yolov8_test/docs/conf.md

Ultralytics YOLO

Default training settings and hyperparameters for medium-augmentation COCO training

Setting the operation type

???+ note "Operation"

| Key    | Value    | Description                                                                                                                                                                                 |
|--------|----------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| task  | `detect` | Set the task via CLI. See Tasks for all supported tasks like - `detect`, `segment`, `classify`.<br> - `init` is a special case that creates a copy of default.yaml configs to the current working dir |
| mode  | `train`  | Set the mode via CLI. It can be `train`, `val`, `predict`   |
| resume  | `False`  | Resume last given task when set to `True`. <br> Resume from a given checkpoint is `model.pt` is passed  |
| model | null     | Set the model. Format can differ for task type. Supports `model_name`, `model.yaml` & `model.pt`                                                                                            |
| data  | null     | Set the data. Format can differ for task type. Supports `data.yaml`, `data_folder`, `dataset_name`|

Training settings

??? note "Train"

Key	Value	Description
device	''	cuda device, i.e. 0 or 0,1,2,3 or cpu. '' selects available cuda 0 device
epochs	100	Number of epochs to train
workers	8	Number of cpu workers used per process. Scales automatically with DDP
batch_size	16	Batch size of the dataloader
imgsz	640	Image size of data in dataloader
optimizer	SGD	Optimizer used. Supported optimizer are: Adam, SGD, RMSProp
single_cls	False	Train on multi-class data as single-class
image_weights	False	Use weighted image selection for training
rect	False	Enable rectangular training
cos_lr	False	Use cosine LR scheduler
lr0	0.01	Initial learning rate
lrf	0.01	Final OneCycleLR learning rate
momentum	0.937	Use as momentum for SGD and beta1 for Adam
weight_decay	0.0005	Optimizer weight decay
warmup_epochs	3.0	Warmup epochs. Fractions are ok.
warmup_momentum	0.8	Warmup initial momentum
warmup_bias_lr	0.1	Warmup initial bias lr
box	0.05	Box loss gain
cls	0.5	cls loss gain
cls_pw	1.0	cls BCELoss positive_weight
obj	1.0	bj loss gain (scale with pixels)
obj_pw	1.0	obj BCELoss positive_weight
iou_t	0.20	IOU training threshold
anchor_t	4.0	anchor-multiple threshold
fl_gamma	0.0	focal loss gamma
label_smoothing	0.0
nbs	64	nominal batch size
overlap_mask	True	Segmentation: Use mask overlapping during training
mask_ratio	4	Segmentation: Set mask downsampling
dropout	False	Classification: Use dropout while training

Prediction Settings

??? note "Prediction"

Key	Value	Description
source	ultralytics/assets	Input source. Accepts image, folder, video, url
view_img	False	View the prediction images
save_txt	False	Save the results in a txt file
save_conf	False	Save the condidence scores
save_crop	Fasle
hide_labels	False	Hide the labels
hide_conf	False	Hide the confidence scores
vid_stride	False	Input video frame-rate stride
line_thickness	3	Bounding-box thickness (pixels)
visualize	False	Visualize model features
augment	False	Augmented inference
agnostic_nms	False	Class-agnostic NMS
retina_masks	False	Segmentation: High resolution masks

Validation settings

??? note "Validation"

Key	Value	Description
noval	False	???
save_json	False
save_hybrid	False
conf_thres	0.001	Confidence threshold
iou_thres	0.6	IoU threshold
max_det	300	Maximum number of detections
half	True	Use .half() mode.
dnn	False	Use OpenCV DNN for ONNX inference
plots	False

Augmentation settings

??? note "Augmentation"

| hsv_h       | 0.015 | Image HSV-Hue augmentation (fraction)           |
|-------------|-------|-------------------------------------------------|
| hsv_s       | 0.7   | Image HSV-Saturation augmentation (fraction)    |
| hsv_v       | 0.4   | Image HSV-Value augmentation (fraction)         |
| degrees     | 0.0   | Image rotation (+/- deg)                        |
| translate   | 0.1   | Image translation (+/- fraction)                |
| scale       | 0.5   | Image scale (+/- gain)                          |
| shear       | 0.0   | Image shear (+/- deg)                           |
| perspective | 0.0   | Image perspective (+/- fraction), range 0-0.001 |
| flipud      | 0.0   | Image flip up-down (probability)                |
| fliplr      | 0.5   | Image flip left-right (probability)             |
| mosaic      | 1.0   | Image mosaic (probability)                      |
| mixup       | 0.0   | Image mixup (probability)                       |
| copy_paste  | 0.0   | Segment copy-paste (probability)                |

Logging, checkpoints, plotting and file management

??? note "files"

Key	Value	Description
project:	'runs'	The project name
name:	'exp'	The run name. exp gets automatically incremented if not specified, i.e, exp, exp2 ...
exist_ok:	False	???
plots	False	Validation: Save plots while validation
nosave	False	Don't save any plots, models or files