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