add nanodet example

examples/CMakeLists.txt

@@ -51,4 +51,5 @@ else()
     ncnn_add_example(simplepose)
     ncnn_add_example(retinaface)
     ncnn_add_example(yolact)
+    ncnn_add_example(nanodet)
 endif()

examples/nanodet.cpp

+// Tencent is pleased to support the open source community by making ncnn available.
+//
+// Copyright (C) 2020 THL A29 Limited, a Tencent company. All rights reserved.
+//
+// Licensed under the BSD 3-Clause License (the "License"); you may not use this file except
+// in compliance with the License. You may obtain a copy of the License at
+//
+// https://opensource.org/licenses/BSD-3-Clause
+//
+// 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.
+
+#include "net.h"
+
+#include <opencv2/core/core.hpp>
+#include <opencv2/highgui/highgui.hpp>
+#include <opencv2/imgproc/imgproc.hpp>
+#include <stdlib.h>
+#include <float.h>
+#include <stdio.h>
+#include <vector>
+
+struct Object
+{
+    cv::Rect_<float> rect;
+    int label;
+    float prob;
+};
+
+static inline float intersection_area(const Object& a, const Object& b)
+{
+    cv::Rect_<float> inter = a.rect & b.rect;
+    return inter.area();
+}
+
+static void qsort_descent_inplace(std::vector<Object>& faceobjects, int left, int right)
+{
+    int i = left;
+    int j = right;
+    float p = faceobjects[(left + right) / 2].prob;
+
+    while (i <= j)
+    {
+        while (faceobjects[i].prob > p)
+            i++;
+
+        while (faceobjects[j].prob < p)
+            j--;
+
+        if (i <= j)
+        {
+            // swap
+            std::swap(faceobjects[i], faceobjects[j]);
+
+            i++;
+            j--;
+        }
+    }
+
+    #pragma omp parallel sections
+    {
+        #pragma omp section
+        {
+            if (left < j) qsort_descent_inplace(faceobjects, left, j);
+        }
+        #pragma omp section
+        {
+            if (i < right) qsort_descent_inplace(faceobjects, i, right);
+        }
+    }
+}
+
+static void qsort_descent_inplace(std::vector<Object>& faceobjects)
+{
+    if (faceobjects.empty())
+        return;
+
+    qsort_descent_inplace(faceobjects, 0, faceobjects.size() - 1);
+}
+
+static void nms_sorted_bboxes(const std::vector<Object>& faceobjects, std::vector<int>& picked, float nms_threshold)
+{
+    picked.clear();
+
+    const int n = faceobjects.size();
+
+    std::vector<float> areas(n);
+    for (int i = 0; i < n; i++)
+    {
+        areas[i] = faceobjects[i].rect.width * faceobjects[i].rect.height;
+    }
+
+    for (int i = 0; i < n; i++)
+    {
+        const Object& a = faceobjects[i];
+
+        int keep = 1;
+        for (int j = 0; j < (int)picked.size(); j++)
+        {
+            const Object& b = faceobjects[picked[j]];
+
+            // intersection over union
+            float inter_area = intersection_area(a, b);
+            float union_area = areas[i] + areas[picked[j]] - inter_area;
+            // float IoU = inter_area / union_area
+            if (inter_area / union_area > nms_threshold)
+                keep = 0;
+        }
+
+        if (keep)
+            picked.push_back(i);
+    }
+}
+
+static void generate_proposals(const ncnn::Mat& cls_pred, const ncnn::Mat& dis_pred, int stride, const ncnn::Mat& in_pad, float prob_threshold, std::vector<Object>& objects)
+{
+    const int num_grid = cls_pred.h;
+
+    int num_grid_x;
+    int num_grid_y;
+    if (in_pad.w > in_pad.h)
+    {
+        num_grid_x = in_pad.w / stride;
+        num_grid_y = num_grid / num_grid_x;
+    }
+    else
+    {
+        num_grid_y = in_pad.h / stride;
+        num_grid_x = num_grid / num_grid_y;
+    }
+
+    const int num_class = cls_pred.w;
+    const int reg_max_1 = dis_pred.w / 4;
+
+    for (int i = 0; i < num_grid_y; i++)
+    {
+        for (int j = 0; j < num_grid_x; j++)
+        {
+            const int idx = i * num_grid_x + j;
+
+            const float* scores = cls_pred.row(idx);
+
+            // find label with max score
+            int label = -1;
+            float score = -FLT_MAX;
+            for (int k = 0; k < num_class; k++)
+            {
+                if (scores[k] > score)
+                {
+                    label = k;
+                    score = scores[k];
+                }
+            }
+
+            if (score >= prob_threshold)
+            {
+                ncnn::Mat bbox_pred(reg_max_1, 4, (void*)dis_pred.row(idx));
+                {
+                    ncnn::Layer* softmax = ncnn::create_layer("Softmax");
+
+                    ncnn::ParamDict pd;
+                    pd.set(0, 1); // axis
+                    pd.set(1, 1);
+                    softmax->load_param(pd);
+
+                    ncnn::Option opt;
+                    opt.num_threads = 1;
+                    opt.use_packing_layout = false;
+
+                    softmax->create_pipeline(opt);
+
+                    softmax->forward_inplace(bbox_pred, opt);
+
+                    softmax->destroy_pipeline(opt);
+
+                    delete softmax;
+                }
+
+                float dis_pred[4];
+                for (int k = 0; k < 4; k++)
+                {
+                    float dis = 0.f;
+                    const float* dis_after_sm = bbox_pred.row(k);
+                    for (int l = 0; l < reg_max_1; l++)
+                    {
+                        dis += l * dis_after_sm[l];
+                    }
+
+                    dis_pred[k] = dis * stride;
+                }
+
+                float pb_cx = (j + 0.5f) * stride;
+                float pb_cy = (i + 0.5f) * stride;
+
+                float x0 = pb_cx - dis_pred[0];
+                float y0 = pb_cy - dis_pred[1];
+                float x1 = pb_cx + dis_pred[2];
+                float y1 = pb_cy + dis_pred[3];
+
+                Object obj;
+                obj.rect.x = x0;
+                obj.rect.y = y0;
+                obj.rect.width = x1 - x0;
+                obj.rect.height = y1 - y0;
+                obj.label = label;
+                obj.prob = score;
+
+                objects.push_back(obj);
+            }
+        }
+    }
+}
+
+static int detect_nanodet(const cv::Mat& bgr, std::vector<Object>& objects)
+{
+    ncnn::Net nanodet;
+
+    nanodet.opt.use_vulkan_compute = true;
+    // nanodet.opt.use_bf16_storage = true;
+
+    // original pretrained model from https://github.com/RangiLyu/nanodet
+    // the ncnn model https://github.com/nihui/ncnn-assets/tree/master/models
+    nanodet.load_param("nanodet_m.param");
+    nanodet.load_model("nanodet_m.bin");
+
+    int width = bgr.cols;
+    int height = bgr.rows;
+
+    const int target_size = 320;
+    const float prob_threshold = 0.4f;
+    const float nms_threshold = 0.5f;
+
+    // pad to multiple of 32
+    int w = width;
+    int h = height;
+    float scale = 1.f;
+    if (w > h)
+    {
+        scale = (float)target_size / w;
+        w = target_size;
+        h = h * scale;
+    }
+    else
+    {
+        scale = (float)target_size / h;
+        h = target_size;
+        w = w * scale;
+    }
+
+    ncnn::Mat in = ncnn::Mat::from_pixels_resize(bgr.data, ncnn::Mat::PIXEL_BGR, width, height, w, h);
+
+    // pad to target_size rectangle
+    int wpad = (w + 31) / 32 * 32 - w;
+    int hpad = (h + 31) / 32 * 32 - h;
+    ncnn::Mat in_pad;
+    ncnn::copy_make_border(in, in_pad, hpad / 2, hpad - hpad / 2, wpad / 2, wpad - wpad / 2, ncnn::BORDER_CONSTANT, 0.f);
+
+    const float mean_vals[3] = {103.53f, 116.28f, 123.675f};
+    const float norm_vals[3] = {0.017429f, 0.017507f, 0.017125f};
+    in_pad.substract_mean_normalize(mean_vals, norm_vals);
+
+    ncnn::Extractor ex = nanodet.create_extractor();
+
+    ex.input("input.1", in_pad);
+
+    std::vector<Object> proposals;
+
+    // stride 8
+    {
+        ncnn::Mat cls_pred;
+        ncnn::Mat dis_pred;
+        ex.extract("792", cls_pred);
+        ex.extract("795", dis_pred);
+
+        std::vector<Object> objects8;
+        generate_proposals(cls_pred, dis_pred, 8, in_pad, prob_threshold, objects8);
+
+        proposals.insert(proposals.end(), objects8.begin(), objects8.end());
+    }
+
+    // stride 16
+    {
+        ncnn::Mat cls_pred;
+        ncnn::Mat dis_pred;
+        ex.extract("814", cls_pred);
+        ex.extract("817", dis_pred);
+
+        std::vector<Object> objects16;
+        generate_proposals(cls_pred, dis_pred, 16, in_pad, prob_threshold, objects16);
+
+        proposals.insert(proposals.end(), objects16.begin(), objects16.end());
+    }
+
+    // stride 32
+    {
+        ncnn::Mat cls_pred;
+        ncnn::Mat dis_pred;
+        ex.extract("836", cls_pred);
+        ex.extract("839", dis_pred);
+
+        std::vector<Object> objects32;
+        generate_proposals(cls_pred, dis_pred, 32, in_pad, prob_threshold, objects32);
+
+        proposals.insert(proposals.end(), objects32.begin(), objects32.end());
+    }
+
+    // sort all proposals by score from highest to lowest
+    qsort_descent_inplace(proposals);
+
+    // apply nms with nms_threshold
+    std::vector<int> picked;
+    nms_sorted_bboxes(proposals, picked, nms_threshold);
+
+    int count = picked.size();
+
+    objects.resize(count);
+    for (int i = 0; i < count; i++)
+    {
+        objects[i] = proposals[picked[i]];
+
+        // adjust offset to original unpadded
+        float x0 = (objects[i].rect.x - (wpad / 2)) / scale;
+        float y0 = (objects[i].rect.y - (hpad / 2)) / scale;
+        float x1 = (objects[i].rect.x + objects[i].rect.width - (wpad / 2)) / scale;
+        float y1 = (objects[i].rect.y + objects[i].rect.height - (hpad / 2)) / scale;
+
+        // clip
+        x0 = std::max(std::min(x0, (float)(width - 1)), 0.f);
+        y0 = std::max(std::min(y0, (float)(height - 1)), 0.f);
+        x1 = std::max(std::min(x1, (float)(width - 1)), 0.f);
+        y1 = std::max(std::min(y1, (float)(height - 1)), 0.f);
+
+        objects[i].rect.x = x0;
+        objects[i].rect.y = y0;
+        objects[i].rect.width = x1 - x0;
+        objects[i].rect.height = y1 - y0;
+    }
+
+    return 0;
+}
+
+static void draw_objects(const cv::Mat& bgr, const std::vector<Object>& objects)
+{
+    static const char* class_names[] = {
+        "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"
+    };
+
+    cv::Mat image = bgr.clone();
+
+    for (size_t i = 0; i < objects.size(); i++)
+    {
+        const Object& obj = objects[i];
+
+        fprintf(stderr, "%d = %.5f at %.2f %.2f %.2f x %.2f\n", obj.label, obj.prob,
+                obj.rect.x, obj.rect.y, obj.rect.width, obj.rect.height);
+
+        cv::rectangle(image, obj.rect, cv::Scalar(255, 0, 0));
+
+        char text[256];
+        sprintf(text, "%s %.1f%%", class_names[obj.label], obj.prob * 100);
+
+        int baseLine = 0;
+        cv::Size label_size = cv::getTextSize(text, cv::FONT_HERSHEY_SIMPLEX, 0.5, 1, &baseLine);
+
+        int x = obj.rect.x;
+        int y = obj.rect.y - label_size.height - baseLine;
+        if (y < 0)
+            y = 0;
+        if (x + label_size.width > image.cols)
+            x = image.cols - label_size.width;
+
+        cv::rectangle(image, cv::Rect(cv::Point(x, y), cv::Size(label_size.width, label_size.height + baseLine)),
+                      cv::Scalar(255, 255, 255), -1);
+
+        cv::putText(image, text, cv::Point(x, y + label_size.height),
+                    cv::FONT_HERSHEY_SIMPLEX, 0.5, cv::Scalar(0, 0, 0));
+    }
+
+    cv::imshow("image", image);
+    cv::waitKey(0);
+}
+
+int main(int argc, char** argv)
+{
+    if (argc != 2)
+    {
+        fprintf(stderr, "Usage: %s [imagepath]\n", argv[0]);
+        return -1;
+    }
+
+    const char* imagepath = argv[1];
+
+    cv::Mat m = cv::imread(imagepath, 1);
+    if (m.empty())
+    {
+        fprintf(stderr, "cv::imread %s failed\n", imagepath);
+        return -1;
+    }
+
+    std::vector<Object> objects;
+    detect_nanodet(m, objects);
+
+    draw_objects(m, objects);
+
+    return 0;
+}