import sys, os, cv2
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.gridspec import GridSpec
from matplotlib.widgets import Slider, Button
from scipy.ndimage import label
import threading
import time

def _changeThreshold(val):
	global _percentThreshold
	global _threshold
	_percentThreshold = _slider.val
	_threshold = _percentThreshold / 100 * 255
	
def _changeMorphologyIterations1(val):
	global _morphIterations1
	_morphIterations1 = _sliderMor1.val
	
def _changeMorphologyIterations2(val):
	global _morphIterations2
	_morphIterations2 = _sliderMor2.val

def _changeImage():
	_ret, _img = _cap.read()
	_img = cv2.cvtColor(_img, cv2.COLOR_BGR2GRAY)
	_fig1ShowIt.set_array(_img)
	
	_ret, _imgBin = cv2.threshold(_img, _threshold, 255, cv2.THRESH_BINARY)
	_imgBin = cv2.erode(_imgBin, _kernel, iterations = int(_morphIterations1))
	_imgBin = cv2.dilate(_imgBin, _kernel, iterations = int(_morphIterations2))
	_labeledBin, _count = label(_imgBin)
	_fig2.set_title("Result: " + str(_count) + " coin(s)")
	
	_fig2ShowIt.set_array(_labeledBin)
	plt.draw()
	
	threading.Timer(0.1, _changeImage).start()

_cap = cv2.VideoCapture(0)
_ret, _img = _cap.read()
_img = cv2.cvtColor(_img, cv2.COLOR_BGR2GRAY)

_flag = True

_sliderInitVal = 50
_percentThreshold = _sliderInitVal
_threshold = _percentThreshold / 100 * 255
_kernel = np.ones((5, 5), np.uint8)

_slider2InitVal = 2
_morphIterations1 = _slider2InitVal

_slider3InitVal = 2
_morphIterations2 = _slider3InitVal

_fig = plt.figure("Labelling")
_gs = GridSpec(15, 2)
_fig1 = plt.subplot(_gs[0:10, 0])
_fig1.set_title("Original")
_fig1ShowIt = plt.imshow(_img, cmap = "gray")

_ret, _imgBin = cv2.threshold(_img, _threshold, 255, cv2.THRESH_BINARY)
_imgBin = cv2.erode(_imgBin, _kernel, iterations = int(_morphIterations1))
_imgBin = cv2.dilate(_imgBin, _kernel, iterations = int(_morphIterations2))
_labeledBin, _count = label(_imgBin)
_fig2 = plt.subplot(_gs[0:10, 1])
_fig2.set_title("Result: " + str(_count) + " coin(s)")
_fig2ShowIt = plt.imshow(_labeledBin, cmap = "nipy_spectral")

_sliderAx = _fig.add_axes([0.1, 0.2, 0.8, 0.05])
_slider = Slider(_sliderAx, "Threshold (%)", 0, 100, valinit = _sliderInitVal)
_sliderCid = _slider.on_changed(_changeThreshold)

_sliderAxMor1 = _fig.add_axes([0.1, 0.1, 0.35, 0.05])
_sliderMor1 = Slider(_sliderAxMor1, "Iterations 1", 0, 10, valinit = _slider2InitVal)
_sliderCidMor1 = _sliderMor1.on_changed(_changeMorphologyIterations1)

_sliderAxMor2 = _fig.add_axes([0.55, 0.1, 0.35, 0.05])
_sliderMor2 = Slider(_sliderAxMor2, "Iterations 2", 0, 10, valinit = _slider3InitVal)
_sliderCidMor2 = _sliderMor2.on_changed(_changeMorphologyIterations2)

_changeImage()

plt.show()
@@ -1,25 +1,4 @@
-import sys, os, cv2%0D%0A
 impo
@@ -24,597 +24,99 @@
 ort 
-matplotlib.pyplot as plt%0D%0Afrom matplotlib.gridspec import GridSpec%0D%0Afrom matplotlib.widgets import Slider, Button%0D%0Afrom scipy.ndimage import label%0D%0Aimport threading%0D%0Aimport time%0D%0A%0D%0Adef _changeThreshold(val):%0D%0A%09global _percentThreshold%0D%0A%09global _threshold%0D%0A%09_percentThreshold = _slider.val%0D%0A%09_threshold = _percentThreshold / 100 * 255%0D%0A%09%0D%0Adef _changeMorphologyIterations1(val):%0D%0A%09global _morphIterations1%0D%0A%09_morphIterations1 = _sliderMor1.val%0D%0A%09%0D%0Adef _changeMorphologyIterations2(val):%0D%0A%09global _morphIterations2%0D%0A%09_morphIterations2 = _sliderMor2.val%0D%0A%0D%0Adef _changeImage():%0D%0A%09_ret, _img
+cv2%0D%0A%0D%0Acap = cv2.VideoCapture(0)%0D%0A%0D%0Awhile(True):%0D%0A%09# Capture frame-by-frame%0D%0A%09ret, frame
  = 
-_
 cap.
@@ -127,575 +127,57 @@
 ()%0D%0A
-%09_img = cv2.cvtColor(_img, cv2.COLOR_BGR2GRAY)%0D%0A%09_fig1ShowIt.set_array(_img)%0D%0A%09%0D%0A%09_ret, _imgBin = cv2.threshold(_img, _threshold, 255, cv2.THRESH_BINARY)%0D%0A%09_imgBin = cv2.erode(_imgBin, _kernel, iterations = int(_morphIterations1))%0D%0A%09_imgBin = cv2.dilate(_imgBin, _kernel, iterations = int(_morphIterations2))%0D%0A%09_labeledBin, _count = label(_imgBin)%0D%0A%09_fig2.set_title(%22Result: %22 + str(_count) + %22 coin(s)%22)%0D%0A%09%0D%0A%09_fig2ShowIt.set_array(_labeledBin)%0D%0A%09plt.draw()%0D%0A%09%0D%0A%09threading.Timer(0.1, _changeImage).start()%0D%0A%0D%0A_cap = cv2.VideoCapture(0)%0D%0A_ret, _img = _cap.read()%0D%0A_img
+%0D%0A%09# Our operations on the frame come here%0D%0A%09gray
  = c
@@ -188,20 +188,21 @@
 vtColor(
-_img
+frame
 , cv2.CO
@@ -222,1510 +222,200 @@
 %0D%0A%0D%0A
-_flag = True%0D%0A%0D%0A_sliderInitVal = 50%0D%0A_percentThreshold = _sliderInitVal%0D%0A_threshold = _percentThreshold / 100 * 255%0D%0A_kernel = np.ones((5, 5), np.uint8)%0D%0A%0D%0A_slider2InitVal = 2%0D%0A_morphIterations1 = _slider2InitVal%0D%0A%0D%0A_slider3InitVal = 2%0D%0A_morphIterations2 = _slider3InitVal%0D%0A%0D%0A_fig = plt.figure(%22Labelling%22)%0D%0A_gs = GridSpec(15, 2)%0D%0A_fig1 = plt.subplot(_gs%5B0:10, 0%5D)%0D%0A_fig1.set_title(%22Original%22)%0D%0A_fig1ShowIt = plt.imshow(_img, cmap = %22gray%22)%0D%0A%0D%0A_ret, _imgBin = cv2.threshold(_img, _threshold, 255, cv2.THRESH_BINARY)%0D%0A_imgBin = cv2.erode(_imgBin, _kernel, iterations = int(_morphIterations1))%0D%0A_imgBin = cv2.dilate(_imgBin, _kernel, iterations = int(_morphIterations2))%0D%0A_labeledBin, _count = label(_imgBin)%0D%0A_fig2 = plt.subplot(_gs%5B0:10, 1%5D)%0D%0A_fig2.set_title(%22Result: %22 + str(_count) + %22 coin(s)%22)%0D%0A_fig2ShowIt = plt.imshow(_labeledBin, cmap = %22nipy_spectral%22)%0D%0A%0D%0A_sliderAx = _fig.add_axes(%5B0.1, 0.2, 0.8, 0.05%5D)%0D%0A_slider = Slider(_sliderAx, %22Threshold (%25)%22, 0, 100, valinit = _sliderInitVal)%0D%0A_sliderCid = _slider.on_changed(_changeThreshold)%0D%0A%0D%0A_sliderAxMor1 = _fig.add_axes(%5B0.1, 0.1, 0.35, 0.05%5D)%0D%0A_sliderMor1 = Slider(_sliderAxMor1, %22Iterations 1%22, 0, 10, valinit = _slider2InitVal)%0D%0A_sliderCidMor1 = _sliderMor1.on_changed(_changeMorphologyIterations1)%0D%0A%0D%0A_sliderAxMor2 = _fig.add_axes(%5B0.55, 0.1, 0.35, 0.05%5D)%0D%0A_sliderMor2 = Slider(_sliderAxMor2, %22Iterations 2%22, 0, 10, valinit = _slider3InitVal)%0D%0A_sliderCidMor2 = _sliderMor2.on_changed(_changeMorphologyIterations2)%0D%0A%0D%0A_changeImage()%0D%0A%0D%0Aplt.show()
+%09# Display the resulting frame%0D%0A%09cv2.imshow(%22frame%22, gray)%0D%0A%09if cv2.waitKey(1) & 0xFF == ord('q'):%0D%0A%09%09break%0D%0A%0D%0A# When everything done, release the capture%0D%0Acap.release()%0D%0Acv2.destroyAllWindows()%0D%0A

Update camera.py