在yolov5的detect代码中,增加计算2个目标框中心点的距离并输出到TXT文件中
时间: 2024-02-25 08:58:48 浏览: 77
YOLO算法-城市电杆数据集-496张图像带标签-电杆.zip
要在YOLOv5的detect代码中增加计算两个目标框中心点距离并输出到TXT文件中,可以按照以下步骤进行:
1. 在`detect.py`文件中,找到以下部分的代码:
```python
# Write results
with open(save_txt, 'a') as file:
for *xyxy, conf, cls in reversed(det):
if save_txt or save_img: # Write to file
file.write(('%g ' * 6 + '\n') % (*xyxy, conf, cls))
if save_img 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}')
plot_one_box(xyxy, im0, label=label, color=colors(c, True), line_thickness=3)
# Stream results
if view_img:
cv2.imshow(str(p), im0)
if cv2.waitKey(1) == ord('q'): # q to quit
raise StopIteration
if save_img: # Save image with detections
if dataset.mode == 'images':
cv2.imwrite(save_path, im0)
else: # 'video'
if vid_path != save_path: # new video
vid_path = save_path
if isinstance(vid_writer, cv2.VideoWriter):
vid_writer.release() # release previous video writer
if vid_cap: # video capture
fps = vid_cap.get(cv2.CAP_PROP_FPS)
w = int(vid_cap.get(cv2.CAP_PROP_FRAME_WIDTH))
h = int(vid_cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
else: # image sequence
fps, w, h = 30, im0.shape[1], im0.shape[0]
save_path = str(Path(save_path).parent / Path(save_path).stem) + '.mp4'
vid_writer = cv2.VideoWriter(save_path, cv2.VideoWriter_fourcc(*opt.fourcc), fps, (w, h))
vid_writer.write(im0)
if save_txt or save_img:
print(f'[{t0:.3f}] {p}')
```
2. 在该部分的代码中,在`if save_txt or save_img:`下面添加以下代码,用于计算两个目标框中心点距离并将结果输出到TXT文件中:
```python
if save_txt:
with open(save_path.replace('.jpg', '.txt'), 'w') as f:
for i, (x1, y1, x2, y2, conf, cls) in enumerate(det):
# Calculate center point coordinates
x_center, y_center = (x1 + x2) / 2, (y1 + y2) / 2
# Calculate distance to other boxes
distances = []
for j, (x1_j, y1_j, x2_j, y2_j, conf_j, cls_j) in enumerate(det):
if i == j:
continue
x_center_j, y_center_j = (x1_j + x2_j) / 2, (y1_j + y2_j) / 2
distance = ((x_center - x_center_j) ** 2 + (y_center - y_center_j) ** 2) ** 0.5
distances.append(distance)
# Write distances to file
f.write(f"{i}: {', '.join([str(d) for d in distances])}\n")
```
其中,`save_path`代表保存检测结果的路径,`.txt`文件将会保存在该路径下,文件名与图片名相同。
3. 运行YOLOv5的检测命令时,加上`--save-txt`参数,用于保存TXT文件,例如:
```bash
python detect.py --source data/images --weights yolov5s.pt --save-txt
```
执行完毕后,会在检测结果保存路径下生成与图片名相同的`.txt`文件,其中包含了每个目标框与其他目标框中心点距离的信息。
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