Add Java and Python code for the following imgproc tutorials: Canny, Remap, threshold and threshold inRange. Use HSV colorspace instead of RGB for inRange threshold tutorial.

samples/python/tutorial_code/ImgTrans/canny_detector/CannyDetector_Demo.py

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+from __future__ import print_function
+import cv2 as cv
+import argparse
+
+max_lowThreshold = 100
+window_name = 'Edge Map'
+title_trackbar = 'Min Threshold:'
+ratio = 3
+kernel_size = 3
+
+def CannyThreshold(val):
+    low_threshold = val
+    img_blur = cv.blur(src_gray, (3,3))
+    detected_edges = cv.Canny(img_blur, low_threshold, low_threshold*ratio, kernel_size)
+    mask = detected_edges != 0
+    dst = src * (mask[:,:,None].astype(src.dtype))
+    cv.imshow(window_name, dst)
+
+parser = argparse.ArgumentParser(description='Code for Canny Edge Detector tutorial.')
+parser.add_argument('--input', help='Path to input image.', default='../data/fruits.jpg')
+args = parser.parse_args()
+
+src = cv.imread(args.input)
+if src is None:
+    print('Could not open or find the image: ', args.input)
+    exit(0)
+
+src_gray = cv.cvtColor(src, cv.COLOR_BGR2GRAY)
+
+cv.namedWindow(window_name)
+cv.createTrackbar(title_trackbar, window_name , 0, max_lowThreshold, CannyThreshold)
+
+CannyThreshold(0)
+cv.waitKey()

samples/python/tutorial_code/ImgTrans/remap/Remap_Demo.py

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+from __future__ import print_function
+import cv2 as cv
+import numpy as np
+import argparse
+
+## [Update]
+def update_map(ind, map_x, map_y):
+    if ind == 0:
+        for i in range(map_x.shape[0]):
+            for j in range(map_x.shape[1]):
+                if j > map_x.shape[1]*0.25 and j < map_x.shape[1]*0.75 and i > map_x.shape[0]*0.25 and i < map_x.shape[0]*0.75:
+                    map_x[i,j] = 2 * (j-map_x.shape[1]*0.25) + 0.5
+                    map_y[i,j] = 2 * (i-map_y.shape[0]*0.25) + 0.5
+                else:
+                    map_x[i,j] = 0
+                    map_y[i,j] = 0
+    elif ind == 1:
+        for i in range(map_x.shape[0]):
+            map_x[i,:] = [x for x in range(map_x.shape[1])]
+        for j in range(map_y.shape[1]):
+            map_y[:,j] = [map_y.shape[0]-y for y in range(map_y.shape[0])]
+    elif ind == 2:
+        for i in range(map_x.shape[0]):
+            map_x[i,:] = [map_x.shape[1]-x for x in range(map_x.shape[1])]
+        for j in range(map_y.shape[1]):
+            map_y[:,j] = [y for y in range(map_y.shape[0])]
+    elif ind == 3:
+        for i in range(map_x.shape[0]):
+            map_x[i,:] = [map_x.shape[1]-x for x in range(map_x.shape[1])]
+        for j in range(map_y.shape[1]):
+            map_y[:,j] = [map_y.shape[0]-y for y in range(map_y.shape[0])]
+## [Update]
+
+parser = argparse.ArgumentParser(description='Code for Remapping tutorial.')
+parser.add_argument('--input', help='Path to input image.', default='../data/chicky_512.png')
+args = parser.parse_args()
+
+## [Load]
+src = cv.imread(args.input, cv.IMREAD_COLOR)
+if src is None:
+    print('Could not open or find the image: ', args.input)
+    exit(0)
+## [Load]
+
+## [Create]
+map_x = np.zeros((src.shape[0], src.shape[1]), dtype=np.float32)
+map_y = np.zeros((src.shape[0], src.shape[1]), dtype=np.float32)
+## [Create]
+
+## [Window]
+window_name = 'Remap demo'
+cv.namedWindow(window_name)
+## [Window]
+
+## [Loop]
+ind = 0
+while True:
+    update_map(ind, map_x, map_y)
+    ind = (ind + 1) % 4
+    dst = cv.remap(src, map_x, map_y, cv.INTER_LINEAR)
+    cv.imshow(window_name, dst)
+    c = cv.waitKey(1000)
+    if c == 27:
+        break
+## [Loop]

samples/python/tutorial_code/imgProc/threshold/threshold.py

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+from __future__ import print_function
+import cv2 as cv
+import argparse
+
+max_value = 255
+max_type = 4
+max_binary_value = 255
+trackbar_type = 'Type: \n 0: Binary \n 1: Binary Inverted \n 2: Truncate \n 3: To Zero \n 4: To Zero Inverted'
+trackbar_value = 'Value'
+window_name = 'Threshold Demo'
+
+## [Threshold_Demo]
+def Threshold_Demo(val):
+    #0: Binary
+    #1: Binary Inverted
+    #2: Threshold Truncated
+    #3: Threshold to Zero
+    #4: Threshold to Zero Inverted
+    threshold_type = cv.getTrackbarPos(trackbar_type, window_name)
+    threshold_value = cv.getTrackbarPos(trackbar_value, window_name)
+    _, dst = cv.threshold(src_gray, threshold_value, max_binary_value, threshold_type )
+    cv.imshow(window_name, dst)
+## [Threshold_Demo]
+
+parser = argparse.ArgumentParser(description='Code for Basic Thresholding Operations tutorial.')
+parser.add_argument('--input', help='Path to input image.', default='../data/stuff.jpg')
+args = parser.parse_args()
+
+## [load]
+# Load an image
+src = cv.imread(args.input)
+if src is None:
+    print('Could not open or find the image: ', args.input)
+    exit(0)
+# Convert the image to Gray
+src_gray = cv.cvtColor(src, cv.COLOR_BGR2GRAY);
+## [load]
+
+## [window]
+# Create a window to display results
+cv.namedWindow(window_name)
+## [window]
+
+## [trackbar]
+# Create Trackbar to choose type of Threshold
+cv.createTrackbar(trackbar_type, window_name , 3, max_type, Threshold_Demo)
+# Create Trackbar to choose Threshold value
+cv.createTrackbar(trackbar_value, window_name , 0, max_value, Threshold_Demo)
+## [trackbar]
+
+# Call the function to initialize
+Threshold_Demo(0)
+# Wait until user finishes program
+cv.waitKey()

samples/python/tutorial_code/imgProc/threshold_inRange/threshold_inRange.py

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+from __future__ import print_function
+import cv2 as cv
+import argparse
+
+max_value = 255
+max_value_H = 360//2
+low_H = 0
+low_S = 0
+low_V = 0
+high_H = max_value_H
+high_S = max_value
+high_V = max_value
+window_capture_name = 'Video Capture'
+window_detection_name = 'Object Detection'
+low_H_name = 'Low H'
+low_S_name = 'Low S'
+low_V_name = 'Low V'
+high_H_name = 'High H'
+high_S_name = 'High S'
+high_V_name = 'High V'
+
+## [low]
+def on_low_H_thresh_trackbar(val):
+    global low_H
+    global high_H
+    low_H = val
+    low_H = min(high_H-1, low_H)
+    cv.setTrackbarPos(low_H_name, window_detection_name, low_H)
+## [low]
+
+## [high]
+def on_high_H_thresh_trackbar(val):
+    global low_H
+    global high_H
+    high_H = val
+    high_H = max(high_H, low_H+1)
+    cv.setTrackbarPos(high_H_name, window_detection_name, high_H)
+## [high]
+
+def on_low_S_thresh_trackbar(val):
+    global low_S
+    global high_S
+    low_S = val
+    low_S = min(high_S-1, low_S)
+    cv.setTrackbarPos(low_S_name, window_detection_name, low_S)
+
+def on_high_S_thresh_trackbar(val):
+    global low_S
+    global high_S
+    high_S = val
+    high_S = max(high_S, low_S+1)
+    cv.setTrackbarPos(high_S_name, window_detection_name, high_S)
+
+def on_low_V_thresh_trackbar(val):
+    global low_V
+    global high_V
+    low_V = val
+    low_V = min(high_V-1, low_V)
+    cv.setTrackbarPos(low_V_name, window_detection_name, low_V)
+
+def on_high_V_thresh_trackbar(val):
+    global low_V
+    global high_V
+    high_V = val
+    high_V = max(high_V, low_V+1)
+    cv.setTrackbarPos(high_V_name, window_detection_name, high_V)
+
+parser = argparse.ArgumentParser(description='Code for Thresholding Operations using inRange tutorial.')
+parser.add_argument('--camera', help='Camera devide number.', default=0, type=int)
+args = parser.parse_args()
+
+## [cap]
+cap = cv.VideoCapture(args.camera)
+## [cap]
+
+## [window]
+cv.namedWindow(window_capture_name)
+cv.namedWindow(window_detection_name)
+## [window]
+
+## [trackbar]
+cv.createTrackbar(low_H_name, window_detection_name , low_H, max_value_H, on_low_H_thresh_trackbar)
+cv.createTrackbar(high_H_name, window_detection_name , high_H, max_value_H, on_high_H_thresh_trackbar)
+cv.createTrackbar(low_S_name, window_detection_name , low_S, max_value, on_low_S_thresh_trackbar)
+cv.createTrackbar(high_S_name, window_detection_name , high_S, max_value, on_high_S_thresh_trackbar)
+cv.createTrackbar(low_V_name, window_detection_name , low_V, max_value, on_low_V_thresh_trackbar)
+cv.createTrackbar(high_V_name, window_detection_name , high_V, max_value, on_high_V_thresh_trackbar)
+## [trackbar]
+
+while True:
+    ## [while]
+    ret, frame = cap.read()
+    if frame is None:
+        break
+
+    frame_HSV = cv.cvtColor(frame, cv.COLOR_BGR2HSV)
+    frame_threshold = cv.inRange(frame_HSV, (low_H, low_S, low_V), (high_H, high_S, high_V));
+    ## [while]
+
+    ## [show]
+    cv.imshow(window_capture_name, frame)
+    cv.imshow(window_detection_name, frame_threshold)
+    ## [show]
+
+    key = cv.waitKey(30)
+    if key == ord('q') or key == 27:
+        break