写出python 检测一幅图中有几个立方体的代码？

这是一道比较复杂的计算机视觉问题，需要使用图像处理和机器学习技术。以下是一个简单的示例代码，使用了OpenCV库和深度学习模型YOLOv3：

import cv2
import numpy as np

# 加载YOLOv3模型
net = cv2.dnn.readNetFromDarknet('yolov3.cfg', 'yolov3.weights')
layer_names = net.getLayerNames()
output_layers = [layer_names[i[0] - 1] for i in net.getUnconnectedOutLayers()]

# 加载图像并进行预处理
img = cv2.imread('image.jpg')
img = cv2.resize(img, None, fx=0.4, fy=0.4)
height, width, channels = img.shape
blob = cv2.dnn.blobFromImage(img, 0.00392, (416, 416), (0, 0, 0), True, crop=False)

# 运行YOLOv3模型进行目标检测
net.setInput(blob)
outs = net.forward(output_layers)

# 解析检测结果
class_ids = []
confidences = []
boxes = []
for out in outs:
    for detection in out:
        scores = detection[5:]
        class_id = np.argmax(scores)
        confidence = scores[class_id]
        if confidence > 0.5:
            center_x = int(detection[0] * width)
            center_y = int(detection[1] * height)
            w = int(detection[2] * width)
            h = int(detection[3] * height)
            x = center_x - w // 2
            y = center_y - h // 2
            class_ids.append(class_id)
            confidences.append(float(confidence))
            boxes.append([x, y, w, h])

# 处理立方体检测结果
cube_ids = []
for i in range(len(class_ids)):
    if class_ids[i] == 0:  # 立方体的class_id为0
        cube_ids.append(i)

print('检测到%d个立方体' % len(cube_ids))

需要注意的是，这个代码仅供参考，具体实现需要根据具体情况进行调整和优化。