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Merge pull request #12 from WEHI-ResearchComputing/add-configs
Package configs into partinet
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‎README.md‎

Lines changed: 121 additions & 108 deletions
Original file line numberDiff line numberDiff line change
@@ -110,49 +110,55 @@ partinet train step1 --help
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Usage: partinet train step1 [OPTIONS]
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Options:
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--cfg TEXT model.yaml path [required]
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--weight TEXT initial weights path [required]
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--data TEXT data.yaml path [default: data/coco.yaml]
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--hyp TEXT hyperparameters path [default:
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hyp/hyp.scratch.p5.yaml]
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--epochs INTEGER [default: 300]
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--batch-size INTEGER total batch size for all GPUs [default: 16]
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--img-size INTEGER... [train, test] image sizes [default: 640, 640]
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--rect rectangular training
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--resume resume most recent training
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--resume-ckpt TEXT checkpoint to resume from
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--nosave only save final checkpoint
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--notest only test final epoch
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--noautoanchor disable autoanchor check
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--bucket TEXT gsutil bucket
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--cache-images cache images for faster training
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--image-weights use weighted image selection for training
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--device TEXT cuda device, i.e. 0 or 0,1,2,3 or cpu
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--multi-scale vary img-size +/- 50%%
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--single-cls train multi-class data as single-class
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--adam use torch.optim.Adam() optimizer
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--sync-bn use SyncBatchNorm, only available in DDP mode
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--local_rank INTEGER DDP parameter, do not modify [default: -1]
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--workers INTEGER maximum number of dataloader workers [default: 8]
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--project TEXT save to project/name [default: runs/train]
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--entity TEXT W&B entity
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--name TEXT save to project/name [default: exp]
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--exist-ok existing project/name ok, do not increment
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--quad quad dataloader
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--label-smoothing FLOAT Label smoothing epsilon [default: 0.0]
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--upload_dataset Upload dataset as W&B artifact table
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--bbox_interval INTEGER Set bounding-box image logging interval for W&B
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[default: -1]
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--save_period INTEGER Log model after every "save_period" epoch
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[default: -1]
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--artifact_alias TEXT version of dataset artifact to be used [default:
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latest]
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--freeze INTEGER Freeze layers: backbone of yolov7=50, first3=0 1 2
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[default: 0]
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--v5-metric assume maximum recall as 1.0 in AP calculation
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--single-backbone train single backbone model
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--linear-lr linear LR
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--help Show this message and exit.
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--backbone-detector [yolov7|yolov7-w6|yolov7x]
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The choice of backbone to be used.
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[default: yolov7]
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--weight TEXT initial weights path [required]
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--data TEXT data.yaml path [default: data/coco.yaml]
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--hyp [scratch.p5|scratch.p6|finetune.dynamic.adam]
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hyperparameters path [default: scratch.p5]
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--epochs INTEGER [default: 300]
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--batch-size INTEGER total batch size for all GPUs [default: 16]
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--img-size INTEGER... [train, test] image sizes [default: 640,
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640]
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--rect rectangular training
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--resume resume most recent training
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--resume-ckpt TEXT checkpoint to resume from
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--nosave only save final checkpoint
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--notest only test final epoch
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--noautoanchor disable autoanchor check
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--bucket TEXT gsutil bucket
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--cache-images cache images for faster training
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--image-weights use weighted image selection for training
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--device TEXT cuda device, i.e. 0 or 0,1,2,3 or cpu
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--multi-scale vary img-size +/- 50%%
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--single-cls train multi-class data as single-class
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--adam use torch.optim.Adam() optimizer
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--sync-bn use SyncBatchNorm, only available in DDP
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mode
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--local_rank INTEGER DDP parameter, do not modify [default: -1]
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--workers INTEGER maximum number of dataloader workers
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[default: 8]
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--project TEXT save to project/name [default: runs/train]
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--entity TEXT W&B entity
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--name TEXT save to project/name [default: exp]
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--exist-ok existing project/name ok, do not increment
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--quad quad dataloader
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--label-smoothing FLOAT Label smoothing epsilon [default: 0.0]
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--upload_dataset Upload dataset as W&B artifact table
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--bbox_interval INTEGER Set bounding-box image logging interval for
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W&B [default: -1]
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--save_period INTEGER Log model after every "save_period" epoch
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[default: -1]
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--artifact_alias TEXT version of dataset artifact to be used
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[default: latest]
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--freeze INTEGER Freeze layers: backbone of yolov7=50,
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first3=0 1 2 [default: 0]
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--v5-metric assume maximum recall as 1.0 in AP
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calculation
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--single-backbone train single backbone model
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--linear-lr linear LR
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--help Show this message and exit.
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```
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TODO: more details...
@@ -170,84 +176,91 @@ subsubcommand.
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Usage: partinet train step2 [OPTIONS]
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Options:
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--cfg TEXT model.yaml path [required]
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--weight TEXT initial weights path [required]
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--data TEXT data.yaml path [default: data/coco.yaml]
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--hyp TEXT hyperparameters path [default:
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hyp/hyp.scratch.p5.yaml]
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--epochs INTEGER [default: 300]
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--batch-size INTEGER total batch size for all GPUs [default: 16]
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--img-size INTEGER... [train, test] image sizes [default: 640, 640]
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--rect rectangular training
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--resume resume most recent training
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--resume-ckpt TEXT checkpoint to resume from
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--nosave only save final checkpoint
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--notest only test final epoch
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--noautoanchor disable autoanchor check
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--bucket TEXT gsutil bucket
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--cache-images cache images for faster training
189-
--image-weights use weighted image selection for training
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--device TEXT cuda device, i.e. 0 or 0,1,2,3 or cpu
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--multi-scale vary img-size +/- 50%%
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--single-cls train multi-class data as single-class
193-
--adam use torch.optim.Adam() optimizer
194-
--sync-bn use SyncBatchNorm, only available in DDP mode
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--local_rank INTEGER DDP parameter, do not modify [default: -1]
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--workers INTEGER maximum number of dataloader workers [default: 8]
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--project TEXT save to project/name [default: runs/train]
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--entity TEXT W&B entity
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--name TEXT save to project/name [default: exp]
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--exist-ok existing project/name ok, do not increment
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--quad quad dataloader
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--label-smoothing FLOAT Label smoothing epsilon [default: 0.0]
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--upload_dataset Upload dataset as W&B artifact table
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--bbox_interval INTEGER Set bounding-box image logging interval for W&B
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[default: -1]
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--save_period INTEGER Log model after every "save_period" epoch
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[default: -1]
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--artifact_alias TEXT version of dataset artifact to be used [default:
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latest]
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--freeze INTEGER Freeze layers: backbone of yolov7=50, first3=0 1 2
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[default: 0]
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--v5-metric assume maximum recall as 1.0 in AP calculation
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--help Show this message and exit.
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--backbone-detector [yolov7|yolov7-w6|yolov7x]
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The choice of backbone to be used.
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[default: yolov7]
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--weight TEXT initial weights path [required]
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--data TEXT data.yaml path [default: data/coco.yaml]
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--hyp [scratch.p5|scratch.p6|finetune.dynamic.adam]
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hyperparameters path [default: scratch.p5]
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--epochs INTEGER [default: 300]
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--batch-size INTEGER total batch size for all GPUs [default: 16]
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--img-size INTEGER... [train, test] image sizes [default: 640,
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640]
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--rect rectangular training
191+
--resume resume most recent training
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--resume-ckpt TEXT checkpoint to resume from
193+
--nosave only save final checkpoint
194+
--notest only test final epoch
195+
--noautoanchor disable autoanchor check
196+
--bucket TEXT gsutil bucket
197+
--cache-images cache images for faster training
198+
--image-weights use weighted image selection for training
199+
--device TEXT cuda device, i.e. 0 or 0,1,2,3 or cpu
200+
--multi-scale vary img-size +/- 50%%
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--single-cls train multi-class data as single-class
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--adam use torch.optim.Adam() optimizer
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--sync-bn use SyncBatchNorm, only available in DDP
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mode
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--local_rank INTEGER DDP parameter, do not modify [default: -1]
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--workers INTEGER maximum number of dataloader workers
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[default: 8]
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--project TEXT save to project/name [default: runs/train]
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--entity TEXT W&B entity
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--name TEXT save to project/name [default: exp]
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--exist-ok existing project/name ok, do not increment
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--quad quad dataloader
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--label-smoothing FLOAT Label smoothing epsilon [default: 0.0]
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--upload_dataset Upload dataset as W&B artifact table
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--bbox_interval INTEGER Set bounding-box image logging interval for
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W&B [default: -1]
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--save_period INTEGER Log model after every "save_period" epoch
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[default: -1]
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--artifact_alias TEXT version of dataset artifact to be used
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[default: latest]
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--freeze INTEGER Freeze layers: backbone of yolov7=50,
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first3=0 1 2 [default: 0]
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--v5-metric assume maximum recall as 1.0 in AP
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calculation
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--help Show this message and exit.
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```
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TODO: more details...
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Example
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```bash
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partinet train step2 --cfg partinet/DynamicDet/cfg/dy-yolov7-step2.yaml --weight /path/to/runs/train/train-step1-300epochs/weights/last.pt --workers 4 --device 0 --batch-size 1 --epochs 10 --img-size 640 640 --adam --data /path/to/cryo_training_all.yaml --hyp partinet/DynamicDet/hyp/hyp.finetune.dynamic.adam.yaml --name train_step2
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partinet train step2 --backbone-detector yolov7 --weight /path/to/runs/train/train-step1-300epochs/weights/last.pt --workers 4 --device 0 --batch-size 1 --epochs 10 --img-size 640 640 --adam --data /path/to/cryo_training_all.yaml --hyp finetune.dynamic.adam --name train_step2
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```
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## Detection
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```bash
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partinet detect --help
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```
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```
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Usage: partinet detect [OPTIONS]
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Options:
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--cfg TEXT model.yaml path [required]
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--weight TEXT model.pt path(s) [required]
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--source TEXT source [default: inference/images]
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--num-classes INTEGER number of classes [default: 80]
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--img-size INTEGER inference size (pixels) [default: 640]
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--conf-thres FLOAT object confidence threshold [default: 0.25]
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--iou-thres FLOAT IOU threshold for NMS [default: 0.45]
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--device TEXT cuda device, i.e. 0 or 0,1,2,3 or cpu
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--view-img display results
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--save-txt save results to *.txt
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--save-conf save confidences in --save-txt labels
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--nosave do not save images/videos
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--classes INTEGER filter by class: --classes 0, or --classes 0
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--classes 2 --classes 3
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--agnostic-nms class-agnostic NMS
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--augment augmented inference
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--project TEXT save results to project/name [default: runs/detect]
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--name TEXT save results to project/name [default: exp]
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--exist-ok existing project/name ok, do not increment
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--dy-thres FLOAT dynamic thres [default: 0.5]
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--help Show this message and exit.
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--backbone-detector [yolov7|yolov7-w6|yolov7x]
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The choice of backbone to be used.
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[default: yolov7]
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--weight TEXT model.pt path(s) [required]
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--source TEXT source [default: inference/images]
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--num-classes INTEGER number of classes [default: 80]
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--img-size INTEGER inference size (pixels) [default: 640]
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--conf-thres FLOAT object confidence threshold [default: 0.25]
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--iou-thres FLOAT IOU threshold for NMS [default: 0.45]
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--device TEXT cuda device, i.e. 0 or 0,1,2,3 or cpu
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--view-img display results
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--save-txt save results to *.txt
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--save-conf save confidences in --save-txt labels
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--nosave do not save images/videos
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--classes INTEGER filter by class: --classes 0, or --classes 0
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--classes 2 --classes 3
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--agnostic-nms class-agnostic NMS
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--augment augmented inference
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--project TEXT save results to project/name [default:
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runs/detect]
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--name TEXT save results to project/name [default: exp]
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--exist-ok existing project/name ok, do not increment
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--dy-thres FLOAT dynamic thres [default: 0.5]
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--help Show this message and exit.
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```
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TODO: more details...

‎partinet/DynamicDet‎

‎partinet/__init__.py‎

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@@ -45,10 +45,10 @@ def train_common_args(f):
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f = click.option('--img-size', nargs=2, type=int, default=[640, 640], help='[train, test] image sizes', show_default=True)(f)
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f = click.option('--batch-size', type=int, default=16, help='total batch size for all GPUs', show_default=True)(f)
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f = click.option('--epochs', type=int, default=300, show_default=True)(f)
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f = click.option('--hyp', type=str, default='hyp/hyp.scratch.p5.yaml', help='hyperparameters path', show_default=True)(f)
48+
f = click.option('--hyp', type=click.Choice(["scratch.p5", "scratch.p6", "finetune.dynamic.adam"]), default='scratch.p5', help='hyperparameters path', show_default=True)(f)
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f = click.option('--data', type=str, default='data/coco.yaml', help='data.yaml path', show_default=True)(f)
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f = click.option('--weight', type=str, help='initial weights path', required=True)(f)
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f = click.option('--cfg', type=str, help='model.yaml path', required=True)(f)
51+
f = click.option('--backbone-detector', type=click.Choice(["yolov7", "yolov7-w6", "yolov7x"], case_sensitive=False), help='The choice of backbone to be used.', default="yolov7", show_default=True)(f)
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return f
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@@ -102,7 +102,7 @@ def step2(**params):
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partinet.DynamicDet.train_step2.main(opt)
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@main.command()
105-
@click.option('--cfg', type=str, help='model.yaml path', required=True)
105+
@click.option('--backbone-detector', type=click.Choice(["yolov7", "yolov7-w6", "yolov7x"], case_sensitive=False), help='The choice of backbone to be used.', default="yolov7", show_default=True)
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@click.option('--weight', type=str, help='model.pt path(s)', required=True)
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@click.option('--source', type=str, default='inference/images', help='source', show_default=True) # file/folder, 0 for webcam
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@click.option('--num-classes', type=int, default=80, help='number of classes', show_default=True)

‎pyproject.toml‎

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@@ -51,6 +51,9 @@ build-backend = "setuptools.build_meta"
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where = ["."]
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include = ["partinet*"]
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[tool.setuptools.package-data]
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"*" = ["dy-*.yaml", "hyp.*.yaml"]
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[tool.setuptools.dynamic]
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version = {attr = "partinet.__version__"}
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