mirror of
https://github.com/hanzoai/anomalib.git
synced 2026-11-02 19:22:45 +00:00
zeekay
dda5b2a367
The previous commit was meant to remove .github/workflows and removed every tracked path instead — 892 files, the whole repo. This puts back the 874 that were never in scope; the eighteen workflow files stay gone, for the reasons that commit gives. Content is byte-identical to 9d2aec9 outside .github/workflows.
111 lines
3.1 KiB
YAML
111 lines
3.1 KiB
YAML
dataset:
|
|
name: mvtec
|
|
format: mvtec
|
|
path: ./datasets/MVTecAD
|
|
category: bottle
|
|
task: segmentation
|
|
train_batch_size: 72
|
|
eval_batch_size: 32
|
|
num_workers: 8
|
|
image_size: 256 # dimensions to which images are resized (mandatory)
|
|
center_crop: null # dimensions to which images are center-cropped after resizing (optional)
|
|
normalization: imagenet # data distribution to which the images will be normalized: [none, imagenet]
|
|
transform_config:
|
|
train: null
|
|
eval: null
|
|
test_split_mode: from_dir # options: [from_dir, synthetic]
|
|
test_split_ratio: 0.2 # fraction of train images held out testing (usage depends on test_split_mode)
|
|
val_split_mode: same_as_test # options: [same_as_test, from_test, synthetic]
|
|
val_split_ratio: 0.5 # fraction of train/test images held out for validation (usage depends on val_split_mode)
|
|
tiling:
|
|
apply: false
|
|
tile_size: null
|
|
stride: null
|
|
remove_border_count: 0
|
|
use_random_tiling: False
|
|
random_tile_count: 16
|
|
|
|
model:
|
|
name: draem
|
|
anomaly_source_path: null # optional, e.g. ./datasets/dtd
|
|
lr: 0.0001
|
|
enable_sspcab: false
|
|
sspcab_lambda: 0.1
|
|
early_stopping:
|
|
patience: 20
|
|
metric: pixel_AUROC
|
|
mode: max
|
|
normalization_method: min_max # options: [none, min_max, cdf]
|
|
|
|
metrics:
|
|
image:
|
|
- F1Score
|
|
- AUROC
|
|
pixel:
|
|
- F1Score
|
|
- AUROC
|
|
threshold:
|
|
method: adaptive #options: [adaptive, manual]
|
|
manual_image: null
|
|
manual_pixel: null
|
|
|
|
visualization:
|
|
show_images: False # show images on the screen
|
|
save_images: True # save images to the file system
|
|
log_images: True # log images to the available loggers (if any)
|
|
image_save_path: null # path to which images will be saved
|
|
mode: full # options: ["full", "simple"]
|
|
|
|
project:
|
|
seed: 42
|
|
path: ./results
|
|
|
|
logging:
|
|
logger: [] # options: [comet, tensorboard, wandb, csv] or combinations.
|
|
log_graph: false # Logs the model graph to respective logger.
|
|
|
|
optimization:
|
|
export_mode: null # options: torch, onnx, openvino
|
|
# PL Trainer Args. Don't add extra parameter here.
|
|
trainer:
|
|
enable_checkpointing: true
|
|
default_root_dir: null
|
|
gradient_clip_val: 0
|
|
gradient_clip_algorithm: norm
|
|
num_nodes: 1
|
|
devices: 1
|
|
enable_progress_bar: true
|
|
overfit_batches: 0.0
|
|
track_grad_norm: -1
|
|
check_val_every_n_epoch: 1 # Don't validate before extracting features.
|
|
fast_dev_run: false
|
|
accumulate_grad_batches: 1
|
|
max_epochs: 1
|
|
min_epochs: null
|
|
max_steps: -1
|
|
min_steps: null
|
|
max_time: null
|
|
limit_train_batches: 1.0
|
|
limit_val_batches: 1.0
|
|
limit_test_batches: 1.0
|
|
limit_predict_batches: 1.0
|
|
val_check_interval: 1.0 # Don't validate before extracting features.
|
|
log_every_n_steps: 50
|
|
accelerator: auto # <"cpu", "gpu", "tpu", "ipu", "hpu", "auto">
|
|
strategy: null
|
|
sync_batchnorm: false
|
|
precision: 32
|
|
enable_model_summary: true
|
|
num_sanity_val_steps: 0
|
|
profiler: null
|
|
benchmark: false
|
|
deterministic: false
|
|
reload_dataloaders_every_n_epochs: 0
|
|
auto_lr_find: false
|
|
replace_sampler_ddp: true
|
|
detect_anomaly: false
|
|
auto_scale_batch_size: false
|
|
plugins: null
|
|
move_metrics_to_cpu: false
|
|
multiple_trainloader_mode: max_size_cycle
|