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- // Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
- //
- // Licensed under the Apache License, Version 2.0 (the "License");
- // you may not use this file except in compliance with the License.
- // You may obtain a copy of the License at
- //
- // http://www.apache.org/licenses/LICENSE-2.0
- //
- // Unless required by applicable law or agreed to in writing, software
- // distributed under the License is distributed on an "AS IS" BASIS,
- // WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- // See the License for the specific language governing permissions and
- // limitations under the License.
- // reference from https://github.com/RangiLyu/nanodet/tree/main/demo_mnn
- #ifndef __PicoDet_H__
- #define __PicoDet_H__
- #pragma once
- #include "Interpreter.hpp"
- #include <algorithm>
- #include <chrono>
- #include <iostream>
- #include <memory>
- #include <opencv2/opencv.hpp>
- #include <string>
- #include <vector>
- #include "ImageProcess.hpp"
- #include "MNNDefine.h"
- #include "Tensor.hpp"
- typedef struct HeadInfo_ {
- std::string cls_layer;
- std::string dis_layer;
- int stride;
- } HeadInfo;
- typedef struct BoxInfo_ {
- float x1;
- float y1;
- float x2;
- float y2;
- float score;
- int label;
- } BoxInfo;
- class PicoDet {
- public:
- PicoDet(const std::string &mnn_path,
- int input_width,
- int input_length,
- int num_thread_ = 4,
- float score_threshold_ = 0.5,
- float nms_threshold_ = 0.3);
- ~PicoDet();
- int detect(cv::Mat &img, std::vector<BoxInfo> &result_list);
- std::string get_label_str(int label);
- private:
- void decode_infer(MNN::Tensor *cls_pred,
- MNN::Tensor *dis_pred,
- int stride,
- float threshold,
- std::vector<std::vector<BoxInfo>> &results);
- BoxInfo disPred2Bbox(
- const float *&dfl_det, int label, float score, int x, int y, int stride);
- void nms(std::vector<BoxInfo> &input_boxes, float NMS_THRESH);
- private:
- std::shared_ptr<MNN::Interpreter> PicoDet_interpreter;
- MNN::Session *PicoDet_session = nullptr;
- MNN::Tensor *input_tensor = nullptr;
- int num_thread;
- int image_w;
- int image_h;
- int in_w = 320;
- int in_h = 320;
- float score_threshold;
- float nms_threshold;
- const float mean_vals[3] = {103.53f, 116.28f, 123.675f};
- const float norm_vals[3] = {0.017429f, 0.017507f, 0.017125f};
- const int num_class = 80;
- const int reg_max = 7;
- std::vector<HeadInfo> heads_info{
- // cls_pred|dis_pred|stride
- {"save_infer_model/scale_0.tmp_1", "save_infer_model/scale_4.tmp_1", 8},
- {"save_infer_model/scale_1.tmp_1", "save_infer_model/scale_5.tmp_1", 16},
- {"save_infer_model/scale_2.tmp_1", "save_infer_model/scale_6.tmp_1", 32},
- {"save_infer_model/scale_3.tmp_1", "save_infer_model/scale_7.tmp_1", 64},
- };
- std::vector<std::string> labels{
- "person", "bicycle", "car",
- "motorcycle", "airplane", "bus",
- "train", "truck", "boat",
- "traffic light", "fire hydrant", "stop sign",
- "parking meter", "bench", "bird",
- "cat", "dog", "horse",
- "sheep", "cow", "elephant",
- "bear", "zebra", "giraffe",
- "backpack", "umbrella", "handbag",
- "tie", "suitcase", "frisbee",
- "skis", "snowboard", "sports ball",
- "kite", "baseball bat", "baseball glove",
- "skateboard", "surfboard", "tennis racket",
- "bottle", "wine glass", "cup",
- "fork", "knife", "spoon",
- "bowl", "banana", "apple",
- "sandwich", "orange", "broccoli",
- "carrot", "hot dog", "pizza",
- "donut", "cake", "chair",
- "couch", "potted plant", "bed",
- "dining table", "toilet", "tv",
- "laptop", "mouse", "remote",
- "keyboard", "cell phone", "microwave",
- "oven", "toaster", "sink",
- "refrigerator", "book", "clock",
- "vase", "scissors", "teddy bear",
- "hair drier", "toothbrush"};
- };
- template <typename _Tp>
- int activation_function_softmax(const _Tp *src, _Tp *dst, int length);
- inline float fast_exp(float x);
- inline float sigmoid(float x);
- #endif
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