Final updates

Software/dev/Calibratie_2.0.py

@@ -0,0 +1,173 @@
+from threading import *
+import time
+import random
+import queue
+
+import cv2
+import numpy as np
+import time
+import math
+import tkinter
+import tkinter.messagebox
+
+#Initiate global variables
+HSV_dick = {"H_min": 160, "H_max":180, "S_min":100, "S_max":255, "V_min":20, "V_max":255}
+
+def Calibratie_GUI(c):
+    main_window = tkinter.Tk()
+
+    frame1 = tkinter.Frame(main_window)
+    frame2 = tkinter.Frame(main_window)
+    frame3 = tkinter.Frame(main_window)
+    frame4 = tkinter.Frame(main_window)
+    frame5 = tkinter.Frame(main_window)
+    frame6 = tkinter.Frame(main_window)
+    frame7 = tkinter.Frame(main_window)
+    frame8 = tkinter.Frame(main_window)
+    frame9 = tkinter.Frame(main_window)
+
+    lbl_welkom = tkinter.Label(frame1, text="KleurenCalibratie a.d.h.v. sliders voor de HSV waarden.")
+    lbl_welkom.pack()
+
+
+    lbl_H_min = tkinter.Label(frame2, text="H min =")
+    slider_H_min = tkinter.Scale(frame2, from_="0", to="180", orient="horizontal", width="30",sliderlength="50",length="500", bd="5", command=slider_H_min_update)
+    slider_H_min.set(HSV_dick["H_min"])
+    lbl_H_min.pack(side="left")
+    slider_H_min.pack(side="left")
+
+
+    lbl_H_max = tkinter.Label(frame3, text="H max =")
+    slider_H_max = tkinter.Scale(frame3, from_="0", to="180", orient="horizontal", width="30",sliderlength="50",length="500", bd="5", command=slider_H_max_update)
+    slider_H_max.set(HSV_dick["H_max"])
+    lbl_H_max.pack(side="left")
+    slider_H_max.pack(side="left")
+
+    lbl_whitespace = tkinter.Label(frame4, text="")
+    lbl_whitespace.pack()
+
+
+    lbl_S_min = tkinter.Label(frame5, text="S min =")
+    slider_S_min = tkinter.Scale(frame5, from_="0", to="255", orient="horizontal", width="30",sliderlength="50",length="500", bd="5", command=slider_S_min_update)
+    slider_S_min.set(HSV_dick["S_min"])
+    lbl_S_min.pack(side="left")
+    slider_S_min.pack(side="left")
+
+    lbl_S_max = tkinter.Label(frame6, text="S max =")
+    slider_S_max = tkinter.Scale(frame6, from_="0", to="255", orient="horizontal", width="30",sliderlength="50",length="500", bd="5", command=slider_S_max_update)
+    slider_S_max.set(HSV_dick["S_max"])
+    lbl_S_max.pack(side="left")
+    slider_S_max.pack(side="left")
+
+    lbl_whitespace2 = tkinter.Label(frame7, text="")
+    lbl_whitespace2.pack()
+
+    lbl_V_min = tkinter.Label(frame8, text="V min =")
+    slider_V_min = tkinter.Scale(frame8, from_="0", to="255", orient="horizontal", width="30",sliderlength="50",length="500", bd="5", command=slider_V_min_update)
+    slider_V_min.set(HSV_dick["V_min"])
+    lbl_V_min.pack(side="left")
+    slider_V_min.pack(side="left")
+
+    lbl_V_max = tkinter.Label(frame9, text="V max =")
+    slider_V_max = tkinter.Scale(frame9, from_="0", to="255", orient="horizontal", width="30",sliderlength="50",length="500", bd="5", command=slider_V_max_update)
+    slider_V_max.set(HSV_dick["V_max"])
+    lbl_V_max.pack(side="left")
+    slider_V_max.pack(side="left")
+
+    frame1.pack()
+    frame2.pack()
+    frame3.pack()
+    frame4.pack()
+    frame5.pack()
+    frame6.pack()
+    frame7.pack()
+    frame8.pack()
+    frame9.pack()
+
+    tkinter.mainloop()    
+
+def slider_H_min_update(i):
+    HSV_dick["H_min"] = i
+    q.put(HSV_dick)
+    print(HSV_dick)
+def slider_H_max_update(i):
+    HSV_dick["H_max"] = i
+    q.put(HSV_dick)
+    print(HSV_dick)  
+def slider_S_min_update(i):
+    HSV_dick["S_min"] = i
+    q.put(HSV_dick)
+    print(HSV_dick)
+def slider_S_max_update(i):
+    HSV_dick["S_max"] = i
+    q.put(HSV_dick)
+    print(HSV_dick)
+def slider_V_min_update(i):
+    HSV_dick["V_min"] = i
+    q.put(HSV_dick)
+    print(HSV_dick)  
+def slider_V_max_update(i):
+    HSV_dick["V_max"] = i
+    q.put(HSV_dick)
+    print(HSV_dick)
+
+
+
+def Calibratie(c):
+
+    #Getting footage
+    webcam_video = cv2.VideoCapture('../videos/gras.avi')
+
+    while webcam_video.isOpened():
+        time.sleep(0.1)
+
+        #Specifying upper and lower ranges of color to detect in hsv format
+        lower = np.array([160, 100, 20])
+        upper = np.array([180, 255, 255]) #These ranges will detect RED
+
+        success, video = webcam_video.read() #Reading footage
+        hight, width, _ = video.shape #Get resolution
+
+        video_hsv = cv2.cvtColor(video, cv2.COLOR_BGR2HSV) #Converting BGR image to HSV format
+
+        mask_video = cv2.inRange(video_hsv, lower, upper) # Masking the image to find our color
+
+        mask_leftBand = mask_video[0:hight, int(200):int(250)] #Crop right band
+        mask_rightBand = mask_video[0:hight, int(width-250):int(width-200)] #crop left band
+
+        mask_contours_leftBand, hierarchy = cv2.findContours(mask_leftBand, cv2.RETR_TREE, cv2.CHAIN_APPROX_NONE) #Finding contours in mask image (leftband)
+        mask_contours_rightBand, hierarchy = cv2.findContours(mask_rightBand, cv2.RETR_TREE, cv2.CHAIN_APPROX_NONE) #Finding contours in mask image (rightband)
+
+        # Finding position of all contours of the bands
+        if len(mask_contours_leftBand or mask_contours_rightBand) != 0:
+            for i_lb, k_rb in zip(mask_contours_leftBand, mask_contours_rightBand):
+                if cv2.contourArea(i_lb) > 500:
+                    x1, y1, w1, h1 = cv2.boundingRect(i_lb)
+                    X_lb = int(x1+(w1/2)) #calculate center of rectangle
+                    Y_lb = int(y1+(h1/2))
+                    cv2.rectangle(video, (x1+200, y1), (x1 + w1+200, y1 + h1), (0, 0, 255), 3) #drawing rectangle
+
+                if cv2.contourArea(k_rb) > 500:
+                    x2, y2, w2, h2 = cv2.boundingRect(k_rb)
+                    X_rb = int(width-(x2+(w2/2))) #calculate center of rectangle
+                    Y_rb = int(y2+(h2/2))
+                    cv2.rectangle(video, ((width-x2-250), y2), (((width-x2-250) + w2), (y2 + h2)), (255, 0, 0), 3) #drawing rectangle (formula needed, otherwise it will add it on the left side
+
+
+
+        cv2.imshow("mask image", mask_video) # Displaying mask image
+        cv2.imshow("original", video) #Displaying webcam image
+        cv2.imshow('Video Left', mask_leftBand) #Displaying left band
+        cv2.imshow('Video Right', mask_rightBand) #Displaying right band
+
+        cv2.waitKey(1)
+
+if __name__ == '__main__':
+    q=queue.Queue()
+    t1=Thread(target=Calibratie_GUI, args=(q,))
+    t2=Thread(target=Calibratie, args=(q,))
+    t1.start()
+    t2.start()
+
+
+

Software/dev/bla.py

@@ -0,0 +1,170 @@
+from threading import *
+import time
+import random
+import queue
+
+import cv2
+import numpy as np
+import time
+import math
+import tkinter
+import tkinter.messagebox
+
+#Initiate global variables
+HSV_dick = {"H_min": 160, "H_max":180, "S_min":100, "S_max":255, "V_min":20, "V_max":255}
+
+def Calibratie_GUI(c):
+    main_window = tkinter.Tk()
+
+    frame1 = tkinter.Frame(main_window)
+    frame2 = tkinter.Frame(main_window)
+    frame3 = tkinter.Frame(main_window)
+    frame4 = tkinter.Frame(main_window)
+    frame5 = tkinter.Frame(main_window)
+    frame6 = tkinter.Frame(main_window)
+    frame7 = tkinter.Frame(main_window)
+    frame8 = tkinter.Frame(main_window)
+    frame9 = tkinter.Frame(main_window)
+
+    lbl_welkom = tkinter.Label(frame1, text="KleurenCalibratie a.d.h.v. sliders voor de HSV waarden.")
+    lbl_welkom.pack()
+
+
+    lbl_H_min = tkinter.Label(frame2, text="H min =")
+    slider_H_min = tkinter.Scale(frame2, from_="0", to="180", orient="horizontal", width="30",sliderlength="50",length="500", bd="5", command=slider_H_min_update)
+    slider_H_min.set(HSV_dick["H_min"])
+    lbl_H_min.pack(side="left")
+    slider_H_min.pack(side="left")
+
+
+    lbl_H_max = tkinter.Label(frame3, text="H max =")
+    slider_H_max = tkinter.Scale(frame3, from_="0", to="180", orient="horizontal", width="30",sliderlength="50",length="500", bd="5", command=slider_H_max_update)
+    slider_H_max.set(HSV_dick["H_max"])
+    lbl_H_max.pack(side="left")
+    slider_H_max.pack(side="left")
+
+    lbl_whitespace = tkinter.Label(frame4, text="")
+    lbl_whitespace.pack()
+
+
+    lbl_S_min = tkinter.Label(frame5, text="S min =")
+    slider_S_min = tkinter.Scale(frame5, from_="0", to="255", orient="horizontal", width="30",sliderlength="50",length="500", bd="5", command=slider_S_min_update)
+    slider_S_min.set(HSV_dick["S_min"])
+    lbl_S_min.pack(side="left")
+    slider_S_min.pack(side="left")
+
+    lbl_S_max = tkinter.Label(frame6, text="S max =")
+    slider_S_max = tkinter.Scale(frame6, from_="0", to="255", orient="horizontal", width="30",sliderlength="50",length="500", bd="5", command=slider_S_max_update)
+    slider_S_max.set(HSV_dick["S_max"])
+    lbl_S_max.pack(side="left")
+    slider_S_max.pack(side="left")
+
+    lbl_whitespace2 = tkinter.Label(frame7, text="")
+    lbl_whitespace2.pack()
+
+    lbl_V_min = tkinter.Label(frame8, text="V min =")
+    slider_V_min = tkinter.Scale(frame8, from_="0", to="255", orient="horizontal", width="30",sliderlength="50",length="500", bd="5", command=slider_V_min_update)
+    slider_V_min.set(HSV_dick["V_min"])
+    lbl_V_min.pack(side="left")
+    slider_V_min.pack(side="left")
+
+    lbl_V_max = tkinter.Label(frame9, text="V max =")
+    slider_V_max = tkinter.Scale(frame9, from_="0", to="255", orient="horizontal", width="30",sliderlength="50",length="500", bd="5", command=slider_V_max_update)
+    slider_V_max.set(HSV_dick["V_max"])
+    lbl_V_max.pack(side="left")
+    slider_V_max.pack(side="left")
+
+    frame1.pack()
+    frame2.pack()
+    frame3.pack()
+    frame4.pack()
+    frame5.pack()
+    frame6.pack()
+    frame7.pack()
+    frame8.pack()
+    frame9.pack()
+
+    tkinter.mainloop()    
+
+def slider_H_min_update(i):
+    HSV_dick["H_min"] = i
+    q.put(HSV_dick)
+    print(HSV_dick)
+def slider_H_max_update(i):
+    HSV_dick["H_max"] = i
+    q.put(HSV_dick)
+    print(HSV_dick)  
+def slider_S_min_update(i):
+    HSV_dick["S_min"] = i
+    q.put(HSV_dick)
+    print(HSV_dick)
+def slider_S_max_update(i):
+    HSV_dick["S_max"] = i
+    q.put(HSV_dick)
+    print(HSV_dick)
+def slider_V_min_update(i):
+    HSV_dick["V_min"] = i
+    q.put(HSV_dick)
+    print(HSV_dick)  
+def slider_V_max_update(i):
+    HSV_dick["V_max"] = i
+    q.put(HSV_dick)
+    print(HSV_dick)
+
+
+
+def Calibratie(c):
+
+    #Getting footage
+    webcam_video = cv2.VideoCapture('../images/cocoon.png')
+
+    while True:
+        time.sleep(0.1)
+
+        #Specifying upper and lower ranges of color to detect in hsv format
+        lower = np.array([160, 100, 20])
+        upper = np.array([180, 255, 255]) #These ranges will detect RED
+
+        success, video = webcam_video.read() #Reading footage
+        hight, width, _ = video.shape #Get resolution
+
+        video_hsv = cv2.cvtColor(video, cv2.COLOR_BGR2HSV) #Converting BGR image to HSV format
+
+        mask_video = cv2.inRange(video_hsv, lower, upper) # Masking the image to find our color
+
+        mask_leftBand = mask_video[0:hight, int(200):int(250)] #Crop right band
+        mask_rightBand = mask_video[0:hight, int(width-250):int(width-200)] #crop left band
+
+        mask_contours_leftBand, hierarchy = cv2.findContours(mask_leftBand, cv2.RETR_TREE, cv2.CHAIN_APPROX_NONE) #Finding contours in mask image (leftband)
+        mask_contours_rightBand, hierarchy = cv2.findContours(mask_rightBand, cv2.RETR_TREE, cv2.CHAIN_APPROX_NONE) #Finding contours in mask image (rightband)
+
+        # Finding position of all contours of the bands
+        if len(mask_contours_leftBand or mask_contours_rightBand) != 0:
+            for i_lb, k_rb in zip(mask_contours_leftBand, mask_contours_rightBand):
+                if cv2.contourArea(i_lb) > 500:
+                    x1, y1, w1, h1 = cv2.boundingRect(i_lb)
+                    X_lb = int(x1+(w1/2)) #calculate center of rectangle
+                    Y_lb = int(y1+(h1/2))
+                    cv2.rectangle(video, (x1+200, y1), (x1 + w1+200, y1 + h1), (0, 0, 255), 3) #drawing rectangle
+
+                if cv2.contourArea(k_rb) > 500:
+                    x2, y2, w2, h2 = cv2.boundingRect(k_rb)
+                    X_rb = int(width-(x2+(w2/2))) #calculate center of rectangle
+                    Y_rb = int(y2+(h2/2))
+                    cv2.rectangle(video, ((width-x2-250), y2), (((width-x2-250) + w2), (y2 + h2)), (255, 0, 0), 3) #drawing rectangle (formula needed, otherwise it will add it on the left side
+
+
+
+        cv2.imshow("mask image", mask_video) # Displaying mask image
+        cv2.imshow("original", video) #Displaying webcam image
+        cv2.imshow('Video Left', mask_leftBand) #Displaying left band
+        cv2.imshow('Video Right', mask_rightBand) #Displaying right band
+
+        cv2.waitKey(1)
+
+if __name__ == '__main__':
+    q=queue.Queue()
+    t1=Thread(target=Calibratie_GUI, args=(q,))
+    t2=Thread(target=Calibratie, args=(q,))
+    t1.start()
+    t2.start()