imshow(output_image);
时间: 2023-09-06 10:08:49 浏览: 35
这行代码是用来在 MATLAB 中显示图像的。你需要将 `output_image` 替换为你要显示的图像变量名。例如,如果你要显示名为 `my_image` 的图像,那么代码应该是这样的:
```
imshow(my_image);
```
注意,你需要确保在运行该代码之前,`my_image` 变量中已经存储了正确的图像数据。
相关问题
import cv2 import numpy as np input_image = cv2.imread('test.png',cv2.IMREAD_GRAYSCALE) height = input_image.shape[0] width = input_image.shape[1] s = np.array([[1,0],[1,1]],dtype=np.boo18) m,n = s.shape[0],s.shape[1] output_image = input_image.copy() for row in range(height-m+1): for col in range(width-n+1): result = input_image[row:row+m,col:col+n] & s if result.sum() >= 1: output_image[row,col] = 255 else: output_image[row,col] = 0 cv2.imshow('input-image',input_image) cv2.imshow('output-image',output_image) cv2.waitKey(0)纠正代码
这段代码存在以下问题:
1. 第一行代码最后缺少换行符;
2. 第二行代码应该写成 `import numpy as np`;
3. 第三行代码中 `np.boo18` 应该改成 `np.uint8`;
4. 第四行代码中 `input_image.shape` 应该改为 `input_image.shape[:2]`;
5. 第七行代码中 `output_image = input_image.copy()` 应该放在第五行代码之后;
6. 第九行代码中 `&` 应该改为 `*`;
7. 第十行代码中 `255` 应该改为 `1`;
8. 第十二行代码中 `0` 应该改为 `255`;
9. 最后一行代码应该加上 `cv2.destroyAllWindows()`。
修改后的代码如下:
```python
import cv2
import numpy as np
input_image = cv2.imread('test.png', cv2.IMREAD_GRAYSCALE)
height, width = input_image.shape[:2]
s = np.array([[1, 0], [1, 1]], dtype=np.uint8)
m, n = s.shape[0], s.shape[1]
output_image = np.zeros((height, width), dtype=np.uint8)
for row in range(height-m+1):
for col in range(width-n+1):
result = input_image[row:row+m, col:col+n] * s
if result.sum() >= 1:
output_image[row, col] = 255
else:
output_image[row, col] = 1
cv2.imshow('input-image', input_image)
cv2.imshow('output-image', output_image)
cv2.waitKey(0)
cv2.destroyAllWindows()
```
帮我继续写代码,实现一条线双线计数的功能。 while True: # 读取每帧图片 _, im = capture.read() if im is None: break # 缩小尺寸 im = cv2.resize(im, (width // 2, height // 2)) list_bboxs = [] # 更新跟踪器 # 跟踪器传入检测的模型和处理之后的图片 output_image_frame, list_bboxs = objtracker.update(detector, im) # 输出图片 output_image_frame = cv2.add(output_image_frame, color_polygons_image) if len(list_bboxs) > 0:
Certainly! Here's a continuation of the code to implement the line counting functionality:
```python
# Iterate through each bounding box detected
for bbox in list_bboxs:
x, y, w, h = bbox
# Check if the bounding box intersects with the blue line
if y + h/2 > h/2 and y + h/2 < h/2 + 20:
# Increment blue line counter
blue_line_count += 1
# Check if the bounding box intersects with the yellow line
if y + h/2 > h/2 + 70 and y + h/2 < h/2 + 90:
# Increment yellow line counter
yellow_line_count += 1
# Display the counts on the output image
cv2.putText(output_image_frame, f"Blue Line Count: {blue_line_count}", (10, 30), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 0, 255), 2)
cv2.putText(output_image_frame, f"Yellow Line Count: {yellow_line_count}", (10, 70), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 255), 2)
# Display the output image
cv2.imshow("Output", output_image_frame)
# Break the loop if "q" is pressed
if cv2.waitKey(1) & 0xFF == ord('q'):
break
# Release the video capture and destroy all windows
capture.release()
cv2.destroyAllWindows()
```
In this code, we iterate through each bounding box detected (`list_bboxs`) and check if it intersects with the blue or yellow lines. If a bounding box intersects with the blue line, we increment the `blue_line_count` variable. If a bounding box intersects with the yellow line, we increment the `yellow_line_count` variable.
We then display the counts on the output image using `cv2.putText()` and show the output image using `cv2.imshow()`. The loop continues until the "q" key is pressed.
Finally, we release the video capture and destroy all windows.
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