yolov5返回坐标（v6版）
1 、从yolov5文件夹李找到detect.py，按Ctrl+F 输入annotator.box_label；
if save_img or save_crop or view_img: # Add bbox to image
c = int(cls) # integer class
label = None if hide_labels else (names[c] if hide_conf else f'{names[c]} {conf:.2f}')
annotator.box_label(xyxy, label, color=colors(c, True))
2、找到这个代码后按住ctrl键，鼠标点击box_label，就会跳到plots.py文件并定位到box_label定义的地方；
3、找到p1, p2 = (int(box[0]), int(box[1])), (int(box[2]), int(box[3]))，在这行代码下面新增：
print("左上点的坐标为：(" + str(p1[0]) + "," + str(p1[1]) + ")，右下点的坐标为(" + str(p2[0]) + "," + str(p2[1]) + ")")
4、完成后的代码如下：
def box_label(self, box, label='', color=(128, 128, 128), txt_color=(255, 255, 255)):
# Add one xyxy box to image with label
if self.pil or not is_ascii(label):
self.draw.rectangle(box, width=self.lw, outline=color) # box
if label:
w, h = self.font.getsize(label) # text width, height
outside = box[1] - h >= 0 # label fits outside box
self.draw.rectangle([box[0],
box[1] - h if outside else box[1],
box[0] + w + 1,
box[1] + 1 if outside else box[1] + h + 1], fill=color)
# self.draw.text((box[0], box[1]), label, fill=txt_color, font=self.font, anchor='ls') # for PIL>8.0
self.draw.text((box[0], box[1] - h if outside else box[1]), label, fill=txt_color, font=self.font)
else: # cv2
p1, p2 = (int(box[0]), int(box[1])), (int(box[2]), int(box[3]))
print("左上点的坐标为：(" + str(p1[0]) + "," + str(p1[1]) + ")，右下点的坐标为(" + str(p2[0]) + "," + str(p2[1]) + ")")
cv2.rectangle(self.im, p1, p2, color, thickness=self.lw, lineType=cv2.LINE_AA)5、测试情况：回到命令行，cd到yolov5文件夹，输入指令：python detect.py --source ../mask.1.jpg，其中mask.1.jpg应改为你yolov5文件夹下的图片名称；按回车键后运行就发现输出的信息多了刚才添加的一行
(venv) (base) rongxiao@rongxiao:~/PycharmProjects/yolococo/yolov5$ python detect.py --source ../mask.1.jpg
detect: weights=yolov5s.pt, source=../mask.1.jpg, imgsz=[640, 640], conf_thres=0.25, iou_thres=0.45, max_det=1000, device=, view_img=False, save_txt=False, save_conf=False, save_crop=False, nosave=False, classes=None, agnostic_nms=False, augment=False, visualize=False, update=False, project=runs/detect, name=exp, exist_ok=False, line_thickness=3, hide_labels=False, hide_conf=False, half=False, dnn=False
YOLOv5 ? v6.0-147-g628817d torch 1.8.2+cpu CPU
Fusing layers...
Model Summary: 213 layers, 7225885 parameters, 0 gradients
左上点的坐标为：(982,384)，右下点的坐标为(1445,767)
左上点的坐标为：(724,237)，右下点的坐标为(770,277)
左上点的坐标为：(711,226)，右下点的坐标为(1689,938)
image 1/1 /home/rongxiao/PycharmProjects/yolococo/mask.1.jpg: 384x640 2 persons, 1 airplane, Done. (0.182s)
Speed: 1.1ms pre-process, 181.7ms inference, 1.0ms NMS per image at shape (1, 3, 640, 640)
Results saved to runs/detect/exp15
附参考：yolov5输出检测到的目标坐标信息（旧版本）
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
总结
到此这篇关于yolov5返回坐标的文章就介绍到这了,更多相关yolov5返回坐标内容请搜索编程网以前的文章或继续浏览下面的相关文章希望大家以后多多支持编程网！
