如何使用张量流对象检测检查是否存在边界框

Question

我正在为小型无人机编写程序。我正在计算每一帧平台的距离和坐标。无人机根据边界框的坐标顺时针或逆时针旋转，直到边界框居中。

                maxBoxes=1 #max boxes to draw
                vis_util.visualize_boxes_and_labels_on_image_array(
                    image,
                    np.squeeze(boxes),
                    np.squeeze(classes).astype(np.int32),
                    np.squeeze(scores),
                    category_index,
                    max_boxes_to_draw=maxBoxes,
                    min_score_thresh=0.5,
                    use_normalized_coordinates=True,
                    line_thickness=4)
                #if here, to check whether there is a detected object and then calculate
                ymin = int((boxes[0][0][0]*imageHeight))
                xmin = int((boxes[0][0][1]*imageWidth))
                ymax = int((boxes[0][0][2]*imageHeight))
                xmax = int((boxes[0][0][3]*imageWidth))
                boxWidth=xmax-xmin
                boxHeight=ymax-ymax
                #Distance calculation
                distance=round(W*F/boxWidth,2) #distance from the object

我的问题是如何检查给定帧是否有检测到的物体（边界框），因为有时它无法找到物体但仍然在随机方向上旋转。

Answer 1

所以，通过github查看源代码后，我已经能够弄明白了。方法是检查第一个分数是否低于阈值，就像我下面的例子。

            maxBoxes=1 #max boxes to draw
            minScoreThreshold=0.5 #minimum score threshold
            vis_util.visualize_boxes_and_labels_on_image_array(
                image,
                np.squeeze(boxes),
                np.squeeze(classes).astype(np.int32),
                np.squeeze(scores),
                category_index,
                max_boxes_to_draw=maxBoxes,
                min_score_thresh=minScoreThreshold,
                use_normalized_coordinates=True,
                line_thickness=4)
            #if here, to check whether there is a detected object and then calculate
            if (scores[0]<minScoreThreshold).all():
                print("Nothing has been detected")
            else:
                print("Object has been detected. Continuing with calculations")
                ymin = int((boxes[0][0][0]*imageHeight))
                xmin = int((boxes[0][0][1]*imageWidth))
                ymax = int((boxes[0][0][2]*imageHeight))
                xmax = int((boxes[0][0][3]*imageWidth))
                boxWidth=xmax-xmin
                boxHeight=ymax-ymax
                #Distance calculation
                distance=round(W*F/boxWidth,2) #distance from the object

如何使用张量流对象检测检查是否存在边界框

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