## 运行YOLOv3图像检测样例 ### 一:准备环境 请您在环境中安装1.7或以上版本的Paddle,具体的安装方式请参照[飞桨官方页面](https://www.paddlepaddle.org.cn/)的指示方式。 ### 二:下载模型以及测试数据 1)**获取预测模型** 点击[链接](https://paddle-inference-dist.cdn.bcebos.com/PaddleLite/yolov3_infer.tar.gz)下载模型, 该模型在imagenet数据集训练得到的,如果你想获取更多的**模型训练信息**,请访问[这里](https://github.com/PaddlePaddle/PaddleDetection)。 2)**获取预测样例图片** 下载[样例图片](https://paddle-inference-dist.bj.bcebos.com/inference_demo/images/kite.jpg)。 图片如下:
### 三:运行预测 文件`utils.py`包含了图像的预处理等帮助函数。 文件`infer_yolov3.py` 包含了创建predictor,读取示例图片,预测,获取输出的等功能。 运行: ``` python infer_yolov3.py --model_file=./yolov3_infer/__model__ --params_file=./yolov3_infer/__params__ --use_gpu=1 ``` 输出结果如下所示: ``` category id is 0.0, bbox is [ 98.47467 471.34283 120.73273 578.5184 ] category id is 0.0, bbox is [ 51.752716 415.51324 73.18762 515.24005 ] category id is 0.0, bbox is [ 37.176304 343.378 46.64221 380.92963 ] category id is 0.0, bbox is [155.78638 328.0806 159.5393 339.37192] category id is 0.0, bbox is [233.86328 339.96912 239.35403 355.3322 ] category id is 0.0, bbox is [ 16.212902 344.42365 25.193722 377.97137 ] category id is 0.0, bbox is [ 10.583471 356.67862 14.9261 372.8137 ] category id is 0.0, bbox is [ 79.76479 364.19492 86.07656 385.64255] category id is 0.0, bbox is [312.8938 311.9908 314.58527 316.60056] category id is 33.0, bbox is [266.97925 51.70044 299.45105 99.996414] category id is 33.0, bbox is [210.45593 229.92128 217.77551 240.97136] category id is 33.0, bbox is [125.36278 159.80171 135.49306 189.8976 ] category id is 33.0, bbox is [486.9354 266.164 494.4437 283.84637] category id is 33.0, bbox is [259.01584 232.23044 270.69266 248.58704] category id is 33.0, bbox is [135.60567 254.57668 144.96178 276.9275 ] category id is 33.0, bbox is [341.91315 255.44394 345.0335 262.3398 ] ```
### 相关链接 - [Paddle Inference使用Quick Start!]() - [Paddle Inference Python Api使用]()