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@ -123,26 +123,26 @@ Intel|i7-8700(X86-cpu)|Linux(amd64)|ncnn|4.51ms|4.33ms
```
### Build the training .yaml configuration file
* Reference./configs/coco.yaml
```
DATASET:
TRAIN: "/home/qiuqiu/Desktop/coco2017/train2017.txt" # Train dataset path .txt file
VAL: "/home/qiuqiu/Desktop/coco2017/val2017.txt" # Val dataset path .txt file
NAMES: "dataset/coco128/coco.names" # .names category label file
MODEL:
NC: 80 # Number of detection categories
INPUT_WIDTH: 352 # The width of the model input image
INPUT_HEIGHT: 352 # The height of the model input image
TRAIN:
LR: 0.001 # Train learn rate
THRESH: 0.25 # ？？？？
WARMUP: true # Trun on warm up
BATCH_SIZE: 64 # Batch size
END_EPOCH: 350 # Train epichs
MILESTIONES: # Declining learning rate steps
- 150
- 250
- 300
```
```
DATASET:
TRAIN: "/home/qiuqiu/Desktop/coco2017/train2017.txt" # Train dataset path .txt file
VAL: "/home/qiuqiu/Desktop/coco2017/val2017.txt" # Val dataset path .txt file
NAMES: "dataset/coco128/coco.names" # .names category label file
MODEL:
NC: 80 # Number of detection categories
INPUT_WIDTH: 352 # The width of the model input image
INPUT_HEIGHT: 352 # The height of the model input image
TRAIN:
LR: 0.001 # Train learn rate
THRESH: 0.25 # ？？？？
WARMUP: true # Trun on warm up
BATCH_SIZE: 64 # Batch size
END_EPOCH: 350 # Train epichs
MILESTIONES: # Declining learning rate steps
- 150
- 250
- 300
```
### Train
* Perform training tasks
```
@ -203,12 +203,15 @@ TRAIN:
pip install onnx-runtime
python3 runtime.py
```
@misc{=FastestDet,
title={FastestDet: Ultra lightweight anchor-free real-time object detection algorithm.},
author={xuehao.ma},
howpublished = {\url{https://github.com/dog-qiuqiu/FastestDet}},
year={2022}
}
```
# Citation
* If you find this project useful in your research, please consider cite:
```
@misc{=FastestDet,
title={FastestDet: Ultra lightweight anchor-free real-time object detection algorithm.},
author={xuehao.ma},
howpublished = {\url{https://github.com/dog-qiuqiu/FastestDet}},
year={2022}
}
```
# Reference
* https://github.com/Tencent/ncnn