OpenCV 3 Computer Vision with Python Cookbook

How to do it

You need to complete the following steps:

1. Import the necessary modules:

import cv2import numpy as np

2. Load the images and exposure times:

imgs_names = ['33', '100', '179', '892', '1560', '2933']exp_times = []images = []for name in imgs_names:    exp_times.append(1/float(name))    images.append(cv2.imread('../data/hdr/%s.jpg' % name, cv2.IMREAD_COLOR))exp_times = np.array(exp_times).astype(np.float32)

3. Recover the CRF:

calibrate = cv2.createCalibrateDebevec()response = calibrate.process(images, exp_times)

4. Compute an HDR image:

merge_debevec = cv2.createMergeDebevec()hdr = merge_debevec.process(images, exp_times, response)

5. Turn the HDR image into a Low Dynamic Range (LDR) image to be able to display it:

tonemap = cv2.createTonemapDurand(2.4) ...