Smoke100 Computer Vision Project from roboflow
$ docker compose exec dethub python tools/image_demo.py configs/projects/smoke100/demo/M_03811_png.rf.dffeb0ed03627dbbc06f9a3ce8da5de7.jpg configs/projects/smoke100/yolox/yolox_s_smoke100.py --weights https://github.com/okotaku/dethub-weights/releases/download/v0.1.1smoke100/yolox_s_smoke100-670611b4.pth --out-dir configs/projects/smoke100/demo/result
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Download data from roboflow
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Unzip the files as follows
data/findfallenpeople
├── train
├── valid
└── test
Set env variables
$ export DATA_DIR=/path/to/data
Start a docker container
$ docker compose up -d dethub
Run train
# preprocess
$ docker compose exec dethub python tools/dataset_converters/prepare_roboflow.py smoke100
# single gpu
$ docker compose exec dethub mim train mmdet configs/projects/smoke100/yolox/yolox_s_smoke100.py
# multi gpus
$ docker compose exec dethub mim train mmdet configs/projects/smoke100/yolox/yolox_s_smoke100.py --gpus 2 --launcher pytorch
@misc{ smoke100-uwe4t_dataset,
title = { Smoke100 Dataset },
type = { Open Source Dataset },
author = { Smoke Detection },
howpublished = { \url{ https://universe.roboflow.com/smoke-detection/smoke100-uwe4t } },
url = { https://universe.roboflow.com/smoke-detection/smoke100-uwe4t },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2022 },
month = { jun },
note = { visited on 2022-12-13 },
}