fixing previous code and adding more example

Author: codeperfectplus

11. Optical Flow/optical_flow.py

@@ -0,0 +1,28 @@
+import numpy as np
+import cv2
+
+cap = cv2.VideoCapture('motion.avi')
+
+ret, frame = cap.read()
+gs_im0 = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
+points_prev = cv2.goodFeaturesToTrack(gs_im0, 100, 0.03, 9.0, False)
+
+while(cap.isOpened()):
+ ret, frame = cap.read()
+ 
+ gs_im1 = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
+ # Call tracker.
+ points, st, err = cv2.calcOpticalFlowPyrLK(gs_im0, gs_im1, points_prev, None, (3,3))
+
+ for i,p in enumerate(points):
+ a,b = p.ravel()
+ frame = cv2.circle(frame,(a,b),3,(255,255,255),-1)
+
+ cv2.imshow('frame',frame)
+ points_prev = points
+ gs_im0 = gs_im1
+ if cv2.waitKey(1) & 0xFF == ord('q'):
+ break
+
+cap.release()
+cv2.destroyAllWindows()

12. Blob Detection/blobDetection.py

@@ -0,0 +1,14 @@
+# Shape Contouring 
+
+Contouring is like drawing an outline along the boundary of an object. In OpenCV this will be achieved with 2 processes: 
+**Thresholding** and **Contouring**. 
+
+* Thresholding allows us to filter the object 
+* Contouring lets us outline/mark the boundary of the object 
+
+## Result 
+**Original** ![](https://github.com/Pranjalmishra30/rep.1/blob/master/Contouring/Data/Shapes.png) **Contoured** ![](https://github.com/Pranjalmishra30/openCV-Rep/blob/master/Mini-Projects/ShapeContouring/Shape_Detected.png) 
+
+## Refrences 
+1. [Thresholding](https://opencv-python-tutroals.readthedocs.io/en/latest/py_tutorials/py_imgproc/py_thresholding/py_thresholding.html) 
+2. [Contours](https://docs.opencv.org/trunk/d4/d73/tutorial_py_contours_begin.html) 

13. contouring/README.md

@@ -0,0 +1,17 @@
+import cv2
+
+img = cv2.imread('./Media/Shapes.png')
+gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
+blur = cv2.GaussianBlur(gray,(11,11),0) #The values need to be >1 and odd
+
+# creating binary thresholding
+ret, th = cv2.threshold(blur,220,255,cv2.THRESH_BINARY_INV) # Inverse Binary thresholding technique
+
+# finding and drawing contour
+(cnts,_) = cv2.findContours(th.copy(),cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_SIMPLE)
+cv2.drawContours(img,cnts,-1,(0,0,0),2)
+
+cv2.imshow('image',img)
+cv2.imwrite("./Media/Shape_Detected.png",img) # Save the contoured image
+cv2.waitKey(0)
+cv2.destroyAllWindows()

13. contouring/Shape_detection.py

@@ -0,0 +1,21 @@
+import cv2
+import matplotlib.pyplot as plt
+
+# read the image
+image = cv2.imread('./Media/thumbs_up_down.jpg')
+# convert to RGB
+image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
+# convert to grayscale
+gray = cv2.cvtColor(image, cv2.COLOR_RGB2GRAY)
+# create a binary thresholded image
+_, binary = cv2.threshold(gray, 225, 255, cv2.THRESH_BINARY_INV)
+
+# find the contours from the thresholded image
+contours, hierarchy = cv2.findContours(binary, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
+# draw all contours
+image = cv2.drawContours(image, contours, -1, (0, 255, 0), 2)
+# show the image with the drawn contours
+plt.imshow(image)
+#plt.imsave('./Media/thumbs_up_down_countour.jpg', image)
+plt.show()
+

13. contouring/countouring.py

@@ -0,0 +1,27 @@
+import cv2
+
+cap = cv2.VideoCapture(0)
+
+while True:
+ cam, frame = cap.read()
+
+ if cam is True:
+ # convert frame into grayscale
+ gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
+
+ # create a binary threshold
+ _, binary = cv2.threshold(gray, 127, 255, cv2.THRESH_BINARY)
+
+ contours, hierarchy = cv2.findContours(binary, cv2.RETR_TREE, 
+ cv2.CHAIN_APPROX_SIMPLE)
+
+ image = cv2.drawContours(image=frame, contours= contours,
+ contourIdx=-1, color=(128, 0, 0), thickness=2)
+
+ cv2.imshow("live-contour-detector", image)
+
+ if cv2.waitKey(1) == ord('q'):
+ break
+
+cap.release()
+cv2.destroyAllWindows()