindex:
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batch_size: 1
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# Cropping Parameters (for analysis and outlier frame detection)
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cropping:
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#if cropping is true for analysis, then set the values here:
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x1:
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x2:
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y1:
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y2:
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# Refinement configuration (parameters from annotation dataset configuration also relevant in this stage)
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corner2move2:
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move2corner:
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alpha_r: 0.02
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apply_prob: 0.5
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clahe: true
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claheratio: 0.1
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crop_sampling: hybrid
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crop_size:
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- 400
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- 400
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cropratio: 0.4
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dataset:
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dataset_type: multi-animal-imgaug
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decay_steps: 30000
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display_iters: 500
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edge: false
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emboss:
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alpha:
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- 0.0
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- 1.0
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embossratio: 0.1
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strength:
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- 0.5
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- 1.5
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global_scale: 0.8
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histeq: true
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histeqratio: 0.1
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init_weights:
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intermediate_supervision: false
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intermediate_supervision_layer: 12
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location_refinement: true
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locref_huber_loss: true
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locref_loss_weight: 0.05
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locref_stdev: 7.2801
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lr_init: 0.0005
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max_input_size: 1500
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max_shift: 0.4
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mean_pixel:
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- 123.68
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- 116.779
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- 103.939
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metadataset:
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min_input_size: 64
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mirror: false
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multi_stage: true
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multi_step:
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- - 0.0001
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- 7500
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- - 5.0e-05
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- 12000
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- - 1.0e-05
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- 200000
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net_type: resnet_50
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num_idchannel: 0
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num_joints: 27
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num_limbs: 351
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optimizer: adam
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pafwidth: 20
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pairwise_huber_loss: false
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pairwise_loss_weight: 0.1
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pairwise_predict: false
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partaffinityfield_graph: []
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partaffinityfield_predict: false
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pos_dist_thresh: 17
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pre_resize: []
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rotation: 25
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rotratio: 0.4
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save_iters: 10000
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scale_jitter_lo: 0.5
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scale_jitter_up: 1.25
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sharpen: false
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sharpenratio: 0.3
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stride: 8.0
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weigh_only_present_joints: false
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gradient_masking: true
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weight_decay: 0.0001
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weigh_part_predictions: false

‎dlclive/modelzoo/model_configs/fasterrcnn_mobilenet_v3_large_fpn.yaml‎

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data:
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colormode: RGB
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inference:
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normalize_images: true
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train:
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affine:
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p: 0.5
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rotation: 30
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scaling: [ 1.0, 1.0 ]
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translation: 40
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collate:
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type: ResizeFromDataSizeCollate
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min_scale: 0.4
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max_scale: 1.0
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min_short_side: 128
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max_short_side: 1152
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multiple_of: 32
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to_square: false
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hflip: true
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normalize_images: true
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device: auto
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model:
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type: FasterRCNN
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variant: fasterrcnn_mobilenet_v3_large_fpn
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box_score_thresh: 0.6
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freeze_bn_stats: true
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freeze_bn_weights: false
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runner:
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type: DetectorTrainingRunner
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key_metric: "test.mAP@50:95"
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key_metric_asc: true
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eval_interval: 10
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optimizer:
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type: AdamW
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params:
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lr: 1e-5
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scheduler:
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type: LRListScheduler
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params:
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milestones: [ 90 ]
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lr_list: [ [ 1e-6 ] ]
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snapshots:
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max_snapshots: 5
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save_epochs: 25
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save_optimizer_state: false
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train_settings:
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batch_size: 1
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dataloader_workers: 0
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dataloader_pin_memory: false
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display_iters: 500
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epochs: 250

‎dlclive/modelzoo/model_configs/fasterrcnn_resnet50_fpn_v2.yaml‎

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data:
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colormode: RGB
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inference:
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normalize_images: true
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train:
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affine:
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p: 0.5
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rotation: 30
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scaling: [ 1.0, 1.0 ]
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translation: 40
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collate:
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type: ResizeFromDataSizeCollate
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min_scale: 0.4
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max_scale: 1.0
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min_short_side: 128
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max_short_side: 1152
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multiple_of: 32
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to_square: false
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hflip: true
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normalize_images: true
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device: auto
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model:
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type: FasterRCNN
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variant: fasterrcnn_resnet50_fpn_v2
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box_score_thresh: 0.6
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freeze_bn_stats: true
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freeze_bn_weights: false
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runner:
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type: DetectorTrainingRunner
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key_metric: "test.mAP@50:95"
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key_metric_asc: true
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eval_interval: 10
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optimizer:
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type: AdamW
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params:
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lr: 1e-5
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scheduler:
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type: LRListScheduler
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params:
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milestones: [ 90 ]
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lr_list: [ [ 1e-6 ] ]
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snapshots:
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max_snapshots: 5
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save_epochs: 25
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save_optimizer_state: false
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train_settings:
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batch_size: 1
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dataloader_workers: 0
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dataloader_pin_memory: false
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display_iters: 500
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epochs: 250

‎dlclive/modelzoo/model_configs/hrnet_w32.yaml‎

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data:
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colormode: RGB
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inference:
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auto_padding:
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pad_width_divisor: 32
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pad_height_divisor: 32
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normalize_images: true
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train:
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affine:
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p: 0.5
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scaling: [1.0, 1.0]
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rotation: 30
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translation: 0
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gaussian_noise: 12.75
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normalize_images: true
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auto_padding:
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pad_width_divisor: 32
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pad_height_divisor: 32
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device: auto
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method: td
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model:
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backbone:
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type: HRNet
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model_name: hrnet_w32
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pretrained: false
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freeze_bn_stats: True
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freeze_bn_weights: False
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interpolate_branches: false
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increased_channel_count: false
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backbone_output_channels: 32
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heads:
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bodypart:
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type: HeatmapHead
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weight_init: "normal"
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predictor:
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type: HeatmapPredictor
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apply_sigmoid: false
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clip_scores: true
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location_refinement: false
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locref_std: 7.2801
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target_generator:
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type: HeatmapGaussianGenerator
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num_heatmaps: "num_bodyparts"
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pos_dist_thresh: 17
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heatmap_mode: KEYPOINT
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generate_locref: false
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locref_std: 7.2801
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criterion:
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heatmap:
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type: WeightedMSECriterion
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weight: 1.0
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heatmap_config:
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channels: [32, "num_bodyparts"]
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kernel_size: [1]
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strides: [1]
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net_type: hrnet_w32
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runner:
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type: PoseTrainingRunner
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key_metric: "test.mAP"
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key_metric_asc: true
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eval_interval: 10
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optimizer:
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type: AdamW
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params:
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lr: 1e-5
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scheduler:
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type: LRListScheduler
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params:
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lr_list: [ [ 1e-6 ], [ 1e-7 ] ]
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milestones: [ 160, 190 ]
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snapshots:
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max_snapshots: 5
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save_epochs: 25
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save_optimizer_state: false
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train_settings:
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batch_size: 1
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dataloader_workers: 0
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dataloader_pin_memory: false
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display_iters: 500
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epochs: 200
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seed: 42

‎dlclive/modelzoo/model_configs/resnet_50.yaml‎

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data:
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colormode: RGB
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inference:
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normalize_images: true
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train:
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affine:
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p: 0.5
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scaling: [1.0, 1.0]
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rotation: 30
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translation: 0
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gaussian_noise: 12.75
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normalize_images: true
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device: auto
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method: td
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model:
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backbone:
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type: ResNet
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model_name: resnet50_gn
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output_stride: 16
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freeze_bn_stats: false
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freeze_bn_weights: false
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backbone_output_channels: 2048
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heads:
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bodypart:
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type: HeatmapHead
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weight_init: normal
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predictor:
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type: HeatmapPredictor
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apply_sigmoid: false
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clip_scores: true
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location_refinement: true
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locref_std: 7.2801
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target_generator:
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type: HeatmapGaussianGenerator
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num_heatmaps: "num_bodyparts"
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pos_dist_thresh: 17
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heatmap_mode: KEYPOINT
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generate_locref: true
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locref_std: 7.2801
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criterion:
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heatmap:
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type: WeightedMSECriterion
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weight: 1.0
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locref:
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type: WeightedHuberCriterion
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weight: 0.05
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heatmap_config:
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channels:
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- 2048
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- "num_bodyparts"
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kernel_size:
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- 3
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strides:
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- 2
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locref_config:
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channels:
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- 2048
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- "num_bodyparts x 2"
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kernel_size:
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- 3
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strides:
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- 2
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net_type: resnet_50
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runner:
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type: PoseTrainingRunner
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key_metric: "test.mAP"
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key_metric_asc: true
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eval_interval: 10
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optimizer:
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type: AdamW
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params:
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lr: 1e-5
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scheduler:
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type: LRListScheduler
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params:
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lr_list: [ [ 1e-6 ], [ 1e-7 ] ]
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milestones: [ 160, 190 ]
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snapshots:
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max_snapshots: 5
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save_epochs: 25
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save_optimizer_state: false
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train_settings:
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batch_size: 1
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dataloader_workers: 0
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dataloader_pin_memory: false
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display_iters: 500
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epochs: 100
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seed: 42

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