Image Processing examples added

sampleImageprocessing/Controll Mouse with a moving object/HSV Color filter.py

@@ -0,0 +1,52 @@
+import cv2
+import numpy as np
+
+def callback(x):
+ pass
+
+cap = cv2.VideoCapture(0)
+cv2.namedWindow('image')
+
+ilowH = 0
+ihighH = 179
+
+ilowS = 0
+ihighS = 255
+ilowV = 0
+ihighV = 255
+
+cv2.createTrackbar('lowH','image',ilowH,179,callback)
+cv2.createTrackbar('highH','image',ihighH,179,callback)
+cv2.createTrackbar('lowS','image',ilowS,255,callback)
+cv2.createTrackbar('highS','image',ihighS,255,callback)
+cv2.createTrackbar('lowV','image',ilowV,255,callback)
+cv2.createTrackbar('highV','image',ihighV,255,callback)
+
+
+
+while(True):
+ ret, frame = cap.read()
+ ilowH = cv2.getTrackbarPos('lowH', 'image')
+ ihighH = cv2.getTrackbarPos('highH', 'image')
+ ilowS = cv2.getTrackbarPos('lowS', 'image')
+ ihighS = cv2.getTrackbarPos('highS', 'image')
+ ilowV = cv2.getTrackbarPos('lowV', 'image')
+ ihighV = cv2.getTrackbarPos('highV', 'image')
+
+ hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
+
+ lower_hsv = np.array([ilowH, ilowS, ilowV])
+ higher_hsv = np.array([ihighH, ihighS, ihighV])
+ mask = cv2.inRange(hsv, lower_hsv, higher_hsv)
+ mask = cv2.erode(mask, None, iterations=6)
+ mask = cv2.dilate(mask, None, iterations=6)
+ frame = cv2.bitwise_and(frame, frame, mask=mask)
+
+ cv2.imshow('image', frame)
+ k = cv2.waitKey(1000) & 0xFF # large wait time to remove freezing
+ if k == 113 or k == 27:
+ break
+
+
+cv2.destroyAllWindows()
+cap.release()

sampleImageprocessing/Controll Mouse with a moving object/Mouse.py

@@ -0,0 +1,47 @@
+import cv2
+import numpy as np
+
+import win32api
+global cam
+cam = cv2.VideoCapture(0)
+
+def diffImg(t0, t1, t2):
+ d1 = cv2.absdiff(t2, t1)
+ d2 = cv2.absdiff(t1, t0)
+ return cv2.bitwise_and(d1, d2)
+def main():
+ global cam
+ t_minus = cv2.cvtColor(cam.read()[1], cv2.COLOR_RGB2GRAY)
+ t = cv2.cvtColor(cam.read()[1], cv2.COLOR_RGB2GRAY)
+ t_plus = cv2.cvtColor(cam.read()[1], cv2.COLOR_RGB2GRAY)
+ while True:
+ ret, frame = cam.read()
+ hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
+ lower_hsv = np.array([0, 130, 147])
+ higher_hsv = np.array([22, 255, 215])
+ mask = cv2.inRange(hsv, lower_hsv, higher_hsv)
+ mask = cv2.erode(mask, None, iterations=5)
+ mask = cv2.dilate(mask, None, iterations=5)
+ cnts = cv2.findContours(mask.copy(), cv2.RETR_EXTERNAL,
+ cv2.CHAIN_APPROX_SIMPLE)
+ cnt=cnts[0]
+ if len(cnts)>0:
+ x,y,w,h = cv2.boundingRect(cnt)
+ xx,yy=(2*x+w)/2 , (2*y+h)/2
+ if xx>0 and xx<1366 and yy>0 and yy<768:
+ win32api.SetCursorPos((1366-(xx*3),yy*3))
+
+
+ (cnts) = cv2.findContours(mask.copy(), cv2.RETR_EXTERNAL,
+ cv2.CHAIN_APPROX_SIMPLE)
+ t_minus = t
+ t = t_plus
+ t_plus = cv2.cvtColor(cam.read()[1], cv2.COLOR_RGB2GRAY)
+ cv2.imshow("Mouse", frame)
+ key = cv2.waitKey(10)
+ if key == 27:
+ cv2.destroyWindow(winName)
+ break
+main()
+
+

sampleImageprocessing/Controll Mouse with a moving object/README.md

@@ -0,0 +1,11 @@
+# ImageProcessing
+Image Processing projects With OpenCV Python.
+
+This Program can control mouse cursor with a moving object.It detects the onject by its color.
+Use "HSV Color filter.py" to filter the object.
+Then Edit "Mouse.py" and change the following lines with values HSV values
+
+ lower_hsv = np.array([lowH, lowS,lowV])
+ higher_hsv = np.array([highH, highS, highV])
+
+Save it and RUN!

sampleImageprocessing/Hand Detection/Finger Detect.py

@@ -0,0 +1,90 @@
+import numpy as np
+import cv2
+from math import *
+def diffImg(t0, t1, t2):
+ d1 = cv2.absdiff(t2, t1)
+ d2 = cv2.absdiff(t1, t0)
+ return cv2.bitwise_and(d1, d2)
+
+cap = cv2.VideoCapture(0)
+nl,pl=[0,0,0,0,0],[0,0,0,0,0]
+jjjj=[0,0,0,0,0]
+while(1):
+ ret, frame = cap.read()
+ crop_frame = frame[0:300, 0:300]
+ gray_image = cv2.cvtColor(crop_frame, cv2.COLOR_BGR2GRAY)
+ ret, mask = cv2.threshold(gray_image, 145, 255, cv2.THRESH_BINARY)
+ mask_inv = cv2.bitwise_not(mask)
+ mask_inv = cv2.erode(mask_inv, None, iterations=1)
+ mask_inv = cv2.dilate(mask_inv, None, iterations=1)
+ drawing=mask_inv
+ ret,thresh = cv2.threshold(mask_inv,127,255,0)
+ im2,contours,hierarchy = cv2.findContours(thresh, 1, 2)
+ cv2.rectangle(frame, (0, 0), (300, 300), (255,0,0), 2)
+
+
+ if len (contours)>0:
+ max_area=100
+ ci=0	
+ for i in range(len(contours)):
+ cnt=contours[i]
+ area = cv2.contourArea(cnt)
+ if(area>max_area):
+ max_area=area
+ ci=i 
+
+ #Largest area contour 
+ cnts = contours[ci]
+ M = cv2.moments(cnts)
+ cX = int(M["m10"] / M["m00"])
+ cY = int(M["m01"] / M["m00"])
+ cv2.circle(frame,(cX,cY),10,[100,255,255],3)
+ hull = cv2.convexHull(cnts)
+ hull2 = cv2.convexHull(cnts,returnPoints = False)
+ defects = cv2.convexityDefects(cnts,hull2)
+ FarDefect = []
+
+ try:
+ ccc=0
+ for i in range(defects.shape[0]):
+ s,e,f,d = defects[i,0]
+ start = tuple(cnts[s][0])
+ end = tuple(cnts[e][0])
+ far = tuple(cnts[f][0])
+ dist = sqrt( (start[0] - end[0])**2 + (start[1] - end[1])**2 )
+
+ if 1:
+ FarDefect.append(far)
+ #print end[0]-far[0],far[1]-end[1]
+ a=sqrt((far[0]-end[0])**2+ (end[1]-far[1])**2)
+ b=sqrt((start[0]-far[0])**2+ (start[1]-far[1])**2)
+ c=sqrt((start[1]-end[1])**2+(start[0]-end[0])**2)
+ angle=(a**2+b**2-c**2)/(2*a*b)
+ angle=acos(angle)
+
+ if (angle*180)/(22/7)<90 and dist>10:
+ cv2.line(frame,(cX,cY),end,[125,255,0],1)
+ cv2.line(frame,(cX,cY),end,[125,255,0] ,1)
+ cv2.circle(frame,end,10,[100,255,255],3)
+ cv2.line(frame,(cX,cY),end,[125,255,0],1) 
+ cv2.circle(frame,end,10,[100,255,255],3)
+
+ except Exception as e:
+ pass
+
+ cv2.imshow('Dilation',drawing)
+
+ frame = cv2.resize(frame, (1366, 765), interpolation=cv2.INTER_CUBIC)
+ cv2.imshow('frame',frame)
+
+ #cv2.imshow('cropped frame',crop_frame)
+ cv2.imshow('grey cropped frame',gray_image)
+ cv2.imshow('t',mask)
+ cv2.imshow('t2',mask_inv)
+ #cv2.imshow('drawing',drawing)
+
+ if cv2.waitKey(1) & 0xFF == ord('q'):
+ break
+
+cap.release()
+cv2.destroyAllWindows()

sampleImageprocessing/Hand Detection/README.md

@@ -0,0 +1,9 @@
+# ImageProcessing
+Image Processing projects With OpenCV Python.
+
+This program identifies fingers of one hand.Just run "Finger Detect.py" and you can seea blue rectangle on the top left.
+Make that area with a light color background and bring your one hand to that area.
+
+See this video
+
+https://vimeo.com/228470426

sampleImageprocessing/Object Detect By Color/HSV Color filter.py

@@ -0,0 +1,52 @@
+import cv2
+import numpy as np
+
+def callback(x):
+ pass
+
+cap = cv2.VideoCapture(0)
+cv2.namedWindow('image')
+
+ilowH = 0
+ihighH = 179
+
+ilowS = 0
+ihighS = 255
+ilowV = 0
+ihighV = 255
+
+cv2.createTrackbar('lowH','image',ilowH,179,callback)
+cv2.createTrackbar('highH','image',ihighH,179,callback)
+cv2.createTrackbar('lowS','image',ilowS,255,callback)
+cv2.createTrackbar('highS','image',ihighS,255,callback)
+cv2.createTrackbar('lowV','image',ilowV,255,callback)
+cv2.createTrackbar('highV','image',ihighV,255,callback)
+
+
+
+while(True):
+ ret, frame = cap.read()
+ ilowH = cv2.getTrackbarPos('lowH', 'image')
+ ihighH = cv2.getTrackbarPos('highH', 'image')
+ ilowS = cv2.getTrackbarPos('lowS', 'image')
+ ihighS = cv2.getTrackbarPos('highS', 'image')
+ ilowV = cv2.getTrackbarPos('lowV', 'image')
+ ihighV = cv2.getTrackbarPos('highV', 'image')
+
+ hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
+
+ lower_hsv = np.array([ilowH, ilowS, ilowV])
+ higher_hsv = np.array([ihighH, ihighS, ihighV])
+ mask = cv2.inRange(hsv, lower_hsv, higher_hsv)
+ mask = cv2.erode(mask, None, iterations=6)
+ mask = cv2.dilate(mask, None, iterations=6)
+ frame = cv2.bitwise_and(frame, frame, mask=mask)
+
+ cv2.imshow('image', frame)
+ k = cv2.waitKey(1000) & 0xFF # large wait time to remove freezing
+ if k == 113 or k == 27:
+ break
+
+
+cv2.destroyAllWindows()
+cap.release()

sampleImageprocessing/Object Detect By Color/README.md

@@ -0,0 +1,11 @@
+# ImageProcessing
+Image Processing projects With OpenCV Python 
+
+
+Run "HSV Color filter.py" and filter the object color you want to detect.
+Then edit "object detect by color.py" and change the following lines with values HSV values
+
+ lower_hsv = np.array([lowH, lowS,lowV])
+ higher_hsv = np.array([highH, highS, highV])
+
+Save it and RUN!

sampleImageprocessing/Object Detect By Color/object detect by color.py

@@ -0,0 +1,33 @@
+import numpy as np
+import cv2
+
+cap = cv2.VideoCapture(0)
+dd=True
+while(dd):
+ ret, frame = cap.read()
+ fg=frame
+ hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
+ lower_hsv = np.array([0, 163, 182])
+ higher_hsv = np.array([110, 255, 254])
+ mask = cv2.inRange(hsv, lower_hsv, higher_hsv)
+ mask = cv2.erode(mask, None, iterations=2)
+ mask = cv2.dilate(mask, None, iterations=2)
+
+ cnts = cv2.findContours(mask.copy(), cv2.RETR_EXTERNAL,
+ cv2.CHAIN_APPROX_SIMPLE)
+ cnt = cnts[0]
+ M = cv2.moments(cnt)
+ if len(cnts)>0:
+ frame=fg
+
+ x,y,w,h = cv2.boundingRect(cnt)
+ cv2.rectangle(frame,(x,y),(x+w,y+h),(0,255,0),2)
+
+
+
+ cv2.imshow('frame',frame)
+ if cv2.waitKey(1) & 0xFF == ord('q'):
+ break
+
+cap.release()
+cv2.destroyAllWindows()

sampleImageprocessing/Controll Mouse with a moving object/HSV Color filter.py

@@ -0,0 +1,52 @@
+import cv2
+import numpy as np
+
+def callback(x):
+ pass
+
+cap = cv2.VideoCapture(0)
+cv2.namedWindow('image')
+
+ilowH = 0
+ihighH = 179
+
+ilowS = 0
+ihighS = 255
+ilowV = 0
+ihighV = 255
+
+cv2.createTrackbar('lowH','image',ilowH,179,callback)
+cv2.createTrackbar('highH','image',ihighH,179,callback)
+cv2.createTrackbar('lowS','image',ilowS,255,callback)
+cv2.createTrackbar('highS','image',ihighS,255,callback)
+cv2.createTrackbar('lowV','image',ilowV,255,callback)
+cv2.createTrackbar('highV','image',ihighV,255,callback)
+
+
+
+while(True):
+ ret, frame = cap.read()
+ ilowH = cv2.getTrackbarPos('lowH', 'image')
+ ihighH = cv2.getTrackbarPos('highH', 'image')
+ ilowS = cv2.getTrackbarPos('lowS', 'image')
+ ihighS = cv2.getTrackbarPos('highS', 'image')
+ ilowV = cv2.getTrackbarPos('lowV', 'image')
+ ihighV = cv2.getTrackbarPos('highV', 'image')
+
+ hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
+
+ lower_hsv = np.array([ilowH, ilowS, ilowV])
+ higher_hsv = np.array([ihighH, ihighS, ihighV])
+ mask = cv2.inRange(hsv, lower_hsv, higher_hsv)
+ mask = cv2.erode(mask, None, iterations=6)
+ mask = cv2.dilate(mask, None, iterations=6)
+ frame = cv2.bitwise_and(frame, frame, mask=mask)
+
+ cv2.imshow('image', frame)
+ k = cv2.waitKey(1000) & 0xFF # large wait time to remove freezing
+ if k == 113 or k == 27:
+ break
+
+
+cv2.destroyAllWindows()
+cap.release()

sampleImageprocessing/Controll Mouse with a moving object/Mouse.py

@@ -0,0 +1,47 @@
+import cv2
+import numpy as np
+
+import win32api
+global cam
+cam = cv2.VideoCapture(0)
+
+def diffImg(t0, t1, t2):
+ d1 = cv2.absdiff(t2, t1)
+ d2 = cv2.absdiff(t1, t0)
+ return cv2.bitwise_and(d1, d2)
+def main():
+ global cam
+ t_minus = cv2.cvtColor(cam.read()[1], cv2.COLOR_RGB2GRAY)
+ t = cv2.cvtColor(cam.read()[1], cv2.COLOR_RGB2GRAY)
+ t_plus = cv2.cvtColor(cam.read()[1], cv2.COLOR_RGB2GRAY)
+ while True:
+ ret, frame = cam.read()
+ hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
+ lower_hsv = np.array([0, 130, 147])
+ higher_hsv = np.array([22, 255, 215])
+ mask = cv2.inRange(hsv, lower_hsv, higher_hsv)
+ mask = cv2.erode(mask, None, iterations=5)
+ mask = cv2.dilate(mask, None, iterations=5)
+ cnts = cv2.findContours(mask.copy(), cv2.RETR_EXTERNAL,
+ cv2.CHAIN_APPROX_SIMPLE)
+ cnt=cnts[0]
+ if len(cnts)>0:
+ x,y,w,h = cv2.boundingRect(cnt)
+ xx,yy=(2*x+w)/2 , (2*y+h)/2
+ if xx>0 and xx<1366 and yy>0 and yy<768:
+ win32api.SetCursorPos((1366-(xx*3),yy*3))
+
+
+ (cnts) = cv2.findContours(mask.copy(), cv2.RETR_EXTERNAL,
+ cv2.CHAIN_APPROX_SIMPLE)
+ t_minus = t
+ t = t_plus
+ t_plus = cv2.cvtColor(cam.read()[1], cv2.COLOR_RGB2GRAY)
+ cv2.imshow("Mouse", frame)
+ key = cv2.waitKey(10)
+ if key == 27:
+ cv2.destroyWindow(winName)
+ break
+main()
+
+

sampleImageprocessing/Controll Mouse with a moving object/README.md

@@ -0,0 +1,11 @@
+# ImageProcessing
+Image Processing projects With OpenCV Python.
+
+This Program can control mouse cursor with a moving object.It detects the onject by its color.
+Use "HSV Color filter.py" to filter the object.
+Then Edit "Mouse.py" and change the following lines with values HSV values
+
+ lower_hsv = np.array([lowH, lowS,lowV])
+ higher_hsv = np.array([highH, highS, highV])
+
+Save it and RUN!

sampleImageprocessing/Hand Detection/Finger Detect.py

@@ -0,0 +1,90 @@
+import numpy as np
+import cv2
+from math import *
+def diffImg(t0, t1, t2):
+ d1 = cv2.absdiff(t2, t1)
+ d2 = cv2.absdiff(t1, t0)
+ return cv2.bitwise_and(d1, d2)
+
+cap = cv2.VideoCapture(0)
+nl,pl=[0,0,0,0,0],[0,0,0,0,0]
+jjjj=[0,0,0,0,0]
+while(1):
+ ret, frame = cap.read()
+ crop_frame = frame[0:300, 0:300]
+ gray_image = cv2.cvtColor(crop_frame, cv2.COLOR_BGR2GRAY)
+ ret, mask = cv2.threshold(gray_image, 145, 255, cv2.THRESH_BINARY)
+ mask_inv = cv2.bitwise_not(mask)
+ mask_inv = cv2.erode(mask_inv, None, iterations=1)
+ mask_inv = cv2.dilate(mask_inv, None, iterations=1)
+ drawing=mask_inv
+ ret,thresh = cv2.threshold(mask_inv,127,255,0)
+ im2,contours,hierarchy = cv2.findContours(thresh, 1, 2)
+ cv2.rectangle(frame, (0, 0), (300, 300), (255,0,0), 2)
+
+
+ if len (contours)>0:
+ max_area=100
+ ci=0	
+ for i in range(len(contours)):
+ cnt=contours[i]
+ area = cv2.contourArea(cnt)
+ if(area>max_area):
+ max_area=area
+ ci=i 
+
+ #Largest area contour 
+ cnts = contours[ci]
+ M = cv2.moments(cnts)
+ cX = int(M["m10"] / M["m00"])
+ cY = int(M["m01"] / M["m00"])
+ cv2.circle(frame,(cX,cY),10,[100,255,255],3)
+ hull = cv2.convexHull(cnts)
+ hull2 = cv2.convexHull(cnts,returnPoints = False)
+ defects = cv2.convexityDefects(cnts,hull2)
+ FarDefect = []
+
+ try:
+ ccc=0
+ for i in range(defects.shape[0]):
+ s,e,f,d = defects[i,0]
+ start = tuple(cnts[s][0])
+ end = tuple(cnts[e][0])
+ far = tuple(cnts[f][0])
+ dist = sqrt( (start[0] - end[0])**2 + (start[1] - end[1])**2 )
+
+ if 1:
+ FarDefect.append(far)
+ #print end[0]-far[0],far[1]-end[1]
+ a=sqrt((far[0]-end[0])**2+ (end[1]-far[1])**2)
+ b=sqrt((start[0]-far[0])**2+ (start[1]-far[1])**2)
+ c=sqrt((start[1]-end[1])**2+(start[0]-end[0])**2)
+ angle=(a**2+b**2-c**2)/(2*a*b)
+ angle=acos(angle)
+
+ if (angle*180)/(22/7)<90 and dist>10:
+ cv2.line(frame,(cX,cY),end,[125,255,0],1)
+ cv2.line(frame,(cX,cY),end,[125,255,0] ,1)
+ cv2.circle(frame,end,10,[100,255,255],3)
+ cv2.line(frame,(cX,cY),end,[125,255,0],1) 
+ cv2.circle(frame,end,10,[100,255,255],3)
+
+ except Exception as e:
+ pass
+
+ cv2.imshow('Dilation',drawing)
+
+ frame = cv2.resize(frame, (1366, 765), interpolation=cv2.INTER_CUBIC)
+ cv2.imshow('frame',frame)
+
+ #cv2.imshow('cropped frame',crop_frame)
+ cv2.imshow('grey cropped frame',gray_image)
+ cv2.imshow('t',mask)
+ cv2.imshow('t2',mask_inv)
+ #cv2.imshow('drawing',drawing)
+
+ if cv2.waitKey(1) & 0xFF == ord('q'):
+ break
+
+cap.release()
+cv2.destroyAllWindows()

sampleImageprocessing/Hand Detection/README.md

@@ -0,0 +1,9 @@
+# ImageProcessing
+Image Processing projects With OpenCV Python.
+
+This program identifies fingers of one hand.Just run "Finger Detect.py" and you can seea blue rectangle on the top left.
+Make that area with a light color background and bring your one hand to that area.
+
+See this video
+
+https://vimeo.com/228470426

sampleImageprocessing/Object Detect By Color/HSV Color filter.py

@@ -0,0 +1,52 @@
+import cv2
+import numpy as np
+
+def callback(x):
+ pass
+
+cap = cv2.VideoCapture(0)
+cv2.namedWindow('image')
+
+ilowH = 0
+ihighH = 179
+
+ilowS = 0
+ihighS = 255
+ilowV = 0
+ihighV = 255
+
+cv2.createTrackbar('lowH','image',ilowH,179,callback)
+cv2.createTrackbar('highH','image',ihighH,179,callback)
+cv2.createTrackbar('lowS','image',ilowS,255,callback)
+cv2.createTrackbar('highS','image',ihighS,255,callback)
+cv2.createTrackbar('lowV','image',ilowV,255,callback)
+cv2.createTrackbar('highV','image',ihighV,255,callback)
+
+
+
+while(True):
+ ret, frame = cap.read()
+ ilowH = cv2.getTrackbarPos('lowH', 'image')
+ ihighH = cv2.getTrackbarPos('highH', 'image')
+ ilowS = cv2.getTrackbarPos('lowS', 'image')
+ ihighS = cv2.getTrackbarPos('highS', 'image')
+ ilowV = cv2.getTrackbarPos('lowV', 'image')
+ ihighV = cv2.getTrackbarPos('highV', 'image')
+
+ hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
+
+ lower_hsv = np.array([ilowH, ilowS, ilowV])
+ higher_hsv = np.array([ihighH, ihighS, ihighV])
+ mask = cv2.inRange(hsv, lower_hsv, higher_hsv)
+ mask = cv2.erode(mask, None, iterations=6)
+ mask = cv2.dilate(mask, None, iterations=6)
+ frame = cv2.bitwise_and(frame, frame, mask=mask)
+
+ cv2.imshow('image', frame)
+ k = cv2.waitKey(1000) & 0xFF # large wait time to remove freezing
+ if k == 113 or k == 27:
+ break
+
+
+cv2.destroyAllWindows()
+cap.release()

sampleImageprocessing/Object Detect By Color/README.md

@@ -0,0 +1,11 @@
+# ImageProcessing
+Image Processing projects With OpenCV Python 
+
+
+Run "HSV Color filter.py" and filter the object color you want to detect.
+Then edit "object detect by color.py" and change the following lines with values HSV values
+
+ lower_hsv = np.array([lowH, lowS,lowV])
+ higher_hsv = np.array([highH, highS, highV])
+
+Save it and RUN!

sampleImageprocessing/Object Detect By Color/object detect by color.py

@@ -0,0 +1,33 @@
+import numpy as np
+import cv2
+
+cap = cv2.VideoCapture(0)
+dd=True
+while(dd):
+ ret, frame = cap.read()
+ fg=frame
+ hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
+ lower_hsv = np.array([0, 163, 182])
+ higher_hsv = np.array([110, 255, 254])
+ mask = cv2.inRange(hsv, lower_hsv, higher_hsv)
+ mask = cv2.erode(mask, None, iterations=2)
+ mask = cv2.dilate(mask, None, iterations=2)
+
+ cnts = cv2.findContours(mask.copy(), cv2.RETR_EXTERNAL,
+ cv2.CHAIN_APPROX_SIMPLE)
+ cnt = cnts[0]
+ M = cv2.moments(cnt)
+ if len(cnts)>0:
+ frame=fg
+
+ x,y,w,h = cv2.boundingRect(cnt)
+ cv2.rectangle(frame,(x,y),(x+w,y+h),(0,255,0),2)
+
+
+
+ cv2.imshow('frame',frame)
+ if cv2.waitKey(1) & 0xFF == ord('q'):
+ break
+
+cap.release()
+cv2.destroyAllWindows()

sampleImageprocessing/Controll Mouse with a moving object/HSV Color filter.py

@@ -0,0 +1,52 @@
+import cv2
+import numpy as np
+
+def callback(x):
+ pass
+
+cap = cv2.VideoCapture(0)
+cv2.namedWindow('image')
+
+ilowH = 0
+ihighH = 179
+
+ilowS = 0
+ihighS = 255
+ilowV = 0
+ihighV = 255
+
+cv2.createTrackbar('lowH','image',ilowH,179,callback)
+cv2.createTrackbar('highH','image',ihighH,179,callback)
+cv2.createTrackbar('lowS','image',ilowS,255,callback)
+cv2.createTrackbar('highS','image',ihighS,255,callback)
+cv2.createTrackbar('lowV','image',ilowV,255,callback)
+cv2.createTrackbar('highV','image',ihighV,255,callback)
+
+
+
+while(True):
+ ret, frame = cap.read()
+ ilowH = cv2.getTrackbarPos('lowH', 'image')
+ ihighH = cv2.getTrackbarPos('highH', 'image')
+ ilowS = cv2.getTrackbarPos('lowS', 'image')
+ ihighS = cv2.getTrackbarPos('highS', 'image')
+ ilowV = cv2.getTrackbarPos('lowV', 'image')
+ ihighV = cv2.getTrackbarPos('highV', 'image')
+
+ hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
+
+ lower_hsv = np.array([ilowH, ilowS, ilowV])
+ higher_hsv = np.array([ihighH, ihighS, ihighV])
+ mask = cv2.inRange(hsv, lower_hsv, higher_hsv)
+ mask = cv2.erode(mask, None, iterations=6)
+ mask = cv2.dilate(mask, None, iterations=6)
+ frame = cv2.bitwise_and(frame, frame, mask=mask)
+
+ cv2.imshow('image', frame)
+ k = cv2.waitKey(1000) & 0xFF # large wait time to remove freezing
+ if k == 113 or k == 27:
+ break
+
+
+cv2.destroyAllWindows()
+cap.release()

sampleImageprocessing/Controll Mouse with a moving object/Mouse.py

@@ -0,0 +1,47 @@
+import cv2
+import numpy as np
+
+import win32api
+global cam
+cam = cv2.VideoCapture(0)
+
+def diffImg(t0, t1, t2):
+ d1 = cv2.absdiff(t2, t1)
+ d2 = cv2.absdiff(t1, t0)
+ return cv2.bitwise_and(d1, d2)
+def main():
+ global cam
+ t_minus = cv2.cvtColor(cam.read()[1], cv2.COLOR_RGB2GRAY)
+ t = cv2.cvtColor(cam.read()[1], cv2.COLOR_RGB2GRAY)
+ t_plus = cv2.cvtColor(cam.read()[1], cv2.COLOR_RGB2GRAY)
+ while True:
+ ret, frame = cam.read()
+ hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
+ lower_hsv = np.array([0, 130, 147])
+ higher_hsv = np.array([22, 255, 215])
+ mask = cv2.inRange(hsv, lower_hsv, higher_hsv)
+ mask = cv2.erode(mask, None, iterations=5)
+ mask = cv2.dilate(mask, None, iterations=5)
+ cnts = cv2.findContours(mask.copy(), cv2.RETR_EXTERNAL,
+ cv2.CHAIN_APPROX_SIMPLE)
+ cnt=cnts[0]
+ if len(cnts)>0:
+ x,y,w,h = cv2.boundingRect(cnt)
+ xx,yy=(2*x+w)/2 , (2*y+h)/2
+ if xx>0 and xx<1366 and yy>0 and yy<768:
+ win32api.SetCursorPos((1366-(xx*3),yy*3))
+
+
+ (cnts) = cv2.findContours(mask.copy(), cv2.RETR_EXTERNAL,
+ cv2.CHAIN_APPROX_SIMPLE)
+ t_minus = t
+ t = t_plus
+ t_plus = cv2.cvtColor(cam.read()[1], cv2.COLOR_RGB2GRAY)
+ cv2.imshow("Mouse", frame)
+ key = cv2.waitKey(10)
+ if key == 27:
+ cv2.destroyWindow(winName)
+ break
+main()
+
+

sampleImageprocessing/Controll Mouse with a moving object/README.md

@@ -0,0 +1,11 @@
+# ImageProcessing
+Image Processing projects With OpenCV Python.
+
+This Program can control mouse cursor with a moving object.It detects the onject by its color.
+Use "HSV Color filter.py" to filter the object.
+Then Edit "Mouse.py" and change the following lines with values HSV values
+
+ lower_hsv = np.array([lowH, lowS,lowV])
+ higher_hsv = np.array([highH, highS, highV])
+
+Save it and RUN!

sampleImageprocessing/Hand Detection/Finger Detect.py

@@ -0,0 +1,90 @@
+import numpy as np
+import cv2
+from math import *
+def diffImg(t0, t1, t2):
+ d1 = cv2.absdiff(t2, t1)
+ d2 = cv2.absdiff(t1, t0)
+ return cv2.bitwise_and(d1, d2)
+
+cap = cv2.VideoCapture(0)
+nl,pl=[0,0,0,0,0],[0,0,0,0,0]
+jjjj=[0,0,0,0,0]
+while(1):
+ ret, frame = cap.read()
+ crop_frame = frame[0:300, 0:300]
+ gray_image = cv2.cvtColor(crop_frame, cv2.COLOR_BGR2GRAY)
+ ret, mask = cv2.threshold(gray_image, 145, 255, cv2.THRESH_BINARY)
+ mask_inv = cv2.bitwise_not(mask)
+ mask_inv = cv2.erode(mask_inv, None, iterations=1)
+ mask_inv = cv2.dilate(mask_inv, None, iterations=1)
+ drawing=mask_inv
+ ret,thresh = cv2.threshold(mask_inv,127,255,0)
+ im2,contours,hierarchy = cv2.findContours(thresh, 1, 2)
+ cv2.rectangle(frame, (0, 0), (300, 300), (255,0,0), 2)
+
+
+ if len (contours)>0:
+ max_area=100
+ ci=0	
+ for i in range(len(contours)):
+ cnt=contours[i]
+ area = cv2.contourArea(cnt)
+ if(area>max_area):
+ max_area=area
+ ci=i 
+
+ #Largest area contour 
+ cnts = contours[ci]
+ M = cv2.moments(cnts)
+ cX = int(M["m10"] / M["m00"])
+ cY = int(M["m01"] / M["m00"])
+ cv2.circle(frame,(cX,cY),10,[100,255,255],3)
+ hull = cv2.convexHull(cnts)
+ hull2 = cv2.convexHull(cnts,returnPoints = False)
+ defects = cv2.convexityDefects(cnts,hull2)
+ FarDefect = []
+
+ try:
+ ccc=0
+ for i in range(defects.shape[0]):
+ s,e,f,d = defects[i,0]
+ start = tuple(cnts[s][0])
+ end = tuple(cnts[e][0])
+ far = tuple(cnts[f][0])
+ dist = sqrt( (start[0] - end[0])**2 + (start[1] - end[1])**2 )
+
+ if 1:
+ FarDefect.append(far)
+ #print end[0]-far[0],far[1]-end[1]
+ a=sqrt((far[0]-end[0])**2+ (end[1]-far[1])**2)
+ b=sqrt((start[0]-far[0])**2+ (start[1]-far[1])**2)
+ c=sqrt((start[1]-end[1])**2+(start[0]-end[0])**2)
+ angle=(a**2+b**2-c**2)/(2*a*b)
+ angle=acos(angle)
+
+ if (angle*180)/(22/7)<90 and dist>10:
+ cv2.line(frame,(cX,cY),end,[125,255,0],1)
+ cv2.line(frame,(cX,cY),end,[125,255,0] ,1)
+ cv2.circle(frame,end,10,[100,255,255],3)
+ cv2.line(frame,(cX,cY),end,[125,255,0],1) 
+ cv2.circle(frame,end,10,[100,255,255],3)
+
+ except Exception as e:
+ pass
+
+ cv2.imshow('Dilation',drawing)
+
+ frame = cv2.resize(frame, (1366, 765), interpolation=cv2.INTER_CUBIC)
+ cv2.imshow('frame',frame)
+
+ #cv2.imshow('cropped frame',crop_frame)
+ cv2.imshow('grey cropped frame',gray_image)
+ cv2.imshow('t',mask)
+ cv2.imshow('t2',mask_inv)
+ #cv2.imshow('drawing',drawing)
+
+ if cv2.waitKey(1) & 0xFF == ord('q'):
+ break
+
+cap.release()
+cv2.destroyAllWindows()

sampleImageprocessing/Hand Detection/README.md

@@ -0,0 +1,9 @@
+# ImageProcessing
+Image Processing projects With OpenCV Python.
+
+This program identifies fingers of one hand.Just run "Finger Detect.py" and you can seea blue rectangle on the top left.
+Make that area with a light color background and bring your one hand to that area.
+
+See this video
+
+https://vimeo.com/228470426

sampleImageprocessing/Object Detect By Color/HSV Color filter.py

@@ -0,0 +1,52 @@
+import cv2
+import numpy as np
+
+def callback(x):
+ pass
+
+cap = cv2.VideoCapture(0)
+cv2.namedWindow('image')
+
+ilowH = 0
+ihighH = 179
+
+ilowS = 0
+ihighS = 255
+ilowV = 0
+ihighV = 255
+
+cv2.createTrackbar('lowH','image',ilowH,179,callback)
+cv2.createTrackbar('highH','image',ihighH,179,callback)
+cv2.createTrackbar('lowS','image',ilowS,255,callback)
+cv2.createTrackbar('highS','image',ihighS,255,callback)
+cv2.createTrackbar('lowV','image',ilowV,255,callback)
+cv2.createTrackbar('highV','image',ihighV,255,callback)
+
+
+
+while(True):
+ ret, frame = cap.read()
+ ilowH = cv2.getTrackbarPos('lowH', 'image')
+ ihighH = cv2.getTrackbarPos('highH', 'image')
+ ilowS = cv2.getTrackbarPos('lowS', 'image')
+ ihighS = cv2.getTrackbarPos('highS', 'image')
+ ilowV = cv2.getTrackbarPos('lowV', 'image')
+ ihighV = cv2.getTrackbarPos('highV', 'image')
+
+ hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
+
+ lower_hsv = np.array([ilowH, ilowS, ilowV])
+ higher_hsv = np.array([ihighH, ihighS, ihighV])
+ mask = cv2.inRange(hsv, lower_hsv, higher_hsv)
+ mask = cv2.erode(mask, None, iterations=6)
+ mask = cv2.dilate(mask, None, iterations=6)
+ frame = cv2.bitwise_and(frame, frame, mask=mask)
+
+ cv2.imshow('image', frame)
+ k = cv2.waitKey(1000) & 0xFF # large wait time to remove freezing
+ if k == 113 or k == 27:
+ break
+
+
+cv2.destroyAllWindows()
+cap.release()

sampleImageprocessing/Object Detect By Color/README.md

@@ -0,0 +1,11 @@
+# ImageProcessing
+Image Processing projects With OpenCV Python 
+
+
+Run "HSV Color filter.py" and filter the object color you want to detect.
+Then edit "object detect by color.py" and change the following lines with values HSV values
+
+ lower_hsv = np.array([lowH, lowS,lowV])
+ higher_hsv = np.array([highH, highS, highV])
+
+Save it and RUN!

sampleImageprocessing/Object Detect By Color/object detect by color.py

@@ -0,0 +1,33 @@
+import numpy as np
+import cv2
+
+cap = cv2.VideoCapture(0)
+dd=True
+while(dd):
+ ret, frame = cap.read()
+ fg=frame
+ hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
+ lower_hsv = np.array([0, 163, 182])
+ higher_hsv = np.array([110, 255, 254])
+ mask = cv2.inRange(hsv, lower_hsv, higher_hsv)
+ mask = cv2.erode(mask, None, iterations=2)
+ mask = cv2.dilate(mask, None, iterations=2)
+
+ cnts = cv2.findContours(mask.copy(), cv2.RETR_EXTERNAL,
+ cv2.CHAIN_APPROX_SIMPLE)
+ cnt = cnts[0]
+ M = cv2.moments(cnt)
+ if len(cnts)>0:
+ frame=fg
+
+ x,y,w,h = cv2.boundingRect(cnt)
+ cv2.rectangle(frame,(x,y),(x+w,y+h),(0,255,0),2)
+
+
+
+ cv2.imshow('frame',frame)
+ if cv2.waitKey(1) & 0xFF == ord('q'):
+ break
+
+cap.release()
+cv2.destroyAllWindows()

sampleImageprocessing/Controll Mouse with a moving object/HSV Color filter.py

@@ -0,0 +1,52 @@
+import cv2
+import numpy as np
+
+def callback(x):
+ pass
+
+cap = cv2.VideoCapture(0)
+cv2.namedWindow('image')
+
+ilowH = 0
+ihighH = 179
+
+ilowS = 0
+ihighS = 255
+ilowV = 0
+ihighV = 255
+
+cv2.createTrackbar('lowH','image',ilowH,179,callback)
+cv2.createTrackbar('highH','image',ihighH,179,callback)
+cv2.createTrackbar('lowS','image',ilowS,255,callback)
+cv2.createTrackbar('highS','image',ihighS,255,callback)
+cv2.createTrackbar('lowV','image',ilowV,255,callback)
+cv2.createTrackbar('highV','image',ihighV,255,callback)
+
+
+
+while(True):
+ ret, frame = cap.read()
+ ilowH = cv2.getTrackbarPos('lowH', 'image')
+ ihighH = cv2.getTrackbarPos('highH', 'image')
+ ilowS = cv2.getTrackbarPos('lowS', 'image')
+ ihighS = cv2.getTrackbarPos('highS', 'image')
+ ilowV = cv2.getTrackbarPos('lowV', 'image')
+ ihighV = cv2.getTrackbarPos('highV', 'image')
+
+ hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
+
+ lower_hsv = np.array([ilowH, ilowS, ilowV])
+ higher_hsv = np.array([ihighH, ihighS, ihighV])
+ mask = cv2.inRange(hsv, lower_hsv, higher_hsv)
+ mask = cv2.erode(mask, None, iterations=6)
+ mask = cv2.dilate(mask, None, iterations=6)
+ frame = cv2.bitwise_and(frame, frame, mask=mask)
+
+ cv2.imshow('image', frame)
+ k = cv2.waitKey(1000) & 0xFF # large wait time to remove freezing
+ if k == 113 or k == 27:
+ break
+
+
+cv2.destroyAllWindows()
+cap.release()

sampleImageprocessing/Controll Mouse with a moving object/Mouse.py

@@ -0,0 +1,47 @@
+import cv2
+import numpy as np
+
+import win32api
+global cam
+cam = cv2.VideoCapture(0)
+
+def diffImg(t0, t1, t2):
+ d1 = cv2.absdiff(t2, t1)
+ d2 = cv2.absdiff(t1, t0)
+ return cv2.bitwise_and(d1, d2)
+def main():
+ global cam
+ t_minus = cv2.cvtColor(cam.read()[1], cv2.COLOR_RGB2GRAY)
+ t = cv2.cvtColor(cam.read()[1], cv2.COLOR_RGB2GRAY)
+ t_plus = cv2.cvtColor(cam.read()[1], cv2.COLOR_RGB2GRAY)
+ while True:
+ ret, frame = cam.read()
+ hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
+ lower_hsv = np.array([0, 130, 147])
+ higher_hsv = np.array([22, 255, 215])
+ mask = cv2.inRange(hsv, lower_hsv, higher_hsv)
+ mask = cv2.erode(mask, None, iterations=5)
+ mask = cv2.dilate(mask, None, iterations=5)
+ cnts = cv2.findContours(mask.copy(), cv2.RETR_EXTERNAL,
+ cv2.CHAIN_APPROX_SIMPLE)
+ cnt=cnts[0]
+ if len(cnts)>0:
+ x,y,w,h = cv2.boundingRect(cnt)
+ xx,yy=(2*x+w)/2 , (2*y+h)/2
+ if xx>0 and xx<1366 and yy>0 and yy<768:
+ win32api.SetCursorPos((1366-(xx*3),yy*3))
+
+
+ (cnts) = cv2.findContours(mask.copy(), cv2.RETR_EXTERNAL,
+ cv2.CHAIN_APPROX_SIMPLE)
+ t_minus = t
+ t = t_plus
+ t_plus = cv2.cvtColor(cam.read()[1], cv2.COLOR_RGB2GRAY)
+ cv2.imshow("Mouse", frame)
+ key = cv2.waitKey(10)
+ if key == 27:
+ cv2.destroyWindow(winName)
+ break
+main()
+
+

sampleImageprocessing/Controll Mouse with a moving object/README.md

@@ -0,0 +1,11 @@
+# ImageProcessing
+Image Processing projects With OpenCV Python.
+
+This Program can control mouse cursor with a moving object.It detects the onject by its color.
+Use "HSV Color filter.py" to filter the object.
+Then Edit "Mouse.py" and change the following lines with values HSV values
+
+ lower_hsv = np.array([lowH, lowS,lowV])
+ higher_hsv = np.array([highH, highS, highV])
+
+Save it and RUN!

sampleImageprocessing/Hand Detection/Finger Detect.py

@@ -0,0 +1,90 @@
+import numpy as np
+import cv2
+from math import *
+def diffImg(t0, t1, t2):
+ d1 = cv2.absdiff(t2, t1)
+ d2 = cv2.absdiff(t1, t0)
+ return cv2.bitwise_and(d1, d2)
+
+cap = cv2.VideoCapture(0)
+nl,pl=[0,0,0,0,0],[0,0,0,0,0]
+jjjj=[0,0,0,0,0]
+while(1):
+ ret, frame = cap.read()
+ crop_frame = frame[0:300, 0:300]
+ gray_image = cv2.cvtColor(crop_frame, cv2.COLOR_BGR2GRAY)
+ ret, mask = cv2.threshold(gray_image, 145, 255, cv2.THRESH_BINARY)
+ mask_inv = cv2.bitwise_not(mask)
+ mask_inv = cv2.erode(mask_inv, None, iterations=1)
+ mask_inv = cv2.dilate(mask_inv, None, iterations=1)
+ drawing=mask_inv
+ ret,thresh = cv2.threshold(mask_inv,127,255,0)
+ im2,contours,hierarchy = cv2.findContours(thresh, 1, 2)
+ cv2.rectangle(frame, (0, 0), (300, 300), (255,0,0), 2)
+
+
+ if len (contours)>0:
+ max_area=100
+ ci=0	
+ for i in range(len(contours)):
+ cnt=contours[i]
+ area = cv2.contourArea(cnt)
+ if(area>max_area):
+ max_area=area
+ ci=i 
+
+ #Largest area contour 
+ cnts = contours[ci]
+ M = cv2.moments(cnts)
+ cX = int(M["m10"] / M["m00"])
+ cY = int(M["m01"] / M["m00"])
+ cv2.circle(frame,(cX,cY),10,[100,255,255],3)
+ hull = cv2.convexHull(cnts)
+ hull2 = cv2.convexHull(cnts,returnPoints = False)
+ defects = cv2.convexityDefects(cnts,hull2)
+ FarDefect = []
+
+ try:
+ ccc=0
+ for i in range(defects.shape[0]):
+ s,e,f,d = defects[i,0]
+ start = tuple(cnts[s][0])
+ end = tuple(cnts[e][0])
+ far = tuple(cnts[f][0])
+ dist = sqrt( (start[0] - end[0])**2 + (start[1] - end[1])**2 )
+
+ if 1:
+ FarDefect.append(far)
+ #print end[0]-far[0],far[1]-end[1]
+ a=sqrt((far[0]-end[0])**2+ (end[1]-far[1])**2)
+ b=sqrt((start[0]-far[0])**2+ (start[1]-far[1])**2)
+ c=sqrt((start[1]-end[1])**2+(start[0]-end[0])**2)
+ angle=(a**2+b**2-c**2)/(2*a*b)
+ angle=acos(angle)
+
+ if (angle*180)/(22/7)<90 and dist>10:
+ cv2.line(frame,(cX,cY),end,[125,255,0],1)
+ cv2.line(frame,(cX,cY),end,[125,255,0] ,1)
+ cv2.circle(frame,end,10,[100,255,255],3)
+ cv2.line(frame,(cX,cY),end,[125,255,0],1) 
+ cv2.circle(frame,end,10,[100,255,255],3)
+
+ except Exception as e:
+ pass
+
+ cv2.imshow('Dilation',drawing)
+
+ frame = cv2.resize(frame, (1366, 765), interpolation=cv2.INTER_CUBIC)
+ cv2.imshow('frame',frame)
+
+ #cv2.imshow('cropped frame',crop_frame)
+ cv2.imshow('grey cropped frame',gray_image)
+ cv2.imshow('t',mask)
+ cv2.imshow('t2',mask_inv)
+ #cv2.imshow('drawing',drawing)
+
+ if cv2.waitKey(1) & 0xFF == ord('q'):
+ break
+
+cap.release()
+cv2.destroyAllWindows()

sampleImageprocessing/Hand Detection/README.md

@@ -0,0 +1,9 @@
+# ImageProcessing
+Image Processing projects With OpenCV Python.
+
+This program identifies fingers of one hand.Just run "Finger Detect.py" and you can seea blue rectangle on the top left.
+Make that area with a light color background and bring your one hand to that area.
+
+See this video
+
+https://vimeo.com/228470426

sampleImageprocessing/Object Detect By Color/HSV Color filter.py

@@ -0,0 +1,52 @@
+import cv2
+import numpy as np
+
+def callback(x):
+ pass
+
+cap = cv2.VideoCapture(0)
+cv2.namedWindow('image')
+
+ilowH = 0
+ihighH = 179
+
+ilowS = 0
+ihighS = 255
+ilowV = 0
+ihighV = 255
+
+cv2.createTrackbar('lowH','image',ilowH,179,callback)
+cv2.createTrackbar('highH','image',ihighH,179,callback)
+cv2.createTrackbar('lowS','image',ilowS,255,callback)
+cv2.createTrackbar('highS','image',ihighS,255,callback)
+cv2.createTrackbar('lowV','image',ilowV,255,callback)
+cv2.createTrackbar('highV','image',ihighV,255,callback)
+
+
+
+while(True):
+ ret, frame = cap.read()
+ ilowH = cv2.getTrackbarPos('lowH', 'image')
+ ihighH = cv2.getTrackbarPos('highH', 'image')
+ ilowS = cv2.getTrackbarPos('lowS', 'image')
+ ihighS = cv2.getTrackbarPos('highS', 'image')
+ ilowV = cv2.getTrackbarPos('lowV', 'image')
+ ihighV = cv2.getTrackbarPos('highV', 'image')
+
+ hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
+
+ lower_hsv = np.array([ilowH, ilowS, ilowV])
+ higher_hsv = np.array([ihighH, ihighS, ihighV])
+ mask = cv2.inRange(hsv, lower_hsv, higher_hsv)
+ mask = cv2.erode(mask, None, iterations=6)
+ mask = cv2.dilate(mask, None, iterations=6)
+ frame = cv2.bitwise_and(frame, frame, mask=mask)
+
+ cv2.imshow('image', frame)
+ k = cv2.waitKey(1000) & 0xFF # large wait time to remove freezing
+ if k == 113 or k == 27:
+ break
+
+
+cv2.destroyAllWindows()
+cap.release()

sampleImageprocessing/Object Detect By Color/README.md

@@ -0,0 +1,11 @@
+# ImageProcessing
+Image Processing projects With OpenCV Python 
+
+
+Run "HSV Color filter.py" and filter the object color you want to detect.
+Then edit "object detect by color.py" and change the following lines with values HSV values
+
+ lower_hsv = np.array([lowH, lowS,lowV])
+ higher_hsv = np.array([highH, highS, highV])
+
+Save it and RUN!

sampleImageprocessing/Object Detect By Color/object detect by color.py

@@ -0,0 +1,33 @@
+import numpy as np
+import cv2
+
+cap = cv2.VideoCapture(0)
+dd=True
+while(dd):
+ ret, frame = cap.read()
+ fg=frame
+ hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
+ lower_hsv = np.array([0, 163, 182])
+ higher_hsv = np.array([110, 255, 254])
+ mask = cv2.inRange(hsv, lower_hsv, higher_hsv)
+ mask = cv2.erode(mask, None, iterations=2)
+ mask = cv2.dilate(mask, None, iterations=2)
+
+ cnts = cv2.findContours(mask.copy(), cv2.RETR_EXTERNAL,
+ cv2.CHAIN_APPROX_SIMPLE)
+ cnt = cnts[0]
+ M = cv2.moments(cnt)
+ if len(cnts)>0:
+ frame=fg
+
+ x,y,w,h = cv2.boundingRect(cnt)
+ cv2.rectangle(frame,(x,y),(x+w,y+h),(0,255,0),2)
+
+
+
+ cv2.imshow('frame',frame)
+ if cv2.waitKey(1) & 0xFF == ord('q'):
+ break
+
+cap.release()
+cv2.destroyAllWindows()

sampleImageprocessing/Controll Mouse with a moving object/HSV Color filter.py

@@ -0,0 +1,52 @@
+import cv2
+import numpy as np
+
+def callback(x):
+ pass
+
+cap = cv2.VideoCapture(0)
+cv2.namedWindow('image')
+
+ilowH = 0
+ihighH = 179
+
+ilowS = 0
+ihighS = 255
+ilowV = 0
+ihighV = 255
+
+cv2.createTrackbar('lowH','image',ilowH,179,callback)
+cv2.createTrackbar('highH','image',ihighH,179,callback)
+cv2.createTrackbar('lowS','image',ilowS,255,callback)
+cv2.createTrackbar('highS','image',ihighS,255,callback)
+cv2.createTrackbar('lowV','image',ilowV,255,callback)
+cv2.createTrackbar('highV','image',ihighV,255,callback)
+
+
+
+while(True):
+ ret, frame = cap.read()
+ ilowH = cv2.getTrackbarPos('lowH', 'image')
+ ihighH = cv2.getTrackbarPos('highH', 'image')
+ ilowS = cv2.getTrackbarPos('lowS', 'image')
+ ihighS = cv2.getTrackbarPos('highS', 'image')
+ ilowV = cv2.getTrackbarPos('lowV', 'image')
+ ihighV = cv2.getTrackbarPos('highV', 'image')
+
+ hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
+
+ lower_hsv = np.array([ilowH, ilowS, ilowV])
+ higher_hsv = np.array([ihighH, ihighS, ihighV])
+ mask = cv2.inRange(hsv, lower_hsv, higher_hsv)
+ mask = cv2.erode(mask, None, iterations=6)
+ mask = cv2.dilate(mask, None, iterations=6)
+ frame = cv2.bitwise_and(frame, frame, mask=mask)
+
+ cv2.imshow('image', frame)
+ k = cv2.waitKey(1000) & 0xFF # large wait time to remove freezing
+ if k == 113 or k == 27:
+ break
+
+
+cv2.destroyAllWindows()
+cap.release()

sampleImageprocessing/Controll Mouse with a moving object/Mouse.py

@@ -0,0 +1,47 @@
+import cv2
+import numpy as np
+
+import win32api
+global cam
+cam = cv2.VideoCapture(0)
+
+def diffImg(t0, t1, t2):
+ d1 = cv2.absdiff(t2, t1)
+ d2 = cv2.absdiff(t1, t0)
+ return cv2.bitwise_and(d1, d2)
+def main():
+ global cam
+ t_minus = cv2.cvtColor(cam.read()[1], cv2.COLOR_RGB2GRAY)
+ t = cv2.cvtColor(cam.read()[1], cv2.COLOR_RGB2GRAY)
+ t_plus = cv2.cvtColor(cam.read()[1], cv2.COLOR_RGB2GRAY)
+ while True:
+ ret, frame = cam.read()
+ hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
+ lower_hsv = np.array([0, 130, 147])
+ higher_hsv = np.array([22, 255, 215])
+ mask = cv2.inRange(hsv, lower_hsv, higher_hsv)
+ mask = cv2.erode(mask, None, iterations=5)
+ mask = cv2.dilate(mask, None, iterations=5)
+ cnts = cv2.findContours(mask.copy(), cv2.RETR_EXTERNAL,
+ cv2.CHAIN_APPROX_SIMPLE)
+ cnt=cnts[0]
+ if len(cnts)>0:
+ x,y,w,h = cv2.boundingRect(cnt)
+ xx,yy=(2*x+w)/2 , (2*y+h)/2
+ if xx>0 and xx<1366 and yy>0 and yy<768:
+ win32api.SetCursorPos((1366-(xx*3),yy*3))
+
+
+ (cnts) = cv2.findContours(mask.copy(), cv2.RETR_EXTERNAL,
+ cv2.CHAIN_APPROX_SIMPLE)
+ t_minus = t
+ t = t_plus
+ t_plus = cv2.cvtColor(cam.read()[1], cv2.COLOR_RGB2GRAY)
+ cv2.imshow("Mouse", frame)
+ key = cv2.waitKey(10)
+ if key == 27:
+ cv2.destroyWindow(winName)
+ break
+main()
+
+

sampleImageprocessing/Controll Mouse with a moving object/README.md

@@ -0,0 +1,11 @@
+# ImageProcessing
+Image Processing projects With OpenCV Python.
+
+This Program can control mouse cursor with a moving object.It detects the onject by its color.
+Use "HSV Color filter.py" to filter the object.
+Then Edit "Mouse.py" and change the following lines with values HSV values
+
+ lower_hsv = np.array([lowH, lowS,lowV])
+ higher_hsv = np.array([highH, highS, highV])
+
+Save it and RUN!

sampleImageprocessing/Hand Detection/Finger Detect.py

@@ -0,0 +1,90 @@
+import numpy as np
+import cv2
+from math import *
+def diffImg(t0, t1, t2):
+ d1 = cv2.absdiff(t2, t1)
+ d2 = cv2.absdiff(t1, t0)
+ return cv2.bitwise_and(d1, d2)
+
+cap = cv2.VideoCapture(0)
+nl,pl=[0,0,0,0,0],[0,0,0,0,0]
+jjjj=[0,0,0,0,0]
+while(1):
+ ret, frame = cap.read()
+ crop_frame = frame[0:300, 0:300]
+ gray_image = cv2.cvtColor(crop_frame, cv2.COLOR_BGR2GRAY)
+ ret, mask = cv2.threshold(gray_image, 145, 255, cv2.THRESH_BINARY)
+ mask_inv = cv2.bitwise_not(mask)
+ mask_inv = cv2.erode(mask_inv, None, iterations=1)
+ mask_inv = cv2.dilate(mask_inv, None, iterations=1)
+ drawing=mask_inv
+ ret,thresh = cv2.threshold(mask_inv,127,255,0)
+ im2,contours,hierarchy = cv2.findContours(thresh, 1, 2)
+ cv2.rectangle(frame, (0, 0), (300, 300), (255,0,0), 2)
+
+
+ if len (contours)>0:
+ max_area=100
+ ci=0	
+ for i in range(len(contours)):
+ cnt=contours[i]
+ area = cv2.contourArea(cnt)
+ if(area>max_area):
+ max_area=area
+ ci=i 
+
+ #Largest area contour 
+ cnts = contours[ci]
+ M = cv2.moments(cnts)
+ cX = int(M["m10"] / M["m00"])
+ cY = int(M["m01"] / M["m00"])
+ cv2.circle(frame,(cX,cY),10,[100,255,255],3)
+ hull = cv2.convexHull(cnts)
+ hull2 = cv2.convexHull(cnts,returnPoints = False)
+ defects = cv2.convexityDefects(cnts,hull2)
+ FarDefect = []
+
+ try:
+ ccc=0
+ for i in range(defects.shape[0]):
+ s,e,f,d = defects[i,0]
+ start = tuple(cnts[s][0])
+ end = tuple(cnts[e][0])
+ far = tuple(cnts[f][0])
+ dist = sqrt( (start[0] - end[0])**2 + (start[1] - end[1])**2 )
+
+ if 1:
+ FarDefect.append(far)
+ #print end[0]-far[0],far[1]-end[1]
+ a=sqrt((far[0]-end[0])**2+ (end[1]-far[1])**2)
+ b=sqrt((start[0]-far[0])**2+ (start[1]-far[1])**2)
+ c=sqrt((start[1]-end[1])**2+(start[0]-end[0])**2)
+ angle=(a**2+b**2-c**2)/(2*a*b)
+ angle=acos(angle)
+
+ if (angle*180)/(22/7)<90 and dist>10:
+ cv2.line(frame,(cX,cY),end,[125,255,0],1)
+ cv2.line(frame,(cX,cY),end,[125,255,0] ,1)
+ cv2.circle(frame,end,10,[100,255,255],3)
+ cv2.line(frame,(cX,cY),end,[125,255,0],1) 
+ cv2.circle(frame,end,10,[100,255,255],3)
+
+ except Exception as e:
+ pass
+
+ cv2.imshow('Dilation',drawing)
+
+ frame = cv2.resize(frame, (1366, 765), interpolation=cv2.INTER_CUBIC)
+ cv2.imshow('frame',frame)
+
+ #cv2.imshow('cropped frame',crop_frame)
+ cv2.imshow('grey cropped frame',gray_image)
+ cv2.imshow('t',mask)
+ cv2.imshow('t2',mask_inv)
+ #cv2.imshow('drawing',drawing)
+
+ if cv2.waitKey(1) & 0xFF == ord('q'):
+ break
+
+cap.release()
+cv2.destroyAllWindows()

sampleImageprocessing/Hand Detection/README.md

@@ -0,0 +1,9 @@
+# ImageProcessing
+Image Processing projects With OpenCV Python.
+
+This program identifies fingers of one hand.Just run "Finger Detect.py" and you can seea blue rectangle on the top left.
+Make that area with a light color background and bring your one hand to that area.
+
+See this video
+
+https://vimeo.com/228470426

sampleImageprocessing/Object Detect By Color/HSV Color filter.py

@@ -0,0 +1,52 @@
+import cv2
+import numpy as np
+
+def callback(x):
+ pass
+
+cap = cv2.VideoCapture(0)
+cv2.namedWindow('image')
+
+ilowH = 0
+ihighH = 179
+
+ilowS = 0
+ihighS = 255
+ilowV = 0
+ihighV = 255
+
+cv2.createTrackbar('lowH','image',ilowH,179,callback)
+cv2.createTrackbar('highH','image',ihighH,179,callback)
+cv2.createTrackbar('lowS','image',ilowS,255,callback)
+cv2.createTrackbar('highS','image',ihighS,255,callback)
+cv2.createTrackbar('lowV','image',ilowV,255,callback)
+cv2.createTrackbar('highV','image',ihighV,255,callback)
+
+
+
+while(True):
+ ret, frame = cap.read()
+ ilowH = cv2.getTrackbarPos('lowH', 'image')
+ ihighH = cv2.getTrackbarPos('highH', 'image')
+ ilowS = cv2.getTrackbarPos('lowS', 'image')
+ ihighS = cv2.getTrackbarPos('highS', 'image')
+ ilowV = cv2.getTrackbarPos('lowV', 'image')
+ ihighV = cv2.getTrackbarPos('highV', 'image')
+
+ hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
+
+ lower_hsv = np.array([ilowH, ilowS, ilowV])
+ higher_hsv = np.array([ihighH, ihighS, ihighV])
+ mask = cv2.inRange(hsv, lower_hsv, higher_hsv)
+ mask = cv2.erode(mask, None, iterations=6)
+ mask = cv2.dilate(mask, None, iterations=6)
+ frame = cv2.bitwise_and(frame, frame, mask=mask)
+
+ cv2.imshow('image', frame)
+ k = cv2.waitKey(1000) & 0xFF # large wait time to remove freezing
+ if k == 113 or k == 27:
+ break
+
+
+cv2.destroyAllWindows()
+cap.release()

sampleImageprocessing/Object Detect By Color/README.md

@@ -0,0 +1,11 @@
+# ImageProcessing
+Image Processing projects With OpenCV Python 
+
+
+Run "HSV Color filter.py" and filter the object color you want to detect.
+Then edit "object detect by color.py" and change the following lines with values HSV values
+
+ lower_hsv = np.array([lowH, lowS,lowV])
+ higher_hsv = np.array([highH, highS, highV])
+
+Save it and RUN!

sampleImageprocessing/Object Detect By Color/object detect by color.py

@@ -0,0 +1,33 @@
+import numpy as np
+import cv2
+
+cap = cv2.VideoCapture(0)
+dd=True
+while(dd):
+ ret, frame = cap.read()
+ fg=frame
+ hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
+ lower_hsv = np.array([0, 163, 182])
+ higher_hsv = np.array([110, 255, 254])
+ mask = cv2.inRange(hsv, lower_hsv, higher_hsv)
+ mask = cv2.erode(mask, None, iterations=2)
+ mask = cv2.dilate(mask, None, iterations=2)
+
+ cnts = cv2.findContours(mask.copy(), cv2.RETR_EXTERNAL,
+ cv2.CHAIN_APPROX_SIMPLE)
+ cnt = cnts[0]
+ M = cv2.moments(cnt)
+ if len(cnts)>0:
+ frame=fg
+
+ x,y,w,h = cv2.boundingRect(cnt)
+ cv2.rectangle(frame,(x,y),(x+w,y+h),(0,255,0),2)
+
+
+
+ cv2.imshow('frame',frame)
+ if cv2.waitKey(1) & 0xFF == ord('q'):
+ break
+
+cap.release()
+cv2.destroyAllWindows()

sampleImageprocessing/Controll Mouse with a moving object/HSV Color filter.py

@@ -0,0 +1,52 @@
+import cv2
+import numpy as np
+
+def callback(x):
+ pass
+
+cap = cv2.VideoCapture(0)
+cv2.namedWindow('image')
+
+ilowH = 0
+ihighH = 179
+
+ilowS = 0
+ihighS = 255
+ilowV = 0
+ihighV = 255
+
+cv2.createTrackbar('lowH','image',ilowH,179,callback)
+cv2.createTrackbar('highH','image',ihighH,179,callback)
+cv2.createTrackbar('lowS','image',ilowS,255,callback)
+cv2.createTrackbar('highS','image',ihighS,255,callback)
+cv2.createTrackbar('lowV','image',ilowV,255,callback)
+cv2.createTrackbar('highV','image',ihighV,255,callback)
+
+
+
+while(True):
+ ret, frame = cap.read()
+ ilowH = cv2.getTrackbarPos('lowH', 'image')
+ ihighH = cv2.getTrackbarPos('highH', 'image')
+ ilowS = cv2.getTrackbarPos('lowS', 'image')
+ ihighS = cv2.getTrackbarPos('highS', 'image')
+ ilowV = cv2.getTrackbarPos('lowV', 'image')
+ ihighV = cv2.getTrackbarPos('highV', 'image')
+
+ hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
+
+ lower_hsv = np.array([ilowH, ilowS, ilowV])
+ higher_hsv = np.array([ihighH, ihighS, ihighV])
+ mask = cv2.inRange(hsv, lower_hsv, higher_hsv)
+ mask = cv2.erode(mask, None, iterations=6)
+ mask = cv2.dilate(mask, None, iterations=6)
+ frame = cv2.bitwise_and(frame, frame, mask=mask)
+
+ cv2.imshow('image', frame)
+ k = cv2.waitKey(1000) & 0xFF # large wait time to remove freezing
+ if k == 113 or k == 27:
+ break
+
+
+cv2.destroyAllWindows()
+cap.release()

sampleImageprocessing/Controll Mouse with a moving object/Mouse.py

@@ -0,0 +1,47 @@
+import cv2
+import numpy as np
+
+import win32api
+global cam
+cam = cv2.VideoCapture(0)
+
+def diffImg(t0, t1, t2):
+ d1 = cv2.absdiff(t2, t1)
+ d2 = cv2.absdiff(t1, t0)
+ return cv2.bitwise_and(d1, d2)
+def main():
+ global cam
+ t_minus = cv2.cvtColor(cam.read()[1], cv2.COLOR_RGB2GRAY)
+ t = cv2.cvtColor(cam.read()[1], cv2.COLOR_RGB2GRAY)
+ t_plus = cv2.cvtColor(cam.read()[1], cv2.COLOR_RGB2GRAY)
+ while True:
+ ret, frame = cam.read()
+ hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
+ lower_hsv = np.array([0, 130, 147])
+ higher_hsv = np.array([22, 255, 215])
+ mask = cv2.inRange(hsv, lower_hsv, higher_hsv)
+ mask = cv2.erode(mask, None, iterations=5)
+ mask = cv2.dilate(mask, None, iterations=5)
+ cnts = cv2.findContours(mask.copy(), cv2.RETR_EXTERNAL,
+ cv2.CHAIN_APPROX_SIMPLE)
+ cnt=cnts[0]
+ if len(cnts)>0:
+ x,y,w,h = cv2.boundingRect(cnt)
+ xx,yy=(2*x+w)/2 , (2*y+h)/2
+ if xx>0 and xx<1366 and yy>0 and yy<768:
+ win32api.SetCursorPos((1366-(xx*3),yy*3))
+
+
+ (cnts) = cv2.findContours(mask.copy(), cv2.RETR_EXTERNAL,
+ cv2.CHAIN_APPROX_SIMPLE)
+ t_minus = t
+ t = t_plus
+ t_plus = cv2.cvtColor(cam.read()[1], cv2.COLOR_RGB2GRAY)
+ cv2.imshow("Mouse", frame)
+ key = cv2.waitKey(10)
+ if key == 27:
+ cv2.destroyWindow(winName)
+ break
+main()
+
+

sampleImageprocessing/Controll Mouse with a moving object/README.md

@@ -0,0 +1,11 @@
+# ImageProcessing
+Image Processing projects With OpenCV Python.
+
+This Program can control mouse cursor with a moving object.It detects the onject by its color.
+Use "HSV Color filter.py" to filter the object.
+Then Edit "Mouse.py" and change the following lines with values HSV values
+
+ lower_hsv = np.array([lowH, lowS,lowV])
+ higher_hsv = np.array([highH, highS, highV])
+
+Save it and RUN!

sampleImageprocessing/Hand Detection/Finger Detect.py

@@ -0,0 +1,90 @@
+import numpy as np
+import cv2
+from math import *
+def diffImg(t0, t1, t2):
+ d1 = cv2.absdiff(t2, t1)
+ d2 = cv2.absdiff(t1, t0)
+ return cv2.bitwise_and(d1, d2)
+
+cap = cv2.VideoCapture(0)
+nl,pl=[0,0,0,0,0],[0,0,0,0,0]
+jjjj=[0,0,0,0,0]
+while(1):
+ ret, frame = cap.read()
+ crop_frame = frame[0:300, 0:300]
+ gray_image = cv2.cvtColor(crop_frame, cv2.COLOR_BGR2GRAY)
+ ret, mask = cv2.threshold(gray_image, 145, 255, cv2.THRESH_BINARY)
+ mask_inv = cv2.bitwise_not(mask)
+ mask_inv = cv2.erode(mask_inv, None, iterations=1)
+ mask_inv = cv2.dilate(mask_inv, None, iterations=1)
+ drawing=mask_inv
+ ret,thresh = cv2.threshold(mask_inv,127,255,0)
+ im2,contours,hierarchy = cv2.findContours(thresh, 1, 2)
+ cv2.rectangle(frame, (0, 0), (300, 300), (255,0,0), 2)
+
+
+ if len (contours)>0:
+ max_area=100
+ ci=0	
+ for i in range(len(contours)):
+ cnt=contours[i]
+ area = cv2.contourArea(cnt)
+ if(area>max_area):
+ max_area=area
+ ci=i 
+
+ #Largest area contour 
+ cnts = contours[ci]
+ M = cv2.moments(cnts)
+ cX = int(M["m10"] / M["m00"])
+ cY = int(M["m01"] / M["m00"])
+ cv2.circle(frame,(cX,cY),10,[100,255,255],3)
+ hull = cv2.convexHull(cnts)
+ hull2 = cv2.convexHull(cnts,returnPoints = False)
+ defects = cv2.convexityDefects(cnts,hull2)
+ FarDefect = []
+
+ try:
+ ccc=0
+ for i in range(defects.shape[0]):
+ s,e,f,d = defects[i,0]
+ start = tuple(cnts[s][0])
+ end = tuple(cnts[e][0])
+ far = tuple(cnts[f][0])
+ dist = sqrt( (start[0] - end[0])**2 + (start[1] - end[1])**2 )
+
+ if 1:
+ FarDefect.append(far)
+ #print end[0]-far[0],far[1]-end[1]
+ a=sqrt((far[0]-end[0])**2+ (end[1]-far[1])**2)
+ b=sqrt((start[0]-far[0])**2+ (start[1]-far[1])**2)
+ c=sqrt((start[1]-end[1])**2+(start[0]-end[0])**2)
+ angle=(a**2+b**2-c**2)/(2*a*b)
+ angle=acos(angle)
+
+ if (angle*180)/(22/7)<90 and dist>10:
+ cv2.line(frame,(cX,cY),end,[125,255,0],1)
+ cv2.line(frame,(cX,cY),end,[125,255,0] ,1)
+ cv2.circle(frame,end,10,[100,255,255],3)
+ cv2.line(frame,(cX,cY),end,[125,255,0],1) 
+ cv2.circle(frame,end,10,[100,255,255],3)
+
+ except Exception as e:
+ pass
+
+ cv2.imshow('Dilation',drawing)
+
+ frame = cv2.resize(frame, (1366, 765), interpolation=cv2.INTER_CUBIC)
+ cv2.imshow('frame',frame)
+
+ #cv2.imshow('cropped frame',crop_frame)
+ cv2.imshow('grey cropped frame',gray_image)
+ cv2.imshow('t',mask)
+ cv2.imshow('t2',mask_inv)
+ #cv2.imshow('drawing',drawing)
+
+ if cv2.waitKey(1) & 0xFF == ord('q'):
+ break
+
+cap.release()
+cv2.destroyAllWindows()

sampleImageprocessing/Hand Detection/README.md

@@ -0,0 +1,9 @@
+# ImageProcessing
+Image Processing projects With OpenCV Python.
+
+This program identifies fingers of one hand.Just run "Finger Detect.py" and you can seea blue rectangle on the top left.
+Make that area with a light color background and bring your one hand to that area.
+
+See this video
+
+https://vimeo.com/228470426

sampleImageprocessing/Object Detect By Color/HSV Color filter.py

@@ -0,0 +1,52 @@
+import cv2
+import numpy as np
+
+def callback(x):
+ pass
+
+cap = cv2.VideoCapture(0)
+cv2.namedWindow('image')
+
+ilowH = 0
+ihighH = 179
+
+ilowS = 0
+ihighS = 255
+ilowV = 0
+ihighV = 255
+
+cv2.createTrackbar('lowH','image',ilowH,179,callback)
+cv2.createTrackbar('highH','image',ihighH,179,callback)
+cv2.createTrackbar('lowS','image',ilowS,255,callback)
+cv2.createTrackbar('highS','image',ihighS,255,callback)
+cv2.createTrackbar('lowV','image',ilowV,255,callback)
+cv2.createTrackbar('highV','image',ihighV,255,callback)
+
+
+
+while(True):
+ ret, frame = cap.read()
+ ilowH = cv2.getTrackbarPos('lowH', 'image')
+ ihighH = cv2.getTrackbarPos('highH', 'image')
+ ilowS = cv2.getTrackbarPos('lowS', 'image')
+ ihighS = cv2.getTrackbarPos('highS', 'image')
+ ilowV = cv2.getTrackbarPos('lowV', 'image')
+ ihighV = cv2.getTrackbarPos('highV', 'image')
+
+ hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
+
+ lower_hsv = np.array([ilowH, ilowS, ilowV])
+ higher_hsv = np.array([ihighH, ihighS, ihighV])
+ mask = cv2.inRange(hsv, lower_hsv, higher_hsv)
+ mask = cv2.erode(mask, None, iterations=6)
+ mask = cv2.dilate(mask, None, iterations=6)
+ frame = cv2.bitwise_and(frame, frame, mask=mask)
+
+ cv2.imshow('image', frame)
+ k = cv2.waitKey(1000) & 0xFF # large wait time to remove freezing
+ if k == 113 or k == 27:
+ break
+
+
+cv2.destroyAllWindows()
+cap.release()

sampleImageprocessing/Object Detect By Color/README.md

@@ -0,0 +1,11 @@
+# ImageProcessing
+Image Processing projects With OpenCV Python 
+
+
+Run "HSV Color filter.py" and filter the object color you want to detect.
+Then edit "object detect by color.py" and change the following lines with values HSV values
+
+ lower_hsv = np.array([lowH, lowS,lowV])
+ higher_hsv = np.array([highH, highS, highV])
+
+Save it and RUN!

sampleImageprocessing/Object Detect By Color/object detect by color.py

@@ -0,0 +1,33 @@
+import numpy as np
+import cv2
+
+cap = cv2.VideoCapture(0)
+dd=True
+while(dd):
+ ret, frame = cap.read()
+ fg=frame
+ hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
+ lower_hsv = np.array([0, 163, 182])
+ higher_hsv = np.array([110, 255, 254])
+ mask = cv2.inRange(hsv, lower_hsv, higher_hsv)
+ mask = cv2.erode(mask, None, iterations=2)
+ mask = cv2.dilate(mask, None, iterations=2)
+
+ cnts = cv2.findContours(mask.copy(), cv2.RETR_EXTERNAL,
+ cv2.CHAIN_APPROX_SIMPLE)
+ cnt = cnts[0]
+ M = cv2.moments(cnt)
+ if len(cnts)>0:
+ frame=fg
+
+ x,y,w,h = cv2.boundingRect(cnt)
+ cv2.rectangle(frame,(x,y),(x+w,y+h),(0,255,0),2)
+
+
+
+ cv2.imshow('frame',frame)
+ if cv2.waitKey(1) & 0xFF == ord('q'):
+ break
+
+cap.release()
+cv2.destroyAllWindows()

sampleImageprocessing/Controll Mouse with a moving object/HSV Color filter.py

@@ -0,0 +1,52 @@
+import cv2
+import numpy as np
+
+def callback(x):
+ pass
+
+cap = cv2.VideoCapture(0)
+cv2.namedWindow('image')
+
+ilowH = 0
+ihighH = 179
+
+ilowS = 0
+ihighS = 255
+ilowV = 0
+ihighV = 255
+
+cv2.createTrackbar('lowH','image',ilowH,179,callback)
+cv2.createTrackbar('highH','image',ihighH,179,callback)
+cv2.createTrackbar('lowS','image',ilowS,255,callback)
+cv2.createTrackbar('highS','image',ihighS,255,callback)
+cv2.createTrackbar('lowV','image',ilowV,255,callback)
+cv2.createTrackbar('highV','image',ihighV,255,callback)
+
+
+
+while(True):
+ ret, frame = cap.read()
+ ilowH = cv2.getTrackbarPos('lowH', 'image')
+ ihighH = cv2.getTrackbarPos('highH', 'image')
+ ilowS = cv2.getTrackbarPos('lowS', 'image')
+ ihighS = cv2.getTrackbarPos('highS', 'image')
+ ilowV = cv2.getTrackbarPos('lowV', 'image')
+ ihighV = cv2.getTrackbarPos('highV', 'image')
+
+ hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
+
+ lower_hsv = np.array([ilowH, ilowS, ilowV])
+ higher_hsv = np.array([ihighH, ihighS, ihighV])
+ mask = cv2.inRange(hsv, lower_hsv, higher_hsv)
+ mask = cv2.erode(mask, None, iterations=6)
+ mask = cv2.dilate(mask, None, iterations=6)
+ frame = cv2.bitwise_and(frame, frame, mask=mask)
+
+ cv2.imshow('image', frame)
+ k = cv2.waitKey(1000) & 0xFF # large wait time to remove freezing
+ if k == 113 or k == 27:
+ break
+
+
+cv2.destroyAllWindows()
+cap.release()

sampleImageprocessing/Controll Mouse with a moving object/Mouse.py

@@ -0,0 +1,47 @@
+import cv2
+import numpy as np
+
+import win32api
+global cam
+cam = cv2.VideoCapture(0)
+
+def diffImg(t0, t1, t2):
+ d1 = cv2.absdiff(t2, t1)
+ d2 = cv2.absdiff(t1, t0)
+ return cv2.bitwise_and(d1, d2)
+def main():
+ global cam
+ t_minus = cv2.cvtColor(cam.read()[1], cv2.COLOR_RGB2GRAY)
+ t = cv2.cvtColor(cam.read()[1], cv2.COLOR_RGB2GRAY)
+ t_plus = cv2.cvtColor(cam.read()[1], cv2.COLOR_RGB2GRAY)
+ while True:
+ ret, frame = cam.read()
+ hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
+ lower_hsv = np.array([0, 130, 147])
+ higher_hsv = np.array([22, 255, 215])
+ mask = cv2.inRange(hsv, lower_hsv, higher_hsv)
+ mask = cv2.erode(mask, None, iterations=5)
+ mask = cv2.dilate(mask, None, iterations=5)
+ cnts = cv2.findContours(mask.copy(), cv2.RETR_EXTERNAL,
+ cv2.CHAIN_APPROX_SIMPLE)
+ cnt=cnts[0]
+ if len(cnts)>0:
+ x,y,w,h = cv2.boundingRect(cnt)
+ xx,yy=(2*x+w)/2 , (2*y+h)/2
+ if xx>0 and xx<1366 and yy>0 and yy<768:
+ win32api.SetCursorPos((1366-(xx*3),yy*3))
+
+
+ (cnts) = cv2.findContours(mask.copy(), cv2.RETR_EXTERNAL,
+ cv2.CHAIN_APPROX_SIMPLE)
+ t_minus = t
+ t = t_plus
+ t_plus = cv2.cvtColor(cam.read()[1], cv2.COLOR_RGB2GRAY)
+ cv2.imshow("Mouse", frame)
+ key = cv2.waitKey(10)
+ if key == 27:
+ cv2.destroyWindow(winName)
+ break
+main()
+
+

sampleImageprocessing/Controll Mouse with a moving object/README.md

@@ -0,0 +1,11 @@
+# ImageProcessing
+Image Processing projects With OpenCV Python.
+
+This Program can control mouse cursor with a moving object.It detects the onject by its color.
+Use "HSV Color filter.py" to filter the object.
+Then Edit "Mouse.py" and change the following lines with values HSV values
+
+ lower_hsv = np.array([lowH, lowS,lowV])
+ higher_hsv = np.array([highH, highS, highV])
+
+Save it and RUN!

sampleImageprocessing/Hand Detection/Finger Detect.py

@@ -0,0 +1,90 @@
+import numpy as np
+import cv2
+from math import *
+def diffImg(t0, t1, t2):
+ d1 = cv2.absdiff(t2, t1)
+ d2 = cv2.absdiff(t1, t0)
+ return cv2.bitwise_and(d1, d2)
+
+cap = cv2.VideoCapture(0)
+nl,pl=[0,0,0,0,0],[0,0,0,0,0]
+jjjj=[0,0,0,0,0]
+while(1):
+ ret, frame = cap.read()
+ crop_frame = frame[0:300, 0:300]
+ gray_image = cv2.cvtColor(crop_frame, cv2.COLOR_BGR2GRAY)
+ ret, mask = cv2.threshold(gray_image, 145, 255, cv2.THRESH_BINARY)
+ mask_inv = cv2.bitwise_not(mask)
+ mask_inv = cv2.erode(mask_inv, None, iterations=1)
+ mask_inv = cv2.dilate(mask_inv, None, iterations=1)
+ drawing=mask_inv
+ ret,thresh = cv2.threshold(mask_inv,127,255,0)
+ im2,contours,hierarchy = cv2.findContours(thresh, 1, 2)
+ cv2.rectangle(frame, (0, 0), (300, 300), (255,0,0), 2)
+
+
+ if len (contours)>0:
+ max_area=100
+ ci=0	
+ for i in range(len(contours)):
+ cnt=contours[i]
+ area = cv2.contourArea(cnt)
+ if(area>max_area):
+ max_area=area
+ ci=i 
+
+ #Largest area contour 
+ cnts = contours[ci]
+ M = cv2.moments(cnts)
+ cX = int(M["m10"] / M["m00"])
+ cY = int(M["m01"] / M["m00"])
+ cv2.circle(frame,(cX,cY),10,[100,255,255],3)
+ hull = cv2.convexHull(cnts)
+ hull2 = cv2.convexHull(cnts,returnPoints = False)
+ defects = cv2.convexityDefects(cnts,hull2)
+ FarDefect = []
+
+ try:
+ ccc=0
+ for i in range(defects.shape[0]):
+ s,e,f,d = defects[i,0]
+ start = tuple(cnts[s][0])
+ end = tuple(cnts[e][0])
+ far = tuple(cnts[f][0])
+ dist = sqrt( (start[0] - end[0])**2 + (start[1] - end[1])**2 )
+
+ if 1:
+ FarDefect.append(far)
+ #print end[0]-far[0],far[1]-end[1]
+ a=sqrt((far[0]-end[0])**2+ (end[1]-far[1])**2)
+ b=sqrt((start[0]-far[0])**2+ (start[1]-far[1])**2)
+ c=sqrt((start[1]-end[1])**2+(start[0]-end[0])**2)
+ angle=(a**2+b**2-c**2)/(2*a*b)
+ angle=acos(angle)
+
+ if (angle*180)/(22/7)<90 and dist>10:
+ cv2.line(frame,(cX,cY),end,[125,255,0],1)
+ cv2.line(frame,(cX,cY),end,[125,255,0] ,1)
+ cv2.circle(frame,end,10,[100,255,255],3)
+ cv2.line(frame,(cX,cY),end,[125,255,0],1) 
+ cv2.circle(frame,end,10,[100,255,255],3)
+
+ except Exception as e:
+ pass
+
+ cv2.imshow('Dilation',drawing)
+
+ frame = cv2.resize(frame, (1366, 765), interpolation=cv2.INTER_CUBIC)
+ cv2.imshow('frame',frame)
+
+ #cv2.imshow('cropped frame',crop_frame)
+ cv2.imshow('grey cropped frame',gray_image)
+ cv2.imshow('t',mask)
+ cv2.imshow('t2',mask_inv)
+ #cv2.imshow('drawing',drawing)
+
+ if cv2.waitKey(1) & 0xFF == ord('q'):
+ break
+
+cap.release()
+cv2.destroyAllWindows()

sampleImageprocessing/Hand Detection/README.md

@@ -0,0 +1,9 @@
+# ImageProcessing
+Image Processing projects With OpenCV Python.
+
+This program identifies fingers of one hand.Just run "Finger Detect.py" and you can seea blue rectangle on the top left.
+Make that area with a light color background and bring your one hand to that area.
+
+See this video
+
+https://vimeo.com/228470426

sampleImageprocessing/Object Detect By Color/HSV Color filter.py

@@ -0,0 +1,52 @@
+import cv2
+import numpy as np
+
+def callback(x):
+ pass
+
+cap = cv2.VideoCapture(0)
+cv2.namedWindow('image')
+
+ilowH = 0
+ihighH = 179
+
+ilowS = 0
+ihighS = 255
+ilowV = 0
+ihighV = 255
+
+cv2.createTrackbar('lowH','image',ilowH,179,callback)
+cv2.createTrackbar('highH','image',ihighH,179,callback)
+cv2.createTrackbar('lowS','image',ilowS,255,callback)
+cv2.createTrackbar('highS','image',ihighS,255,callback)
+cv2.createTrackbar('lowV','image',ilowV,255,callback)
+cv2.createTrackbar('highV','image',ihighV,255,callback)
+
+
+
+while(True):
+ ret, frame = cap.read()
+ ilowH = cv2.getTrackbarPos('lowH', 'image')
+ ihighH = cv2.getTrackbarPos('highH', 'image')
+ ilowS = cv2.getTrackbarPos('lowS', 'image')
+ ihighS = cv2.getTrackbarPos('highS', 'image')
+ ilowV = cv2.getTrackbarPos('lowV', 'image')
+ ihighV = cv2.getTrackbarPos('highV', 'image')
+
+ hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
+
+ lower_hsv = np.array([ilowH, ilowS, ilowV])
+ higher_hsv = np.array([ihighH, ihighS, ihighV])
+ mask = cv2.inRange(hsv, lower_hsv, higher_hsv)
+ mask = cv2.erode(mask, None, iterations=6)
+ mask = cv2.dilate(mask, None, iterations=6)
+ frame = cv2.bitwise_and(frame, frame, mask=mask)
+
+ cv2.imshow('image', frame)
+ k = cv2.waitKey(1000) & 0xFF # large wait time to remove freezing
+ if k == 113 or k == 27:
+ break
+
+
+cv2.destroyAllWindows()
+cap.release()

sampleImageprocessing/Object Detect By Color/README.md

@@ -0,0 +1,11 @@
+# ImageProcessing
+Image Processing projects With OpenCV Python 
+
+
+Run "HSV Color filter.py" and filter the object color you want to detect.
+Then edit "object detect by color.py" and change the following lines with values HSV values
+
+ lower_hsv = np.array([lowH, lowS,lowV])
+ higher_hsv = np.array([highH, highS, highV])
+
+Save it and RUN!

sampleImageprocessing/Object Detect By Color/object detect by color.py

@@ -0,0 +1,33 @@
+import numpy as np
+import cv2
+
+cap = cv2.VideoCapture(0)
+dd=True
+while(dd):
+ ret, frame = cap.read()
+ fg=frame
+ hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
+ lower_hsv = np.array([0, 163, 182])
+ higher_hsv = np.array([110, 255, 254])
+ mask = cv2.inRange(hsv, lower_hsv, higher_hsv)
+ mask = cv2.erode(mask, None, iterations=2)
+ mask = cv2.dilate(mask, None, iterations=2)
+
+ cnts = cv2.findContours(mask.copy(), cv2.RETR_EXTERNAL,
+ cv2.CHAIN_APPROX_SIMPLE)
+ cnt = cnts[0]
+ M = cv2.moments(cnt)
+ if len(cnts)>0:
+ frame=fg
+
+ x,y,w,h = cv2.boundingRect(cnt)
+ cv2.rectangle(frame,(x,y),(x+w,y+h),(0,255,0),2)
+
+
+
+ cv2.imshow('frame',frame)
+ if cv2.waitKey(1) & 0xFF == ord('q'):
+ break
+
+cap.release()
+cv2.destroyAllWindows()

sampleImageprocessing/Controll Mouse with a moving object/HSV Color filter.py

@@ -0,0 +1,52 @@
+import cv2
+import numpy as np
+
+def callback(x):
+ pass
+
+cap = cv2.VideoCapture(0)
+cv2.namedWindow('image')
+
+ilowH = 0
+ihighH = 179
+
+ilowS = 0
+ihighS = 255
+ilowV = 0
+ihighV = 255
+
+cv2.createTrackbar('lowH','image',ilowH,179,callback)
+cv2.createTrackbar('highH','image',ihighH,179,callback)
+cv2.createTrackbar('lowS','image',ilowS,255,callback)
+cv2.createTrackbar('highS','image',ihighS,255,callback)
+cv2.createTrackbar('lowV','image',ilowV,255,callback)
+cv2.createTrackbar('highV','image',ihighV,255,callback)
+
+
+
+while(True):
+ ret, frame = cap.read()
+ ilowH = cv2.getTrackbarPos('lowH', 'image')
+ ihighH = cv2.getTrackbarPos('highH', 'image')
+ ilowS = cv2.getTrackbarPos('lowS', 'image')
+ ihighS = cv2.getTrackbarPos('highS', 'image')
+ ilowV = cv2.getTrackbarPos('lowV', 'image')
+ ihighV = cv2.getTrackbarPos('highV', 'image')
+
+ hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
+
+ lower_hsv = np.array([ilowH, ilowS, ilowV])
+ higher_hsv = np.array([ihighH, ihighS, ihighV])
+ mask = cv2.inRange(hsv, lower_hsv, higher_hsv)
+ mask = cv2.erode(mask, None, iterations=6)
+ mask = cv2.dilate(mask, None, iterations=6)
+ frame = cv2.bitwise_and(frame, frame, mask=mask)
+
+ cv2.imshow('image', frame)
+ k = cv2.waitKey(1000) & 0xFF # large wait time to remove freezing
+ if k == 113 or k == 27:
+ break
+
+
+cv2.destroyAllWindows()
+cap.release()

sampleImageprocessing/Controll Mouse with a moving object/Mouse.py

@@ -0,0 +1,47 @@
+import cv2
+import numpy as np
+
+import win32api
+global cam
+cam = cv2.VideoCapture(0)
+
+def diffImg(t0, t1, t2):
+ d1 = cv2.absdiff(t2, t1)
+ d2 = cv2.absdiff(t1, t0)
+ return cv2.bitwise_and(d1, d2)
+def main():
+ global cam
+ t_minus = cv2.cvtColor(cam.read()[1], cv2.COLOR_RGB2GRAY)
+ t = cv2.cvtColor(cam.read()[1], cv2.COLOR_RGB2GRAY)
+ t_plus = cv2.cvtColor(cam.read()[1], cv2.COLOR_RGB2GRAY)
+ while True:
+ ret, frame = cam.read()
+ hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
+ lower_hsv = np.array([0, 130, 147])
+ higher_hsv = np.array([22, 255, 215])
+ mask = cv2.inRange(hsv, lower_hsv, higher_hsv)
+ mask = cv2.erode(mask, None, iterations=5)
+ mask = cv2.dilate(mask, None, iterations=5)
+ cnts = cv2.findContours(mask.copy(), cv2.RETR_EXTERNAL,
+ cv2.CHAIN_APPROX_SIMPLE)
+ cnt=cnts[0]
+ if len(cnts)>0:
+ x,y,w,h = cv2.boundingRect(cnt)
+ xx,yy=(2*x+w)/2 , (2*y+h)/2
+ if xx>0 and xx<1366 and yy>0 and yy<768:
+ win32api.SetCursorPos((1366-(xx*3),yy*3))
+
+
+ (cnts) = cv2.findContours(mask.copy(), cv2.RETR_EXTERNAL,
+ cv2.CHAIN_APPROX_SIMPLE)
+ t_minus = t
+ t = t_plus
+ t_plus = cv2.cvtColor(cam.read()[1], cv2.COLOR_RGB2GRAY)
+ cv2.imshow("Mouse", frame)
+ key = cv2.waitKey(10)
+ if key == 27:
+ cv2.destroyWindow(winName)
+ break
+main()
+
+

sampleImageprocessing/Controll Mouse with a moving object/README.md

@@ -0,0 +1,11 @@
+# ImageProcessing
+Image Processing projects With OpenCV Python.
+
+This Program can control mouse cursor with a moving object.It detects the onject by its color.
+Use "HSV Color filter.py" to filter the object.
+Then Edit "Mouse.py" and change the following lines with values HSV values
+
+ lower_hsv = np.array([lowH, lowS,lowV])
+ higher_hsv = np.array([highH, highS, highV])
+
+Save it and RUN!

sampleImageprocessing/Hand Detection/Finger Detect.py

@@ -0,0 +1,90 @@
+import numpy as np
+import cv2
+from math import *
+def diffImg(t0, t1, t2):
+ d1 = cv2.absdiff(t2, t1)
+ d2 = cv2.absdiff(t1, t0)
+ return cv2.bitwise_and(d1, d2)
+
+cap = cv2.VideoCapture(0)
+nl,pl=[0,0,0,0,0],[0,0,0,0,0]
+jjjj=[0,0,0,0,0]
+while(1):
+ ret, frame = cap.read()
+ crop_frame = frame[0:300, 0:300]
+ gray_image = cv2.cvtColor(crop_frame, cv2.COLOR_BGR2GRAY)
+ ret, mask = cv2.threshold(gray_image, 145, 255, cv2.THRESH_BINARY)
+ mask_inv = cv2.bitwise_not(mask)
+ mask_inv = cv2.erode(mask_inv, None, iterations=1)
+ mask_inv = cv2.dilate(mask_inv, None, iterations=1)
+ drawing=mask_inv
+ ret,thresh = cv2.threshold(mask_inv,127,255,0)
+ im2,contours,hierarchy = cv2.findContours(thresh, 1, 2)
+ cv2.rectangle(frame, (0, 0), (300, 300), (255,0,0), 2)
+
+
+ if len (contours)>0:
+ max_area=100
+ ci=0	
+ for i in range(len(contours)):
+ cnt=contours[i]
+ area = cv2.contourArea(cnt)
+ if(area>max_area):
+ max_area=area
+ ci=i 
+
+ #Largest area contour 
+ cnts = contours[ci]
+ M = cv2.moments(cnts)
+ cX = int(M["m10"] / M["m00"])
+ cY = int(M["m01"] / M["m00"])
+ cv2.circle(frame,(cX,cY),10,[100,255,255],3)
+ hull = cv2.convexHull(cnts)
+ hull2 = cv2.convexHull(cnts,returnPoints = False)
+ defects = cv2.convexityDefects(cnts,hull2)
+ FarDefect = []
+
+ try:
+ ccc=0
+ for i in range(defects.shape[0]):
+ s,e,f,d = defects[i,0]
+ start = tuple(cnts[s][0])
+ end = tuple(cnts[e][0])
+ far = tuple(cnts[f][0])
+ dist = sqrt( (start[0] - end[0])**2 + (start[1] - end[1])**2 )
+
+ if 1:
+ FarDefect.append(far)
+ #print end[0]-far[0],far[1]-end[1]
+ a=sqrt((far[0]-end[0])**2+ (end[1]-far[1])**2)
+ b=sqrt((start[0]-far[0])**2+ (start[1]-far[1])**2)
+ c=sqrt((start[1]-end[1])**2+(start[0]-end[0])**2)
+ angle=(a**2+b**2-c**2)/(2*a*b)
+ angle=acos(angle)
+
+ if (angle*180)/(22/7)<90 and dist>10:
+ cv2.line(frame,(cX,cY),end,[125,255,0],1)
+ cv2.line(frame,(cX,cY),end,[125,255,0] ,1)
+ cv2.circle(frame,end,10,[100,255,255],3)
+ cv2.line(frame,(cX,cY),end,[125,255,0],1) 
+ cv2.circle(frame,end,10,[100,255,255],3)
+
+ except Exception as e:
+ pass
+
+ cv2.imshow('Dilation',drawing)
+
+ frame = cv2.resize(frame, (1366, 765), interpolation=cv2.INTER_CUBIC)
+ cv2.imshow('frame',frame)
+
+ #cv2.imshow('cropped frame',crop_frame)
+ cv2.imshow('grey cropped frame',gray_image)
+ cv2.imshow('t',mask)
+ cv2.imshow('t2',mask_inv)
+ #cv2.imshow('drawing',drawing)
+
+ if cv2.waitKey(1) & 0xFF == ord('q'):
+ break
+
+cap.release()
+cv2.destroyAllWindows()

sampleImageprocessing/Hand Detection/README.md

@@ -0,0 +1,9 @@
+# ImageProcessing
+Image Processing projects With OpenCV Python.
+
+This program identifies fingers of one hand.Just run "Finger Detect.py" and you can seea blue rectangle on the top left.
+Make that area with a light color background and bring your one hand to that area.
+
+See this video
+
+https://vimeo.com/228470426

sampleImageprocessing/Object Detect By Color/HSV Color filter.py

@@ -0,0 +1,52 @@
+import cv2
+import numpy as np
+
+def callback(x):
+ pass
+
+cap = cv2.VideoCapture(0)
+cv2.namedWindow('image')
+
+ilowH = 0
+ihighH = 179
+
+ilowS = 0
+ihighS = 255
+ilowV = 0
+ihighV = 255
+
+cv2.createTrackbar('lowH','image',ilowH,179,callback)
+cv2.createTrackbar('highH','image',ihighH,179,callback)
+cv2.createTrackbar('lowS','image',ilowS,255,callback)
+cv2.createTrackbar('highS','image',ihighS,255,callback)
+cv2.createTrackbar('lowV','image',ilowV,255,callback)
+cv2.createTrackbar('highV','image',ihighV,255,callback)
+
+
+
+while(True):
+ ret, frame = cap.read()
+ ilowH = cv2.getTrackbarPos('lowH', 'image')
+ ihighH = cv2.getTrackbarPos('highH', 'image')
+ ilowS = cv2.getTrackbarPos('lowS', 'image')
+ ihighS = cv2.getTrackbarPos('highS', 'image')
+ ilowV = cv2.getTrackbarPos('lowV', 'image')
+ ihighV = cv2.getTrackbarPos('highV', 'image')
+
+ hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
+
+ lower_hsv = np.array([ilowH, ilowS, ilowV])
+ higher_hsv = np.array([ihighH, ihighS, ihighV])
+ mask = cv2.inRange(hsv, lower_hsv, higher_hsv)
+ mask = cv2.erode(mask, None, iterations=6)
+ mask = cv2.dilate(mask, None, iterations=6)
+ frame = cv2.bitwise_and(frame, frame, mask=mask)
+
+ cv2.imshow('image', frame)
+ k = cv2.waitKey(1000) & 0xFF # large wait time to remove freezing
+ if k == 113 or k == 27:
+ break
+
+
+cv2.destroyAllWindows()
+cap.release()

sampleImageprocessing/Object Detect By Color/README.md

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+# ImageProcessing
+Image Processing projects With OpenCV Python 
+
+
+Run "HSV Color filter.py" and filter the object color you want to detect.
+Then edit "object detect by color.py" and change the following lines with values HSV values
+
+ lower_hsv = np.array([lowH, lowS,lowV])
+ higher_hsv = np.array([highH, highS, highV])
+
+Save it and RUN!

sampleImageprocessing/Object Detect By Color/object detect by color.py

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+import numpy as np
+import cv2
+
+cap = cv2.VideoCapture(0)
+dd=True
+while(dd):
+ ret, frame = cap.read()
+ fg=frame
+ hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
+ lower_hsv = np.array([0, 163, 182])
+ higher_hsv = np.array([110, 255, 254])
+ mask = cv2.inRange(hsv, lower_hsv, higher_hsv)
+ mask = cv2.erode(mask, None, iterations=2)
+ mask = cv2.dilate(mask, None, iterations=2)
+
+ cnts = cv2.findContours(mask.copy(), cv2.RETR_EXTERNAL,
+ cv2.CHAIN_APPROX_SIMPLE)
+ cnt = cnts[0]
+ M = cv2.moments(cnt)
+ if len(cnts)>0:
+ frame=fg
+
+ x,y,w,h = cv2.boundingRect(cnt)
+ cv2.rectangle(frame,(x,y),(x+w,y+h),(0,255,0),2)
+
+
+
+ cv2.imshow('frame',frame)
+ if cv2.waitKey(1) & 0xFF == ord('q'):
+ break
+
+cap.release()
+cv2.destroyAllWindows()