prompter: I have images loaded with cv2 in python. After detecting the edges using cv2.Canny I want to draw boxes around the objects in the image. Give me an example in python.

assistant: 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.

assistant: One possible way to draw boxes around objects in an image using cv2 is to use the selectROI() function. This function allows you to select a region of interest (ROI) by drawing a rectangle with your mouse. You can then crop the image within the ROI and display it as output.

Another possible way is to use contours. Contours are boundaries around objects that have the same color or intensity. You can use cv2.findContours() to detect contours in an image, and then use cv2.boundingRect() to get the coordinates of the bounding boxes around each contour. You can then use cv2.rectangle() to draw the boxes on the original image.

Here is an example code for both methods:

```python
#importing cv2 module
import cv2 as cv

#reading an image
img = cv.imread('image.jpg')

#converting it to grayscale
gray = cv.cvtColor(img, cv.COLOR_BGR2GRAY)

#applying Canny edge detection
edges = cv.Canny(gray, 100, 200)

#using selectROI() function
roi = cv.selectROI(edges)
x, y, w, h = roi #getting coordinates of ROI
crop = img[y:y+h, x:x+w] #cropping image within ROI
cv.imshow('Cropped Image', crop) #displaying cropped image

#using contours
contours, hierarchy = cv.findContours(edges, cv.RETR_EXTERNAL, cv.CHAIN_APPROX_SIMPLE) #finding contours
for cnt in contours:
    x,y,w,h = cv.boundingRect(cnt) #getting coordinates of bounding box for each contour
    img = cv.rectangle(img,(x,y),(x+w,y+h),(0,255,0),2) #drawing rectangle on original image

cv.imshow('Original Image', img) #displaying original image with boxes

cv.waitKey(0)
cv.destroyAllWindows()
```

assistant: Sure, here's an example code snippet in Python that should achieve what you are looking for:
```
import cv2

# Load the image
img = cv2.imread('path_to_image')

# Convert the image to grayscale
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

# Use Canny edge detection to detect the edges in the image
edges = cv2.Canny(gray, 100, 200)

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

# Loop over each contour in the image
for cnt in contours:
    # Get the bounding box of each contour
    x, y, w, h = cv2.boundingRect(cnt)
    
    # Draw a rectangle around the object
    cv2.rectangle(img, (x, y), (x + w, y + h), (0, 255, 0), 2)

# Display the final image with boxes around objects
cv2.imshow('image', img)
cv2.waitKey(0)
cv2.destroyAllWindows()
```

In this code snippet, we load the image and convert it to grayscale. We then use the Canny edge detection method to detect the edges in the image. Next, we find the contours in the image using the ```findContours``` function in cv2. Finally, we loop over each contour, get its bounding box, and draw a rectangle around the object using the rectangle function in cv2. The final image with boxes around objects is then displayed using ```imshow```.