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yolov7.yml
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# train and val data as 1) directory: path/images/, 2) file: path/images.txt, or 3) list: [path1/images/, path2/images/]
train : .datasets/coco/train2017.txt
val : .datasets/coco/val2017.txt
test : .datasets/coco/test-dev2017.txt
device : 0 # cuda device, i.e. 0 or 0,1,2,3 or cpu
# number of classes
nc : 6
# class names
names : [ "Pedestrian", "Cyclist", "Car", "Truck", "Tram", "Tricycle" ]
# coco
# names: [ 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'traffic light',
# 'fire hydrant', 'stop sign', 'parking meter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow',
# 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee',
# 'skis', 'snowboard', 'sports ball', 'kite', 'baseball bat', 'baseball glove', 'skateboard', 'surfboard',
# 'tennis racket', 'bottle', 'wine glass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple',
# 'sandwich', 'orange', 'broccoli', 'carrot', 'hot dog', 'pizza', 'donut', 'cake', 'chair', 'couch',
# 'potted plant', 'bed', 'dining table', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cell phone',
# 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddy bear',
# 'hair drier', 'toothbrush' ]
# saving results to wandb and local dir
wandb : False # save results to weights and bias
project : SSLAD-2D # results will be saved to runs/project/run_name
run_name : yolov7
train :
weights : weights/yolov7/yolov7.pt # model.pt path(s) - choices [yolov7.pt, yolov7x.pt, yolov7-w6.pt, yolov7-e6.pt, yolov7-d6.pt, yolov7-e6e.pt]
cfg : None # model.yaml path
data : data/coco.yaml # data.yaml path
hyp : data/hyp.scratch.p5.yaml # hyperparameters path
epochs : 100 # num of epochs
batch-size : 16 # total batch size for all GPUs
img-size : [640, 640] # [train, test] image sizes
rect : False # rectangular training
resume : False # resume most recent training
nosave : False # only save final checkpoint
notest : False # only test final epoch
noautoanchor : False # disable autoanchor check
evolve : False # evolve hyperparameters
bucket : None # gsutil bucket
cache-images : False # cache images for faster training
image-weights : False # use weighted image selection for training
multi-scale : False # vary img-size +/- 50%%
single-cls : False # train multi-class data as single-class
adam : False # use torch.optim.Adam() optimizer
sync-bn : False # use SyncBatchNorm, only available in DDP mode
local_rank : -1 # DDP parameter, do not modify
workers : 8 # maximum number of dataloader workers
project : runs/train # save to project/name
entity : None # W&B entity
name : exp # save to project/name
exist-ok : False # existing project/name ok, do not increment
quad : False # quad dataloader
linear-lr : False # linear LR
label-smoothing : 0.0 # Label smoothing epsilon
upload_dataset: False # Upload dataset as W&B artifact table
bbox_interval : -1 # Set bounding-box image logging interval for W&B
save_period : -1 # Log model after every "save_period" epoch
artifact_alias: latest # version of dataset artifact to be used
freeze : [0] # Freeze layers: backbone of yolov7=50, first3=0 1 2
v5-metric : False # assume maximum recall as 1.0 in AP calculation
test :
weights : weights/yolov7/yolov7.pt # model.pt path(s) - choices [yolov7.pt, yolov7x.pt, yolov7-w6.pt, yolov7-e6.pt, yolov7-d6.pt, yolov7-e6e.pt]
data : data/coco.yaml # *.data path
batch-size : 32 # size of each image batch
img-size : 640 # inference size (pixels)
conf-thres : 0.001 # object confidence threshold
iou-thres : 0.65 # IOU threshold for NMS
task : val # train, val, test, speed or study
single-cls : False # treat as single-class dataset
augment : False # augmented inference
verbose : False # report mAP by class
save-txt : False # save results to *.txt
save-hybrid : False # save label+prediction hybrid results to *.txt
save-conf : False # save confidences in --save-txt labels
save-json : False # save a cocoapi-compatible JSON results file
no-trace : True # don`t trace model
v5-metric : False # assume maximum recall as 1.0 in AP calculation
inference :
weights : weights/yolov7/yolov7.pt # model.pt path(s) - choices [yolov7.pt, yolov7x.pt, yolov7-w6.pt, yolov7-e6.pt, yolov7-d6.pt, yolov7-e6e.pt]
source : datasets/demo.jpg # source file/folder, 0 for webcam
img_size : 640 # inference size (pixels)
conf_thres : 0.25 # object confidence threshold
iou_thres : 0.45 # IOU threshold for NMS'
view_img : False # display results
save_txt : False # save results to *.txt
save_conf : False # save confidences in --save-txt labels
nosave : False # do not save images/videos
classes : # filter by class: --class 0, or --class 0 2 3
agnostic_nms : None # class-agnostic NMS
augment : False # augmented inference
update : False # update all models
no_trace : True # don`t trace model