add more files of opencv tutorials

Author: manthan89-py

Readme.md

@@ -25,6 +25,9 @@
 * image_blending_using_pyramids_opencv.py
 * Find_and_draw_contours_using_opencv.py
 * basic_motion_detection_using_opencv.py
+* shape_detection_opencv.py
+* histogram_opencv.py
+* template_matching_opencv.py
 
 ## Helpful Documentations⭐:
 * OpenCV : https://docs.opencv.org/master/

histogram_opencv.py

@@ -0,0 +1,34 @@
+import cv2
+import numpy as np
+import matplotlib.pyplot as plt
+
+img = cv2.imread('test_images/lena.jpg', 0)
+# img = np.zeros((200,200) , np.uint8)
+# cv2.rectangle(img ,(0,50) , (100,100), (127) , -1)
+
+# b,g,r = cv2.split(img)
+
+# cv2.imshow('Main image' , img)
+# cv2.imshow('Blue Channel' , b)
+# cv2.imshow('Green Channel' , g)
+# cv2.imshow('Red Channel' , r)
+
+# Histogram in Matplotlib
+
+# plt.hist(img.ravel() , 256 , [0,256])
+# plt.hist(b.ravel() , 256 , [0,256])
+# plt.hist(g.ravel() , 256 , [0,256])
+# plt.hist(r.ravel() , 256 , [0,256])
+# plt.title('Histogram of Color Image(lena.jpg)')
+# plt.show()
+
+
+# Histogram in Opencv
+
+hist = cv2.calcHist([img], [0] , None , [256],[0,256])
+plt.plot(hist)
+plt.show()
+
+
+cv2.waitKey(0)
+cv2.destroyAllWindows()

output/Readme.md

@@ -11,4 +11,7 @@
 <img src="edge_detection_algorithms.png">
 
 # Canny Edge Detection
-<img src="canny_edge_detection.png">
+<img src="canny_edge_detection.png">
+
+# Approximation Of Geometircal Shapes
+<img src="approximation_of_shapes.png">

output/approximation_of_shapes.png

@@ -0,0 +1,57 @@
+import cv2
+# import matplotlib.pyplot as plt
+
+img = cv2.imread('test_images/shapes.jpg')
+
+imgGrey = cv2.cvtColor(img , cv2.COLOR_BGR2GRAY)
+
+# find threshold 
+_,thresh = cv2.threshold(imgGrey ,240 ,255 , cv2.THRESH_BINARY)
+
+# find contours
+contours, _ = cv2.findContours(thresh, cv2.RETR_TREE , cv2.CHAIN_APPROX_NONE)
+
+# 2nd Argument epsilon : approximation accuracy
+for contour in contours:
+    approx = cv2.approxPolyDP(contour, 0.01*cv2.arcLength(contour,True) , True)
+    cv2.drawContours(img,[approx] , 0 , (255,0,0) , 5)
+
+    # find coordinates
+    x = approx.ravel()[0]
+    y = approx.ravel()[1]
+
+    # shape name
+    if len(approx) == 3:
+        cv2.putText(img , 'Triangle' , (x-10,y-20) , cv2.FONT_HERSHEY_SIMPLEX , 0.5 , (255,255,255),2)
+    
+    elif len(approx) == 4:
+        x, y , w ,h = cv2.boundingRect(approx)
+        aspect_ratio = float(w)/h
+
+        if aspect_ratio >= 0.95 and aspect_ratio <= 1.05:
+            cv2.putText(img , 'Square' , (x-10,y-20) , cv2.FONT_HERSHEY_SIMPLEX , 0.5 , (0,0,0),2)
+        else:
+            cv2.putText(img , 'Rectangle' , (x-10,y-20) , cv2.FONT_HERSHEY_SIMPLEX , 0.5 , (0,0,0),2)
+
+    elif len(approx) == 5:
+        cv2.putText(img , 'Pentagon' , (x-10,y-10) , cv2.FONT_HERSHEY_SIMPLEX , 0.5 , (0,0,0),2)
+    
+    elif len(approx) == 6:
+        cv2.putText(img , 'Hexagon' , (x-10,y-20) , cv2.FONT_HERSHEY_SIMPLEX , 0.5 , (0,0,0),2) 
+    
+    elif len(approx) == 10:
+        cv2.putText(img , 'Star' , (x-10,y-20) , cv2.FONT_HERSHEY_SIMPLEX , 0.5 , (0,0,0),2)
+    
+    else:
+        cv2.putText(img , 'Circle' , (x-10,y-20) , cv2.FONT_HERSHEY_SIMPLEX , 0.5 , (0,0,0),2)
+    
+cv2.imshow('Main Image',img)
+
+cv2.waitKey(0)
+cv2.destroyAllWindows()
+
+# plt.imshow(img , 'gray')
+# plt.title('Approximation of Shapes')
+# plt.xticks([]) , plt.yticks([])
+# plt.show()
+

output/histogram_of_image.png

@@ -0,0 +1,22 @@
+import cv2
+import numpy as np
+
+img = cv2.imread('test_images/messi5.jpg')
+grey_img = cv2.cvtColor(img , cv2.COLOR_BGR2GRAY)
+
+template = cv2.imread('test_images/messi_face.jpg', 0)
+
+w, h = template.shape[::-1]
+
+res = cv2.matchTemplate(grey_img , template , cv2.TM_CCOEFF_NORMED)
+threshold = 0.95
+loc = np.where(res >= threshold)
+# print(loc)
+
+for pt in zip(*loc[::-1]):
+    cv2.rectangle(img, pt , (pt[0]+w , pt[1]+h) , (0,0,255),2)
+
+
+cv2.imshow('image' , img)
+cv2.waitKey(0)
+cv2.destroyAllWindows()