fr/tasks/detect/

[giscus[bot]]

fr/tasks/detect/

Découvrez la détection d'objets avec YOLO11. Explorez les modèles pré-entraînés, l'entraînement, la validation, la prédiction et les détails de l'exportation pour une reconnaissance efficace des objets.

https://docs.ultralytics.com/fr/tasks/detect/

[RoaminS]

Hi guy thanks for your work. I would share with you this => I train the yolo11l.pt with this command on coco with rtx3060 & i obtain:
result epoch 32:
0.54448 => metrics/maP50-95(B)
0.71356 => metrics/maP50(B)

Paramètre training:
task: detect
mode: train
model: yolo11l.pt
data: coco.yaml
epochs: 100
time: null
patience: 100
batch: 6
imgsz: 1024
save: true
save_period: -1
cache: false
device: null
workers: 8
project: null
name: 1024_stable_l2
exist_ok: false
pretrained: true
optimizer: AdamW
verbose: true
seed: 0
deterministic: true
single_cls: false
rect: false
cos_lr: true
close_mosaic: 20
resume: false
amp: true
fraction: 1.0
profile: false
freeze: null
multi_scale: false
overlap_mask: true
mask_ratio: 4
dropout: 0.0
val: true
split: val
save_json: false
conf: null
iou: 0.7
max_det: 300
half: false
dnn: false
plots: true
source: null
vid_stride: 1
stream_buffer: false
visualize: false
augment: false
agnostic_nms: false
classes: null
retina_masks: false
embed: null
show: false
save_frames: false
save_txt: false
save_conf: false
save_crop: false
show_labels: true
show_conf: true
show_boxes: true
line_width: null
format: torchscript
keras: false
optimize: false
int8: false
dynamic: false
simplify: true
opset: null
workspace: null
nms: false
lr0: 1.0e-05
lrf: 0.01
momentum: 0.937
weight_decay: 0.0005
warmup_epochs: 5
warmup_momentum: 0.8
warmup_bias_lr: 0.1
box: 7.5
cls: 0.5
dfl: 1.5
pose: 12.0
kobj: 1.0
nbs: 64
hsv_h: 0.015
hsv_s: 0.7
hsv_v: 0.4
degrees: 5
translate: 0.05
scale: 0.2
shear: 1.0
perspective: 0.0
flipud: 0.1
fliplr: 0.5
bgr: 0.0
mosaic: 1.0
mixup: 0.0
cutmix: 0.0
copy_paste: 0.0
copy_paste_mode: flip
auto_augment: randaugment
erasing: 0.4
cfg: null
tracker: botsort.yaml
save_dir: runs/detect/1024_stable_l2

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