Yy2_3[i] = XYxy[ei[i, 2 - 1] - 1, 0][1] - XYxy[ei[i, 3 - 1] - 1, 0][1] B[i, 0] = 1 / 2 / Ae[i] * Yy2_3[i] Yy3_1[i] = XYxy[ei[i, 3 - 1] - 1, 0][1] - XYxy[ei[i, 1 - 1] - 1, 0][1] B[i, 1] = 1 / 2 / Ae[i] * Yy3_1[i] Yy1_2[i] = XYxy[ei[i, 1 - 1] - 1, 0][1] - XYxy[ei[i, 2 - 1] - 1, 0][1] B[i, 2] = 1 / 2 / Ae[i] * Yy1_2[i] 优化

可以将代码中的重复计算进行简化，优化后的代码如下：

y_diff = XYxy[ei[:,2]-1, 0][:, 1] - XYxy[ei[:,3]-1, 0][:, 1]
B[:, 0] = 1 / 2 / Ae * y_diff

y_diff = XYxy[ei[:,3]-1, 0][:, 1] - XYxy[ei[:,1]-1, 0][:, 1]
B[:, 1] = 1 / 2 / Ae * y_diff

y_diff = XYxy[ei[:,1]-1, 0][:, 1] - XYxy[ei[:,2]-1, 0][:, 1]
B[:, 2] = 1 / 2 / Ae * y_diff

其中，通过使用切片操作和数组索引，可以避免重复计算。同时，注意到B、ei、Ae、XYxy、y_diff都是数组，需要在代码其他部分定义或赋值。

相关问题

def trigger(self, detections: Detections) -> np.ndarray: """ Determines if the detections are within the polygon zone. Parameters: detections (Detections): The detections to be checked against the polygon zone Returns: np.ndarray: A boolean numpy array indicating if each detection is within the polygon zone """ clipped_xyxy = clip_boxes( boxes_xyxy=detections.xyxy, frame_resolution_wh=self.frame_resolution_wh ) clipped_detections = replace(detections, xyxy=clipped_xyxy) clipped_anchors = np.ceil( clipped_detections.get_anchor_coordinates(anchor=self.triggering_position) ).astype(int) is_in_zone = self.mask[clipped_anchors[:, 1], clipped_anchors[:, 0]] self.current_count = np.sum(is_in_zone) return is_in_zone.astype(bool)

这是一个名为 `trigger` 的方法，用于确定检测结果是否位于多边形区域内。

该方法接受一个 `Detections` 对象作为参数，该对象包含了待检测的结果。在方法中，首先通过 `clip_boxes` 函数对检测结果的边界框进行裁剪，以确保其不超出帧的分辨率。然后，使用 `replace` 函数将裁剪后的边界框应用到 `detections` 对象中。

接下来，使用 `get_anchor_coordinates` 方法获取裁剪后的边界框的锚点坐标，并将其取整为最接近的整数，并将其设置为 `clipped_anchors`。

然后，通过使用 `self.mask` 和 `clipped_anchors`，获取每个锚点坐标是否位于多边形区域内的布尔值，并将结果保存在 `is_in_zone` 中。

最后，通过使用 `np.sum` 统计位于多边形区域内的锚点的数量，并将其保存在 `self.current_count` 中。最后，将 `is_in_zone` 转换为布尔类型并返回。

请注意，上述代码中使用的函数和类，如 `clip_boxes`、`replace`、`Detections` 等，都没有给出具体实现。您需要根据您的需求自行实现或导入这些函数和类。

以下是代码示例：

import numpy as np

class PolygonZone:
    def trigger(self, detections: Detections) -> np.ndarray:
        # 裁剪边界框
        clipped_xyxy = clip_boxes(
            boxes_xyxy=detections.xyxy, frame_resolution_wh=self.frame_resolution_wh
        )
        clipped_detections = replace(detections, xyxy=clipped_xyxy)
        
        # 获取锚点坐标
        clipped_anchors = np.ceil(
            clipped_detections.get_anchor_coordinates(anchor=self.triggering_position)
        ).astype(int)
        
        # 检测是否位于多边形区域内
        is_in_zone = self.mask[clipped_anchors[:, 1], clipped_anchors[:, 0]]
        
        # 统计位于多边形区域内的数量
        self.current_count = np.sum(is_in_zone)
        
        return is_in_zone.astype(bool)

请根据您的需求实现或导入缺失的函数和类，并根据具体情况进行调整。

translation this code to c:def filter_box(org_box, conf_thres, iou_thres): org_box = np.squeeze(org_box) conf = org_box[..., 4] > conf_thres box = org_box[conf == True] print('box:') print(box.shape) cls_cinf = box[..., 5:] cls = [] for i in range(len(cls_cinf)): cls.append(int(np.argmax(cls_cinf[i]))) all_cls = list(set(cls)) output = [] for i in range(len(all_cls)): curr_cls = all_cls[i] curr_cls_box = [] curr_out_box = [] for j in range(len(cls)): if cls[j] == curr_cls: box[j][5] = curr_cls curr_cls_box.append(box[j][:6]) curr_cls_box = np.array(curr_cls_box) curr_cls_box = xywh2xyxy(curr_cls_box) curr_out_box = nms(curr_cls_box, iou_thres) for k in curr_out_box: output.append(curr_cls_box[k]) output = np.array(output) return output

以下是该代码的 C 语言版本：

#include <stdio.h>
#include <stdlib.h>
#include <math.h>

#define MAX_BOX_NUM 1000

typedef struct {
    float x, y, w, h, score;
    int cls;
} Box;

float max(float a, float b) {
    return a > b ? a : b;
}

float min(float a, float b) {
    return a < b ? a : b;
}

float iou(Box a, Box b) {
    float inter_xmin = max(a.x - a.w / 2, b.x - b.w / 2);
    float inter_ymin = max(a.y - a.h / 2, b.y - b.h / 2);
    float inter_xmax = min(a.x + a.w / 2, b.x + b.w / 2);
    float inter_ymax = min(a.y + a.h / 2, b.y + b.h / 2);
    float inter_w = max(inter_xmax - inter_xmin, 0.f);
    float inter_h = max(inter_ymax - inter_ymin, 0.f);
    float inter_area = inter_w * inter_h;
    float a_area = a.w * a.h;
    float b_area = b.w * b.h;
    float union_area = a_area + b_area - inter_area;
    return inter_area / union_area;
}

void xywh2xyxy(float* box) {
    float x = box[0], y = box[1], w = box[2], h = box[3];
    box[0] = x - w / 2;
    box[1] = y - h / 2;
    box[2] = x + w / 2;
    box[3] = y + h / 2;
}

void nms(Box* boxes, int box_num, float iou_thres, Box* out_boxes, int* out_box_num) {
    int* mask = (int*)malloc(sizeof(int) * box_num);
    int i, j, k;
    for (i = 0; i < box_num; ++i) {
        mask[i] = 1;
    }
    for (i = 0; i < box_num; ++i) {
        if (!mask[i]) {
            continue;
        }
        out_boxes[(*out_box_num)++] = boxes[i];
        for (j = i + 1; j < box_num; ++j) {
            if (!mask[j]) {
                continue;
            }
            float iou_val = iou(boxes[i], boxes[j]);
            if (iou_val > iou_thres) {
                mask[j] = 0;
            }
        }
    }
    free(mask);
}

Box* filter_box(float* org_box, float conf_thres, float iou_thres, int* box_num) {
    int i, j;
    float* box = (float*)malloc(sizeof(float) * MAX_BOX_NUM * 6);
    int conf_box_num = 0;
    int cls[MAX_BOX_NUM];
    int cls_num = 0;
    for (i = 0; i < MAX_BOX_NUM; ++i) {
        float* cur_box = org_box + i * 6;
        if (cur_box[4] <= conf_thres) {
            continue;
        }
        for (j = 0; j < 5; ++j) {
            box[conf_box_num * 6 + j] = cur_box[j];
        }
        cls[conf_box_num] = (int)round(cur_box[5]);
        ++conf_box_num;
    }
    for (i = 0; i < conf_box_num; ++i) {
        int cur_cls = cls[i];
        int is_new_cls = 1;
        for (j = 0; j < cls_num; ++j) {
            if (cur_cls == cls[j]) {
                is_new_cls = 0;
                break;
            }
        }
        if (is_new_cls) {
            cls[cls_num++] = cur_cls;
        }
    }
    Box* output = (Box*)malloc(sizeof(Box) * MAX_BOX_NUM);
    int output_box_num = 0;
    for (i = 0; i < cls_num; ++i) {
        int cur_cls = cls[i];
        float curr_cls_box[MAX_BOX_NUM][6];
        int curr_cls_box_num = 0;
        for (j = 0; j < conf_box_num; ++j) {
            if (cls[j] == cur_cls) {
                box[j * 6 + 5] = cur_cls;
                int k;
                for (k = 0; k < 6; ++k) {
                    curr_cls_box[curr_cls_box_num][k] = box[j * 6 + k];
                }
                ++curr_cls_box_num;
            }
        }
        for (j = 0; j < curr_cls_box_num; ++j) {
            xywh2xyxy(curr_cls_box[j]);
        }
        Box curr_out_box[MAX_BOX_NUM];
        int curr_out_box_num = 0;
        nms((Box*)curr_cls_box, curr_cls_box_num, iou_thres, curr_out_box, &curr_out_box_num);
        for (j = 0; j < curr_out_box_num; ++j) {
            output[output_box_num++] = curr_out_box[j];
        }
    }
    free(box);
    *box_num = output_box_num;
    return output;
}