もちろん！Pythonでの例です：

```py
import cv2

# Load image and convert to grayscale
img = cv2.imread('your_image.jpg')
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

# Perform Canny edge detection
edges = cv2.Canny(gray, 100, 200)

# Find contours of objects in the image
contours, hierarchy = cv2.findContours(edges, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)

# Draw bounding boxes around each object
for cnt in contours:
    x,y,w,h = cv2.boundingRect(cnt)
    cv2.rectangle(img,(x,y),(x+w,y+h),(0,255,0),2)

# Display result
cv2.imshow('Image with bounding boxes', img)
cv2.waitKey(0)
cv2.destroyAllWindows()

```
このコードでは，まず画像を読み込み，それをグレースケールに変換します．次に，関数 `cv2.Canny()` を用いて，画像のエッジを検出します．次に， `cv2.findContours()` を用いて，画像中のオブジェクトの輪郭を求めます．最後に，各輪郭をループ処理し， `cv2.rectangle()` を用いてオブジェクトの周囲にバウンディングボックスを描きます．

cv2.Canny()` と `cv2.findContours()` のパラメータを調整することで，それぞれエッジ検出と輪郭検出の感度を変更することができます．
Sure! Here's an example in Python:

```py
import cv2

# Load image and convert to grayscale
img = cv2.imread('your_image.jpg')
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

# Perform Canny edge detection
edges = cv2.Canny(gray, 100, 200)

# Find contours of objects in the image
contours, hierarchy = cv2.findContours(edges, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)

# Draw bounding boxes around each object
for cnt in contours:
    x,y,w,h = cv2.boundingRect(cnt)
    cv2.rectangle(img,(x,y),(x+w,y+h),(0,255,0),2)

# Display result
cv2.imshow('Image with bounding boxes', img)
cv2.waitKey(0)
cv2.destroyAllWindows()

```
In this code, we first load the image and convert it to grayscale. We then use the `cv2.Canny()` function to detect edges in the image. Next, we use `cv2.findContours()` to find the contours of objects in the image. Finally, we loop through each contour and use `cv2.rectangle()` to draw a bounding box around the object.

You can adjust the parameters of `cv2.Canny()` and `cv2.findContours()` to change the sensitivity of edge detection and contour detection, respectively.