answer_94.py

import cv2
import numpy as np

np.random.seed(0)

# read image
img = cv2.imread("imori_1.jpg")
H, W, C = img.shape

# Grayscale
gray = 0.2126 * img[..., 2] + 0.7152 * img[..., 1] + 0.0722 * img[..., 0]

gt = np.array((47, 41, 129, 103), dtype=np.float32)

cv2.rectangle(img, (gt[0], gt[1]), (gt[2], gt[3]), (0,255,0), 1)

def iou(a, b):
    area_a = (a[2] - a[0]) * (a[3] - a[1])
    area_b = (b[2] - b[0]) * (b[3] - b[1])
    iou_x1 = np.maximum(a[0], b[0])
    iou_y1 = np.maximum(a[1], b[1])
    iou_x2 = np.minimum(a[2], b[2])
    iou_y2 = np.minimum(a[3], b[3])
    iou_w = max(iou_x2 - iou_x1, 0)
    iou_h = max(iou_y2 - iou_y1, 0)
    area_iou = iou_w * iou_h
    iou = area_iou / (area_a + area_b - area_iou)
    return iou


# crop and create database
Crop_num = 200
L = 60

for i in range(Crop_num):
    x1 = np.random.randint(W-L)
    y1 = np.random.randint(H-L)
    x2 = x1 + L
    y2 = y1 + L
    crop = np.array((x1, y1, x2, y2))

    _iou = iou(gt, crop)

    if _iou >= 0.5:
        cv2.rectangle(img, (x1, y1), (x2, y2), (0,0,255), 1)
        label = 1
    else:
        cv2.rectangle(img, (x1, y1), (x2, y2), (255,0,0), 1)
        label = 0

cv2.imwrite("out.jpg", img)
cv2.imshow("result", img)
cv2.waitKey(0)