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small fix of yolov5

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wang-xinyu 2021-04-23 08:34:10 +00:00
parent 501160d262
commit e63a6a874f
3 changed files with 7 additions and 8 deletions
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10
yolov5/README.md
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@ -6,11 +6,11 @@ The Pytorch implementation is [ultralytics/yolov5](https://github.com/ultralytic
Currently, we support yolov5 v1.0(yolov5s only), v2.0, v3.0, v3.1 and v4.0.
- For yolov5 v4.0, download .pt from [yolov5 release v4.0](https://github.com/ultralytics/yolov5/releases/tag/v4.0), `git clone -b v4.0 https://github.com/ultralytics/yolov5.git` and `git clone https://github.com/wang-xinyu/tensorrtx.git`.
- For yolov5 v3.1, download .pt from [yolov5 release v3.1](https://github.com/ultralytics/yolov5/releases/tag/v3.1), `git clone -b v3.1 https://github.com/ultralytics/yolov5.git` and `git clone -b yolov5-v3.1 https://github.com/wang-xinyu/tensorrtx.git`.
- For yolov5 v3.0, download .pt from [yolov5 release v3.0](https://github.com/ultralytics/yolov5/releases/tag/v3.0), `git clone -b v3.0 https://github.com/ultralytics/yolov5.git` and `git clone -b yolov5-v3.0 https://github.com/wang-xinyu/tensorrtx.git`.
- For yolov5 v2.0, download .pt from [yolov5 release v2.0](https://github.com/ultralytics/yolov5/releases/tag/v2.0), `git clone -b v2.0 https://github.com/ultralytics/yolov5.git` and `git clone -b yolov5-v2.0 https://github.com/wang-xinyu/tensorrtx.git`.
- For yolov5 v1.0, download .pt from [yolov5 release v1.0](https://github.com/ultralytics/yolov5/releases/tag/v1.0), `git clone -b v1.0 https://github.com/ultralytics/yolov5.git` and `git clone -b yolov5-v1.0 https://github.com/wang-xinyu/tensorrtx.git`.
- For yolov5 v4.0, download .pt from [yolov5 release v4.0](https://github.com/ultralytics/yolov5/releases/tag/v4.0), `git clone -b v4.0 https://github.com/ultralytics/yolov5.git` and `git clone https://github.com/wang-xinyu/tensorrtx.git`, then follow how-to-run in current page.
- For yolov5 v3.1, download .pt from [yolov5 release v3.1](https://github.com/ultralytics/yolov5/releases/tag/v3.1), `git clone -b v3.1 https://github.com/ultralytics/yolov5.git` and `git clone -b yolov5-v3.1 https://github.com/wang-xinyu/tensorrtx.git`, then follow how-to-run in [tensorrtx/yolov5-v3.1](https://github.com/wang-xinyu/tensorrtx/tree/yolov5-v3.1/yolov5).
- For yolov5 v3.0, download .pt from [yolov5 release v3.0](https://github.com/ultralytics/yolov5/releases/tag/v3.0), `git clone -b v3.0 https://github.com/ultralytics/yolov5.git` and `git clone -b yolov5-v3.0 https://github.com/wang-xinyu/tensorrtx.git`, then follow how-to-run in [tensorrtx/yolov5-v3.0](https://github.com/wang-xinyu/tensorrtx/tree/yolov5-v3.0/yolov5).
- For yolov5 v2.0, download .pt from [yolov5 release v2.0](https://github.com/ultralytics/yolov5/releases/tag/v2.0), `git clone -b v2.0 https://github.com/ultralytics/yolov5.git` and `git clone -b yolov5-v2.0 https://github.com/wang-xinyu/tensorrtx.git`, then follow how-to-run in [tensorrtx/yolov5-v2.0](https://github.com/wang-xinyu/tensorrtx/tree/yolov5-v2.0/yolov5).
- For yolov5 v1.0, download .pt from [yolov5 release v1.0](https://github.com/ultralytics/yolov5/releases/tag/v1.0), `git clone -b v1.0 https://github.com/ultralytics/yolov5.git` and `git clone -b yolov5-v1.0 https://github.com/wang-xinyu/tensorrtx.git`, then follow how-to-run in [tensorrtx/yolov5-v1.0](https://github.com/wang-xinyu/tensorrtx/tree/yolov5-v1.0/yolov5).
## Config

4
yolov5/yololayer.h
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@ -17,8 +17,8 @@ namespace Yolo
};
static constexpr int MAX_OUTPUT_BBOX_COUNT = 1000;
static constexpr int CLASS_NUM = 80;
static constexpr int INPUT_H = 608;
static constexpr int INPUT_W = 608;
static constexpr int INPUT_H = 640; // yolov5's input height and width must be divisible by 32.
static constexpr int INPUT_W = 640;
static constexpr int LOCATIONS = 4;
struct alignas(float) Detection {

1
yolov5/yolov5.cpp
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@ -45,7 +45,6 @@ ICudaEngine* build_engine(unsigned int maxBatchSize, IBuilder* builder, IBuilder
assert(data);
std::map<std::string, Weights> weightMap = loadWeights(wts_name);
Weights emptywts{ DataType::kFLOAT, nullptr, 0 };
/* ------ yolov5 backbone------ */
auto focus0 = focus(network, weightMap, *data, 3, get_width(64, gw), 3, "model.0");