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• Google Analytics Sampling : Why It Matters and How to Avoid It

  21 octobre 2024, par Daniel Crough — Analytics Tips

  When marketing decisions rely on website analytics, accuracy matters.
  However, Google Analytics and other analytics platforms sample data to
  generate reports, which can sometimes misrepresent the true data trends.

  Read More

• FFmpeg -filter_complex_script crop & blurbox with time based values

  6 juin 2021, par user1503606

  I am trying to create a script that will move a blur boxed across a video based on x and y cords in a text script.

  


  I can easily create a blur box with the following ffmpeg command.

  


  ffmpeg -y -i pex.mp4 -filter_complex_script cropblur.txt -map "[v]" out_crop.mp4


  


  The cropblur.txt has the following.

  


  [0:v]crop=400:400:300:350,boxblur=10[fg]; [0:v][fg]overlay=300:350:enable='between(t\,0\,5)'[v]


  


  This creates this.

  


  

  


  What I want is the blur box to move across where the lady is running.

  


  

  


  She obviously runs out from where the box is positioned.

  


  I can create a script where I can track the correct x and y positions for the blox using jquery ui or something I just dont understand how to implement this in a filter_complex_script.

  


  I thought it would be a simple as just appending to the script something like this.

  


  [0:v]crop=400:400:300:350,boxblur=10[fg]; [0:v][fg]overlay=300:350:enable='between(t\,0\,2)'[v]
[0:v]crop=200:200:200:360,boxblur=10[fg]; [0:v][fg]overlay=300:350:enable='between(t\,2\,3)'[v]
[0:v]crop=200:200:200:370,boxblur=10[fg]; [0:v][fg]overlay=300:350:enable='between(t\,3\,4)'[v]
[0:v]crop=200:200:200:380,boxblur=10[fg]; [0:v][fg]overlay=300:350:enable='between(t\,4\,5)'[v]


  


  Changing the time and the x position based on the incremented time.

  


  If I run this script I get this error.

  


  No output pad can be associated to link label '0:v'


  


  Obviously I am doing something wrong but I cannot find any documentation that really helps me understand how to do this https://ffmpeg.org/ffmpeg.html the official docs dont really help.

  


  I could do it by running multiple passes like this.

  


  ffmpeg -y -i pex.mp4 -filter_complex "[0:v]crop=400:400:300:350,boxblur=10[fg]; [0:v][fg]overlay=300:350:enable='between(t\,0\,2)'[v]" -map "[v]" out_crop.mp4 && ffmpeg -y -i out_crop.mp4 -filter_complex "[0:v]crop=200:200:200:360,boxblur=10[fg]; [0:v][fg]overlay=300:350:enable='between(t\,2\,3)'[v]" -map "[v]" out_crop2.mp4


  


  I Would just really like to understand how to use the filter complex scripts in this way ?

  


  Any help would be great.

  


  Thanks

  


• DNN OpenCV Python using RSTP always crash after few minutes

  1er juillet 2022, par renaldyks

  Description :

  


  I want to create a people counter using DNN. The model I'm using is MobileNetSSD. The camera I use is IPCam from Hikvision. Python communicates with IPCam using the RSTP protocol.

  


  The program that I made is good and there are no bugs, when running the sample video the program does its job well. But when I replaced it with IPcam there was an unknown error.

  


  Error :

  


  Sometimes the error is :

  


  [h264 @ 000001949f7adfc0] error while decoding MB 13 4, bytestream -6
[h264 @ 000001949f825ac0] left block unavailable for requested intra4x4 mode -1
[h264 @ 000001949f825ac0] error while decoding MB 0 17, bytestream 762


  


  Sometimes the error does not appear and the program is killed.

  


  ---

  


  Update Error

  


  After revising the code, I caught the error. The error found is

  


  [h264 @ 0000019289b3fa80] error while decoding MB 4 5, bytestream -25


  


  Now I don't know what to do, because the error is not in Google.

  


  Source Code :

  


  Old Code

  


  This is my very earliest code before getting suggestions from the comments field.

  


  import time
import cv2
import numpy as np
import math
import threading

print("Load MobileNeteSSD model")

prototxt = "MobileNetSSD_deploy.prototxt"
model = "MobileNetSSD_deploy.caffemodel"

CLASSES = ["background", "aeroplane", "bicycle", "bird", "boat",
           "bottle", "bus", "car", "cat", "chair", "cow", "diningtable",
           "dog", "horse", "motorbike", "person", "pottedplant", "sheep",
           "sofa", "train", "tvmonitor"]

net = cv2.dnn.readNetFromCaffe(prototxt, model)

pos_line = 0
offset = 50
car = 0
detected = False
check = 0
prev_frame_time = 0


def detect():
    global check, car, detected
    check = 0
    if(detected == False):
        car += 1
        detected = True


def center_object(x, y, w, h):
    cx = x + int(w / 2)
    cy = y + int(h / 2)
    return cx, cy


def process_frame_MobileNetSSD(next_frame):
    global car, check, detected

    rgb = cv2.cvtColor(next_frame, cv2.COLOR_BGR2RGB)
    (H, W) = next_frame.shape[:2]

    blob = cv2.dnn.blobFromImage(next_frame, size=(300, 300), ddepth=cv2.CV_8U)
    net.setInput(blob, scalefactor=1.0/127.5, mean=[127.5, 127.5, 127.5])
    detections = net.forward()

    for i in np.arange(0, detections.shape[2]):
        confidence = detections[0, 0, i, 2]

        if confidence > 0.5:

            idx = int(detections[0, 0, i, 1])
            if CLASSES[idx] != "person":
                continue

            label = CLASSES[idx]

            box = detections[0, 0, i, 3:7] * np.array([W, H, W, H])
            (startX, startY, endX, endY) = box.astype("int")

            center_ob = center_object(startX, startY, endX-startX, endY-startY)
            cv2.circle(next_frame, center_ob, 4, (0, 0, 255), -1)

            if center_ob[0] < (pos_line+offset) and center_ob[0] > (pos_line-offset):
                # car+=1
                detect()

            else:
                check += 1
                if(check >= 5):
                    detected = False

            cv2.putText(next_frame, label+' '+str(round(confidence, 2)),
                        (startX, startY-10), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 0, 255), 2)
            cv2.rectangle(next_frame, (startX, startY),
                          (endX, endY), (0, 255, 0), 3)

    return next_frame


def PersonDetection_UsingMobileNetSSD():
    cap = cv2.VideoCapture()
    cap.open("rtsp://admin:Admin12345@192.168.100.20:554/Streaming/channels/2/")

    global car,pos_line,prev_frame_time

    frame_count = 0

    while True:
        try:
            time.sleep(0.1)
            new_frame_time = time.time()
            fps = int(1/(new_frame_time-prev_frame_time))
            prev_frame_time = new_frame_time

            ret, next_frame = cap.read()
            w_video = cap.get(cv2.CAP_PROP_FRAME_WIDTH)
            h_video = cap.get(cv2.CAP_PROP_FRAME_HEIGHT)
            pos_line = int(h_video/2)-50

            if ret == False: break

            frame_count += 1
            cv2.line(next_frame, (int(h_video/2), 0),
                     (int(h_video/2), int(h_video)), (255, 127, 0), 3)
            next_frame = process_frame_MobileNetSSD(next_frame)

            cv2.rectangle(next_frame, (248,22), (342,8), (0,0,0), -1)
            cv2.putText(next_frame, "Counter : "+str(car), (250, 20),
                        cv2.FONT_HERSHEY_SIMPLEX, 0.5, (255, 255, 255), 1)
            cv2.putText(next_frame, "FPS : "+str(fps), (0, int(h_video)-10),
                        cv2.FONT_HERSHEY_SIMPLEX, 0.5, (255, 255, 255), 1)
            cv2.imshow("Video Original", next_frame)
            # print(car)

        except Exception as e:
            print(str(e))

        if cv2.waitKey(1) & 0xFF == ord('q'): 
            break


    print("/MobileNetSSD Person Detector")


    cap.release()
    cv2.destroyAllWindows()

if __name__ == "__main__":
    t1 = threading.Thread(PersonDetection_UsingMobileNetSSD())
    t1.start()


  


  New Code

  


  I have revised my code and the program still stops taking frames. I just revised the PersonDetection_UsingMobileNetSSD() function. I've also removed the multithreading I was using. The code has been running for about 30 minutes but after a broken frame, the code will never re-execute the program block if ret == True.

  


  def PersonDetection_UsingMobileNetSSD():
    cap = cv2.VideoCapture()
    cap.open("rtsp://admin:Admin12345@192.168.100.20:554/Streaming/channels/2/")

    global car,pos_line,prev_frame_time

    frame_count = 0

    while True:
        try:
            if cap.isOpened():
                ret, next_frame = cap.read()
                if ret:
                    new_frame_time = time.time()
                    fps = int(1/(new_frame_time-prev_frame_time))
                    prev_frame_time = new_frame_time
                    w_video = cap.get(cv2.CAP_PROP_FRAME_WIDTH)
                    h_video = cap.get(cv2.CAP_PROP_FRAME_HEIGHT)
                    pos_line = int(h_video/2)-50

                    # next_frame = cv2.resize(next_frame,(720,480),fx=0,fy=0, interpolation = cv2.INTER_CUBIC)

                    if ret == False: break

                    frame_count += 1
                    cv2.line(next_frame, (int(h_video/2), 0),
                            (int(h_video/2), int(h_video)), (255, 127, 0), 3)
                    next_frame = process_frame_MobileNetSSD(next_frame)

                    cv2.rectangle(next_frame, (248,22), (342,8), (0,0,0), -1)
                    cv2.putText(next_frame, "Counter : "+str(car), (250, 20),
                                cv2.FONT_HERSHEY_SIMPLEX, 0.5, (255, 255, 255), 1)
                    cv2.putText(next_frame, "FPS : "+str(fps), (0, int(h_video)-10),
                                cv2.FONT_HERSHEY_SIMPLEX, 0.5, (255, 255, 255), 1)
                    cv2.imshow("Video Original", next_frame)
                    # print(car)
                else:
                    print("Crashed Frame")
            else:
                print("Cap is not open")

        except Exception as e:
            print(str(e))

        if cv2.waitKey(1) & 0xFF == ord('q'): 
            break


    print("/MobileNetSSD Person Detector")


    cap.release()
    cv2.destroyAllWindows()


  


  Requirement :

  


  Hardware : Intel i5-1035G1, RAM 8 GB, NVIDIA GeForce MX330

  


  Software : Python 3.6.2 , OpenCV 4.5.1, Numpy 1.16.0

  


  Question :

  


  

  1. What should i do for fixing this error ?

  


  2. What causes this to happen ?

  


  


  Best Regards,

  


  ---

  


  Thanks