inference on 2 webcams in parallel

[Stefano0513]

I have 2 webcams connected via USB to my PC which, taken individually, work perfectly, but when I go to "get" them with the py and openCV code I can never detect them together in parallel... here is the error: [ WARN:[email protected] ] global cap_msmf.cpp:471 anonymous-namespace'::SourceReaderCB::OnReadSample videoio(MSMF): OnReadSample() is called with error status: -1072875772 [ WARN:[email protected]] global cap_msmf.cpp:483 anonymous-namespace'::SourceReaderCB::OnReadSample videoio(MSMF): async ReadSample() call is failed with error status: -1072875772
[ WARN:[email protected]] global cap_msmf.cpp:1759 CvCapture_MSMF::grabFrame videoio(MSMF): can't grab frame. Error: -1072875772

I also leave the code below to understand what I do but it's very simple...
I really hope someone helps me because I can't understand why they do this and I can't find anything online, Thanks in advance everyone!

Py code: import cv2
import numpy as np
import threading
import os
from threading import Thread
from queue import Queue
from ultralytics import YOLO
import supervision as sv
import time
os.environ["KMP_DUPLICATE_LIB_OK"] = "TRUE"

def inference_webcam(webcam_id, model, cap):
polygon = np.array([
[50, 450], # top left
[500, 450], # top right
[500, 10], # bottom right
[50, 10] # bottom left
])

   width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))
   height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
   webcam_data = (width, height)

   zone = sv.PolygonZone(polygon=polygon, frame_resolution_wh=webcam_data)
   box_annotator = sv.BoxAnnotator(thickness=4, text_thickness=4, text_scale=2)
   zone_annotator = sv.PolygonZoneAnnotator(zone=zone, color=sv.Color.green(), thickness=6, text_thickness=6,
                                           text_scale=4)

   while True:

       ret, frame = cap.read()

       if not ret:
           break
  
       results = model(frame)
      
       for result in results:
           frame = result.orig_img

           detections = sv.Detections.from_yolov8(result)

           labels = [
               f"{tracker_id} {model.names[class_id]} {confidence:0.2f}"
               for _, confidence, class_id, tracker_id
               in detections
           ]

           frame = box_annotator.annotate(
               scene=frame,
               detections=detections,
               labels=labels
           )

           zone.trigger(detections=detections)
           zone_annotator.annotate(scene=frame)
           print("END webcam cycle "+str(webcam_id) +"\n")

           cv2.imshow(f"yolov8-{webcam_id}", frame)

       if cv2.waitKey(1) & 0xFF == 27:
           break

   cap.release()
   cv2.destroyAllWindows()

def main():
model = YOLO("yoloV8m.pt")

   webcam_id_1 = 0
   webcam_id_2 = 1

   cap2 = cv2.VideoCapture(1)# cv2.CAP_DSHOW
   cap = cv2.VideoCapture(0)# cv2.CAP_DSHOW

   thread2 = Thread(target=webcam_inference, args=(webcam_id_2, model, cap2))
   thread1 = Thread(target=webcam_inference, args=(webcam_id_1, model, cap))

   thread2.start()
   thread1.start()
  
   thread1.join()
   thread2.join()

if name == "main":
main()

[Stefano0513]

I found the solution with the help of another form, but if anyone comes by here and needs it, here's where you can read the solution: https://forum.opencv.org/t/real-time-inference-on-dual-webcams-in-parallel/14729

[SkalskiP]

Hi, @Stefano0513! 🔥 I'm sorry you needed to figure it out on your own. Too much work and not enough time. I'm happy you found the answer!