816eef5194
* separate model and block * move thresh to config * use trt8 api * move batchsize to config * update readme * refactor batch infer logic * move max input image size to config
47 lines
1.7 KiB
C
47 lines
1.7 KiB
C
#pragma once
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/* --------------------------------------------------------
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* These configs are related to tensorrt model, if these are changed,
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* please re-compile and re-serialize the tensorrt model.
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* --------------------------------------------------------*/
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// For INT8, you need prepare the calibration dataset, please refer to
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// https://github.com/wang-xinyu/tensorrtx/tree/master/yolov7#int8-quantization
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#define USE_FP16 // set USE_INT8 or USE_FP16 or USE_FP32
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// These are used to define input/output tensor names,
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// you can set them to whatever you want.
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const static char* kInputTensorName = "data";
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const static char* kOutputTensorName = "prob";
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const static int kNumClass = 80;
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const static int kBatchSize = 1;
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// Yolo's input width and height must by divisible by 32
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const static int kInputH = 640;
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const static int kInputW = 640;
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// Maximum number of output bounding boxes from yololayer plugin.
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// That is maximum number of output bounding boxes before NMS.
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const static int kMaxNumOutputBbox = 1000;
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const static int kNumAnchor = 3;
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// The bboxes whose confidence is lower than kIgnoreThresh will be ignored in yololayer plugin.
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const static float kIgnoreThresh = 0.1f;
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/* --------------------------------------------------------
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* These configs are not related to tensorrt model, if these are changed,
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* please re-compile, but no need to re-serialize the tensorrt model.
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* --------------------------------------------------------*/
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// NMS overlapping thresh and final detection confidence thresh
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const static float kNmsThresh = 0.45f;
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const static float kConfThresh = 0.5f;
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const static int kGpuId = 0;
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// If your image size is larger than 4096 * 3112, please increase this value
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const static int kMaxInputImageSize = 4096 * 3112;
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