yolov5输出检测到的目标坐标信息

找到detect.py，在大概113行，找到plot_one_box

                # Write results                for *xyxy, conf, cls in reversed(det):                    if save_txt:  # Write to file                        xywh = (xyxy2xywh(torch.tensor(xyxy).view(1, 4)) / gn).view(-1).tolist()  # normalized xywh                        with open(txt_path + '.txt', 'a') as f:                            f.write(('%g ' * 5 + '\n') % (cls, *xywh))  # label format                    if save_img or view_img:  # Add bbox to image                        label = '%s %.2f' % (names[int(cls)], conf)                        plot_one_box(xyxy, im0, label=label, color=colors[int(cls)], line_thickness=3)

ctr+鼠标点击，进入general.py，并自动定位到plot_one_box函数，修改函数为

def plot_one_box(x, img, color=None, label=None, line_thickness=None):    # Plots one bounding box on image img    tl = line_thickness or round(0.002 * (img.shape[0] + img.shape[1]) / 2) + 1  # line/font thickness    color = color or [random.randint(0, 255) for _ in range(3)]    c1, c2 = (int(x[0]), int(x[1])), (int(x[2]), int(x[3]))    cv2.rectangle(img, c1, c2, color, thickness=tl, lineType=cv2.LINE_AA)    print("左上点的坐标为：(" + str(c1[0]) + "," + str(c1[1]) + ")，右下点的坐标为(" + str(c2[0]) + "," + str(c2[1]) + ")")

即可输出目标坐标信息了