Image Segmentation
ultralytics
PyTorch
semantic-segmentation
aerial-imagery
drone
vdd
yolo26
computer-vision
Eval Results (legacy)
Instructions to use dronefreak/vdd-yolo26n-sem with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ultralytics
How to use dronefreak/vdd-yolo26n-sem with ultralytics:
# Couldn't find a valid YOLO version tag. # Replace XX with the correct version. from ultralytics import YOLOvXX model = YOLOvXX.from_pretrained("dronefreak/vdd-yolo26n-sem") source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - Notebooks
- Google Colab
- Kaggle
File size: 1,767 Bytes
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mode: train
model: yolo26n-sem.pt
data: /home/saumya.saksena/projects/CABiNet/configs/dataset/vdd_yolo.yaml
epochs: 300
time: null
patience: 50
batch: 4
imgsz: 1024
save: true
save_period: 50
cache: false
device: '0'
workers: 8
project: /home/saumya.saksena/projects/CABiNet/experiments/vdd_yolo
name: yolo26n
exist_ok: false
pretrained: true
cls_remap: true
optimizer: SGD
verbose: true
seed: 0
deterministic: true
single_cls: false
rect: false
cos_lr: true
close_mosaic: 15
resume: false
amp: true
fraction: 1.0
profile: false
freeze: null
multi_scale: 0.0
compile: 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
quantize: null
dnn: false
plots: true
end2end: null
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
dynamic: false
simplify: true
opset: null
workspace: null
nms: false
lr0: 0.01
lrf: 0.01
momentum: 0.937
weight_decay: 0.0005
warmup_epochs: 3.0
warmup_momentum: 0.8
warmup_bias_lr: 0.1
distill_model: null
dis: 6.0
box: 7.5
cls: 0.5
cls_pw: 0.5
dfl: 1.5
pose: 12.0
kobj: 1.0
rle: 1.0
angle: 1.0
nbs: 64
hsv_h: 0.01
hsv_s: 0.4
hsv_v: 0.3
degrees: 10.0
translate: 0.05
scale: 0.3
shear: 0.0
perspective: 0.0
flipud: 0.2
fliplr: 0.5
bgr: 0.0
mosaic: 0.8
mixup: 0.15
cutmix: 0.0
copy_paste: 0.15
copy_paste_mode: flip
auto_augment: randaugment
erasing: 0.4
cfg: null
tracker: tracktrack.yaml
save_dir: /home/saumya.saksena/projects/CABiNet/experiments/vdd_yolo/yolo26n
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