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‎03-07-2019-at-night/a.py‎

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from imutils.video import VideoStream
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import numpy as np
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import imutils
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import time
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import cv2
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cropping = False
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x_start, y_start, x_end, y_end = 0, 0, 0, 0
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# OpenCV object tracker implementations
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OPENCV_OBJECT_TRACKERS = {
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#"csrt": cv2.TrackerCSRT_create,
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"kcf": cv2.TrackerKCF_create,
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"boosting": cv2.TrackerBoosting_create,
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"mil": cv2.TrackerMIL_create,
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"tld": cv2.TrackerTLD_create,
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"medianflow": cv2.TrackerMedianFlow_create,
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#"mosse": cv2.TrackerMOSSE_create
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}
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# initialize OpenCV's special multi-object tracker
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trackers = cv2.MultiTracker_create()
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video = 'C:\\Users\\enesa\\Desktop\\openCV\\Object Tracking\\videos\\traffic.mp4'
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cap = cv2.VideoCapture(video)
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tracker_type = "kcf"
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if cap.isOpened():
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ret, frame = cap.read()
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frame = imutils.resize(frame, width=800)
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oriFrame = np.copy(frame)
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else:
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ret = False
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def mouse_crop(event, x, y, flags, param):
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global x_start, y_start, x_end, y_end, cropping
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# if the left click of mouse was DOWN, start RECORDING
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# (x, y) coordinates and indicate that cropping is being
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if event == cv2.EVENT_LBUTTONDOWN:
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x_start, y_start, x_end, y_end = x, y, x, y
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cropping = True
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# Mouse is Moving
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elif event == cv2.EVENT_MOUSEMOVE:
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if cropping == True:
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x_end, y_end = x, y
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# if the left click of mouse button was released
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elif event == cv2.EVENT_LBUTTONUP:
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# record the ending (x, y) coordinates
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x_end, y_end = x, y
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cropping = False # cropping is finished
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#refPoint = [(x_start, y_start), (x_end, y_end)]
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#if len(refPoint) == 2: #when two points were found
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#roi = oriFrame[refPoint[0][1]:refPoint[1][1], refPoint[0][0]:refPoint[1][0]]
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#cv2.imshow("Cropped", roi)
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cv2.namedWindow("Object Tracking")
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cv2.setMouseCallback("Object Tracking", mouse_crop)
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while True:
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frame = cap.read()
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frame = frame[1]
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# check to see if we have reached the end of the stream
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if frame is None:
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break
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# resize the frame (so we can process it faster)
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frame = imutils.resize(frame, width=800)
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i = np.copy(frame)
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# Start timer
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timer = cv2.getTickCount()
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# grab the updated bounding box coordinates (if any) for each object that is being tracked
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#(success, boxes) = trackers.update(frame)
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# Calculate Frames per second (FPS)
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fps = cv2.getTickFrequency() / (cv2.getTickCount() - timer);
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# loop over the bounding boxes and draw then on the frame
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# for box in boxes:
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# (x, y, w, h) = [int(v) for v in box]
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# cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 2)
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if not cropping:
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cv2.imshow("Object Tracking", frame)
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elif cropping:
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cv2.rectangle(i, (x_start, y_start), (x_end, y_end), (255, 0, 0), 2)
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cv2.imshow("Object Tracking", i)
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roi = i[y_start:y_end, x_start:x_end]
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cv2.imshow("Cropped", roi)
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# Display tracker type on frame
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#cv2.putText(frame, tracker_type + " Tracker", (10,20), cv2.FONT_HERSHEY_SIMPLEX, 0.75, (50,170,50),2);
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# Display FPS on frame
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#cv2.putText(frame, "FPS : " + str(int(fps)), (10,50), cv2.FONT_HERSHEY_SIMPLEX, 0.75, (50,170,50), 2);
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# show the output frame
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#cv2.imshow("Frame", frame)
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key = cv2.waitKey(10) & 0xFF
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# if the 's' key is selected, we are going to "select" a bounding
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# box to track
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# if key == ord("s"):
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# # select the bounding box of the object we want to track (make
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# # sure you press ENTER or SPACE after selecting the ROI)
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# box = cv2.selectROI("Frame", frame, fromCenter=False, showCrosshair=True)
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# # create a new object tracker for the bounding box and add it to our multi-object tracker
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# tracker = OPENCV_OBJECT_TRACKERS["kcf"]()
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# trackers.add(tracker, frame, box)
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# if the `q` key was pressed, break from the loop
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if key == ord("q"):
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break
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cap.release()
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cv2.destroyAllWindows()

‎03-07-2019-at-night/b.py‎

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from imutils.video import VideoStream
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import numpy as np
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import imutils
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import time
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import cv2
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# OpenCV object tracker implementations
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OPENCV_OBJECT_TRACKERS = {
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#"csrt": cv2.TrackerCSRT_create,
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"kcf": cv2.TrackerKCF_create,
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"boosting": cv2.TrackerBoosting_create,
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"mil": cv2.TrackerMIL_create,
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"tld": cv2.TrackerTLD_create,
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"medianflow": cv2.TrackerMedianFlow_create,
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#"mosse": cv2.TrackerMOSSE_create
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}
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# initialize OpenCV's special multi-object tracker
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trackers = cv2.MultiTracker_create()
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video = 'videos/soccer_02.mp4'
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cap = cv2.VideoCapture(video)
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tracker_type = "kcf"
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tracker = OPENCV_OBJECT_TRACKERS["kcf"]()
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while True:
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frame = cap.read()
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frame = frame[1]
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# check to see if we have reached the end of the stream
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if frame is None:
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break
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# resize the frame (so we can process it faster)
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frame = imutils.resize(frame, width=800)
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# Start timer
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timer = cv2.getTickCount()
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# grab the updated bounding box coordinates (if any) for each object that is being tracked
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(success, boxes) = trackers.update(frame)
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# Calculate Frames per second (FPS)
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fps = cv2.getTickFrequency() / (cv2.getTickCount() - timer)
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box = cv2.selectROI("Frame", np.copy(frame), fromCenter=False, showCrosshair=True)
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if box:
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# create a new object tracker for the bounding box and add it to our multi-object tracker
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trackers.add(tracker, np.copy(frame), box)
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# loop over the bounding boxes and draw then on the frame
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for box in boxes:
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(x, y, w, h) = [int(v) for v in box]
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cv2.rectangle(np.copy(frame), (x, y), (x + w, y + h), (0, 255, 0), 2)
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# Display tracker type on frame
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cv2.putText(frame, tracker_type + " Tracker", (100,20), cv2.FONT_HERSHEY_SIMPLEX, 0.75, (50,170,50),2);
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# Display FPS on frame
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cv2.putText(frame, "FPS : " + str(int(fps)), (100,50), cv2.FONT_HERSHEY_SIMPLEX, 0.75, (50,170,50), 2);
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# show the output frame
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cv2.imshow("Frame", frame)
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key = cv2.waitKey(1) & 0xFF
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# if the `q` key was pressed, break from the loop
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if key == ord("q"):
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break
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cap.release()
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cv2.destroyAllWindows()

‎03-07-2019-at-night/select_Roi01.py‎

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import cv2
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import numpy as np
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cropping = False
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x_start, y_start, x_end, y_end = 0, 0, 0, 0
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image = cv2.imread('videos/baykar_makina_logo.jpg')
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oriImage = image.copy()
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def mouse_crop(event, x, y, flags, param):
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global x_start, y_start, x_end, y_end, cropping
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# if the left click of mouse was DOWN, start RECORDING
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# (x, y) coordinates and indicate that cropping is being
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if event == cv2.EVENT_LBUTTONDOWN:
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x_start, y_start, x_end, y_end = x, y, x, y
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cropping = True
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# Mouse is Moving
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elif event == cv2.EVENT_MOUSEMOVE:
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if cropping == True:
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x_end, y_end = x, y
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# if the left click of mouse button was released
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elif event == cv2.EVENT_LBUTTONUP:
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# record the ending (x, y) coordinates
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x_end, y_end = x, y
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cropping = False # cropping is finished
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refPoint = [(x_start, y_start), (x_end, y_end)]
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if len(refPoint) == 2: #when two points were found
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roi = oriImage[refPoint[0][1]:refPoint[1][1], refPoint[0][0]:refPoint[1][0]]
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cv2.imshow("Cropped", roi)
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cv2.namedWindow("image")
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cv2.setMouseCallback("image", mouse_crop)
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while True:
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i = image.copy()
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if not cropping:
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cv2.imshow("image", image)
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elif cropping:
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cv2.rectangle(i, (x_start, y_start), (x_end, y_end), (255, 0, 0), 2)
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#i[y_start:y_end, x_start:x_end]
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cv2.imshow("image", i)
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key = cv2.waitKey(1) & 0xFF
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if key == ord("q"):
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break
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# close all open windows
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cv2.destroyAllWindows()

‎03-07-2019-at-night/select_Roi02.py‎

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import cv2
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import numpy as np
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if __name__ == '__main__' :
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# Read image
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im = cv2.imread("videos/baykar_makina_logo.jpg")
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# Select ROI
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rects = []
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r = cv2.selectROI("Frame", im, rects, fromCenter=False, showCrosshair=False)
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# Crop image
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imCrop = im[int(r[1]):int(r[1]+r[3]), int(r[0]):int(r[0]+r[2])]
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# Display cropped image
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cv2.imshow("Image", imCrop)
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cv2.waitKey(0)

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