Object detection and bounding box

import torch
from d2l import torch as d2l

d2l.set_figsize()
img = d2l.plt.imread('./catdog.jpg')
d2l.plt.imshow(img)

#@save
def box_corner_to_center(boxes):
    """ From top left to bottom right to middle width and height """
    x1,y1,x2,y2 = boxes[:,0],boxes[:,1],boxes[:,2],boxes[:,3]
    cx = (x1 + x2)/2
    cy = (y1 + y2)/2
    w = x2 - x1
    h = y2 - y1
    boxes = torch.stack((cx,cy,w,h),axis = -1)
    return boxes

#@save
def box_center_to_corner(boxes):
    """ From middle width and height to top left and bottom right """
    cx,cy,w,h = boxes[:,0],boxes[:,1],boxes[:,2],boxes[:,3]
    x1 = cx - 0.5*w
    y1 = cy - 0.5*h
    x2 = cx + 0.5*w
    y2 = cy + 0.5*h
    boxes = torch.stack((x1,y1,x2,y2),axis = -1)
    return boxes
dog_bbox,cat_bbox = [60.0,45.0,378.0,516.0],[400.0,112.0,655.0,493.0]
boxes = torch.tensor((dog_bbox, cat_bbox))

def bbox_to_rect(bbox,color):
    return d2l.plt.Rectangle(
    xy = (bbox[0],bbox[1]),width = bbox[2] - bbox[0],height = bbox[3] - bbox[1],
        fill = False,edgecolor = color,linewidth = 2
    )

img = d2l.plt.imread('./catdog.jpg')
fig = d2l.plt.imshow(img)
fig.axes.add_patch(bbox_to_rect(dog_bbox, 'blue'))
fig.axes.add_patch(bbox_to_rect(cat_bbox, 'red'))