python train.py --weights model/weights/yolov8n_dict_converted.pt --train-config model/config/training/fine_tune.yaml --model-config model/config/models/yolov8n.yaml --dataset model/config/datasets/kitty_infer.yaml --save --dataset-mode train -d cuda

python inference.py --weights model/weights/ours_1000_e5_pre_kitti_9000_e10.pt --config model/config/models/yolov8l.yaml --dataset model/config/datasets/ours_train.yaml --dataset-mode test -d cuda --save

python convert_yolo_weights.py --model yolov8l.pt --dict --config model/config/models/yolov8l.yaml --output model/weights/yolov8l_dict_converted.pt

python scripts/generate_depth_labels.py --images_dir C:\dataset\ours\train\images --labels_dir C:\dataset\ours\train\labels --output_images_dir C:\dataset\ours\depth\train\images --output_labels_dir C:\dataset\ours\depth\train\labels

python scripts/generate_depth_labels.py --images_dir C:\dataset\ours\test\images --labels_dir C:\dataset\ours\test\labels --output_images_dir C:\dataset\ours\depth\test\images --output_labels_dir C:\dataset\ours\depth\test\labels

ours

generate depth labels

python scripts/generate_depth_labels.py --images_dir C:\dataset\ours\train\images --labels_dir C:\dataset\ours\train\labels --output_images_dir C:\dataset\ours\depth\train\images --output_labels_dir C:\dataset\ours\depth\train\labels

python scripts/generate_depth_labels.py --images_dir C:\dataset\ours\test\images --labels_dir C:\dataset\ours\test\labels --output_images_dir C:\dataset\ours\depth\test\images --output_labels_dir C:\dataset\ours\depth\test\labels

train finetune on kitti

python train.py --weights model/weights/kitti_9000_e10.pt --pt --train-config model/config/training/fine_tune.yaml --model-config model/config/models/yolov8l.yaml --dataset model/config/datasets/ours_train.yaml --save --dataset-mode train -d cuda

generate inference results on test set

python inference.py --weights model/weights/ours_1000_e15_pre_kitti_9000_e10.pt --config model/config/models/yolov8l.yaml --dataset model/config/datasets/ours_train.yaml --dataset-mode test -d cuda --save

generate inference results on train set

python inference.py --weights model/weights/ours_1000_e15_pre_kitti_9000_e10.pt --config model/config/models/yolov8l.yaml --dataset model/config/datasets/ours_train.yaml --dataset-mode val -d cuda --save

parking

generate depth labels

python scripts/generate_depth_labels_parking.py --images_dir C:\dataset\parking\og\images --labels_dir C:\dataset\parking\og\labels --output_images_dir C:\dataset\parking\depth\images --output_labels_dir C:\dataset\parking\depth\labels

generate inference on parking set

python inference.py --weights model/weights/ours_1000_e15_pre_kitti_9000_e10.pt --config model/config/models/yolov8l.yaml --dataset model/config/datasets/parking.yaml --dataset-mode test -d cuda --save

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