Add Java and Python code for cascade classifier and HDR tutorials.

samples/python/tutorial_code/objectDetection/cascade_classifier/objectDetection.py

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+from __future__ import print_function
+import cv2 as cv
+import argparse
+
+def detectAndDisplay(frame):
+    frame_gray = cv.cvtColor(frame, cv.COLOR_BGR2GRAY)
+    frame_gray = cv.equalizeHist(frame_gray)
+
+    #-- Detect faces
+    faces = face_cascade.detectMultiScale(frame_gray)
+    for (x,y,w,h) in faces:
+        center = (x + w//2, y + h//2)
+        frame = cv.ellipse(frame, center, (w//2, h//2), 0, 0, 360, (255, 0, 255), 4)
+
+        faceROI = frame_gray[y:y+h,x:x+w]
+        #-- In each face, detect eyes
+        eyes = eyes_cascade.detectMultiScale(faceROI)
+        for (x2,y2,w2,h2) in eyes:
+            eye_center = (x + x2 + w2//2, y + y2 + h2//2)
+            radius = int(round((w2 + h2)*0.25))
+            frame = cv.circle(frame, eye_center, radius, (255, 0, 0 ), 4)
+
+    cv.imshow('Capture - Face detection', frame)
+
+parser = argparse.ArgumentParser(description='Code for Cascade Classifier tutorial.')
+parser.add_argument('--face_cascade', help='Path to face cascade.', default='../../data/haarcascades/haarcascade_frontalface_alt.xml')
+parser.add_argument('--eyes_cascade', help='Path to eyes cascade.', default='../../data/haarcascades/haarcascade_eye_tree_eyeglasses.xml')
+parser.add_argument('--camera', help='Camera devide number.', type=int, default=0)
+args = parser.parse_args()
+
+face_cascade_name = args.face_cascade
+eyes_cascade_name = args.eyes_cascade
+
+face_cascade = cv.CascadeClassifier()
+eyes_cascade = cv.CascadeClassifier()
+
+#-- 1. Load the cascades
+if not face_cascade.load(face_cascade_name):
+    print('--(!)Error loading face cascade')
+    exit(0)
+if not eyes_cascade.load(eyes_cascade_name):
+    print('--(!)Error loading eyes cascade')
+    exit(0)
+
+camera_device = args.camera
+#-- 2. Read the video stream
+cap = cv.VideoCapture(camera_device)
+if not cap.isOpened:
+    print('--(!)Error opening video capture')
+    exit(0)
+
+while True:
+    ret, frame = cap.read()
+    if frame is None:
+        print('--(!) No captured frame -- Break!')
+        break
+
+    detectAndDisplay(frame)
+
+    if cv.waitKey(10) == 27:
+        break

samples/python/tutorial_code/photo/hdr_imaging/hdr_imaging.py

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+from __future__ import print_function
+from __future__ import division
+import cv2 as cv
+import numpy as np
+import argparse
+import os
+
+def loadExposureSeq(path):
+    images = []
+    times = []
+    with open(os.path.join(path, 'list.txt')) as f:
+        content = f.readlines()
+    for line in content:
+        tokens = line.split()
+        images.append(cv.imread(os.path.join(path, tokens[0])))
+        times.append(1 / float(tokens[1]))
+
+    return images, np.asarray(times, dtype=np.float32)
+
+parser = argparse.ArgumentParser(description='Code for High Dynamic Range Imaging tutorial.')
+parser.add_argument('--input', type=str, help='Path to the directory that contains images and exposure times.')
+args = parser.parse_args()
+
+if not args.input:
+    parser.print_help()
+    exit(0)
+
+## [Load images and exposure times]
+images, times = loadExposureSeq(args.input)
+## [Load images and exposure times]
+
+## [Estimate camera response]
+calibrate = cv.createCalibrateDebevec()
+response = calibrate.process(images, times)
+## [Estimate camera response]
+
+## [Make HDR image]
+merge_debevec = cv.createMergeDebevec()
+hdr = merge_debevec.process(images, times, response)
+## [Make HDR image]
+
+## [Tonemap HDR image]
+tonemap = cv.createTonemapDurand(2.2)
+ldr = tonemap.process(hdr)
+## [Tonemap HDR image]
+
+## [Perform exposure fusion]
+merge_mertens = cv.createMergeMertens()
+fusion = merge_mertens.process(images)
+## [Perform exposure fusion]
+
+## [Write results]
+cv.imwrite('fusion.png', fusion * 255)
+cv.imwrite('ldr.png', ldr * 255)
+cv.imwrite('hdr.hdr', hdr)
+## [Write results]