add optical flow + fix typo

10.Invisible_Cloak/invisiblecloak.py → 10. Invisible_Cloak/invisiblecloak.py

@@ -1,80 +1,80 @@
- 
-import cv2
-import time
-import numpy as np
-
-## Preparation for writing the ouput video
-fourcc = cv2.VideoWriter_fourcc(*'XVID')
-out = cv2.VideoWriter('output.avi', fourcc, 20.0, (640, 480))
-
-##reading from the webcam
-cap = cv2.VideoCapture(0)
-
-## Allow the system to sleep for 3 seconds before the webcam starts
-time.sleep(3)
-count = 0
-background = 0
-
-## Capture the background in range of 60
-for i in range(60):
- ret, background = cap.read()
-background = np.flip(background, axis=1)
-
-## Read every frame from the webcam, until the camera is open
-while (cap.isOpened()):
- ret, img = cap.read()
- if not ret:
- break
- count += 1
- img = np.flip(img, axis=1)
-
- ## Convert the color space from BGR to HSV
- hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
-
- ## Generat masks to detect red color
- lower_red = np.array([0, 120, 50])
- upper_red = np.array([10, 255,255])
- mask1 = cv2.inRange(hsv, lower_red, upper_red)
-
- lower_red = np.array([170, 120, 70])
- upper_red = np.array([180, 255, 255])
- mask2 = cv2.inRange(hsv, lower_red, upper_red)
-
- mask1 = mask1 + mask2
-
- ## Open and Dilate the mask image
- mask1 = cv2.morphologyEx(mask1, cv2.MORPH_OPEN, np.ones((3, 3), np.uint8))
- mask1 = cv2.morphologyEx(mask1, cv2.MORPH_DILATE, np.ones((3, 3), np.uint8))
-
- ## Create an inverted mask to segment out the red color from the frame
- mask2 = cv2.bitwise_not(mask1)
-
- ## Segment the red color part out of the frame using bitwise and with the inverted mask
- res1 = cv2.bitwise_and(img, img, mask=mask2)
-
- ## Create image showing static background frame pixels only for the masked region
- res2 = cv2.bitwise_and(background, background, mask=mask1)
-
- ## Generating the final output and writing
- finalOutput = cv2.addWeighted(res1, 1, res2, 1, 0)
- out.write(finalOutput)
- cv2.imshow("magic", finalOutput)
- cv2.waitKey(1)
-
-
-cap.release()
-out.release()
-cv2.destroyAllWindows()
-
-#------------------------
-#colors code
-
-#skin color
-#lower_red = np.array([0, 0, 70])
-#upper_red = np.array([100, 255,255])
-# mask1 = cv2.inRange(hsv, lower_red, upper_red)
-
-# lower_red = np.array([170, 120, 70])
-# upper_red = np.array([180, 255, 255])
-
+
+import cv2
+import time
+import numpy as np
+
+## Preparation for writing the ouput video
+fourcc = cv2.VideoWriter_fourcc(*'XVID')
+out = cv2.VideoWriter('output.avi', fourcc, 20.0, (640, 480))
+
+##reading from the webcam
+cap = cv2.VideoCapture(0)
+
+## Allow the system to sleep for 3 seconds before the webcam starts
+time.sleep(3)
+count = 0
+background = 0
+
+## Capture the background in range of 60
+for i in range(60):
+ ret, background = cap.read()
+background = np.flip(background, axis=1)
+
+## Read every frame from the webcam, until the camera is open
+while (cap.isOpened()):
+ ret, img = cap.read()
+ if not ret:
+ break
+ count += 1
+ img = np.flip(img, axis=1)
+
+ ## Convert the color space from BGR to HSV
+ hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
+
+ ## Generat masks to detect red color
+ lower_red = np.array([0, 120, 50])
+ upper_red = np.array([10, 255,255])
+ mask1 = cv2.inRange(hsv, lower_red, upper_red)
+
+ lower_red = np.array([170, 120, 70])
+ upper_red = np.array([180, 255, 255])
+ mask2 = cv2.inRange(hsv, lower_red, upper_red)
+
+ mask1 = mask1 + mask2
+
+ ## Open and Dilate the mask image
+ mask1 = cv2.morphologyEx(mask1, cv2.MORPH_OPEN, np.ones((3, 3), np.uint8))
+ mask1 = cv2.morphologyEx(mask1, cv2.MORPH_DILATE, np.ones((3, 3), np.uint8))
+
+ ## Create an inverted mask to segment out the red color from the frame
+ mask2 = cv2.bitwise_not(mask1)
+
+ ## Segment the red color part out of the frame using bitwise and with the inverted mask
+ res1 = cv2.bitwise_and(img, img, mask=mask2)
+
+ ## Create image showing static background frame pixels only for the masked region
+ res2 = cv2.bitwise_and(background, background, mask=mask1)
+
+ ## Generating the final output and writing
+ finalOutput = cv2.addWeighted(res1, 1, res2, 1, 0)
+ out.write(finalOutput)
+ cv2.imshow("magic", finalOutput)
+ cv2.waitKey(1)
+
+
+cap.release()
+out.release()
+cv2.destroyAllWindows()
+
+#------------------------
+#colors code
+
+#skin color
+#lower_red = np.array([0, 0, 70])
+#upper_red = np.array([100, 255,255])
+# mask1 = cv2.inRange(hsv, lower_red, upper_red)
+
+# lower_red = np.array([170, 120, 70])
+# upper_red = np.array([180, 255, 255])
+
 #-----------------------

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()