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Hi! I have even older GPU chip than you mentioned (my GTX 970) and it works perfectly well for mw with OpenCV 4.1.1. I have compiled darknet with CUDA 10.0 and cuDNN 7.4 (for CUDA 10.0) and particulary for darknet compilation I used OpenCV 3.3 according to this link: [https://github.com/AlexeyAB/darknet].

I trained my own YOLO model based on yolov3-tiny and used it within the following Python code:

import cv2 as cv
import numpy as np
classFile = "obj.names" #my own class names
with open(classFile, 'rt') as f:
classes = f.read().rstrip('\n').split('\n')

Hi! I have even older GPU chip than you mentioned (my gpu is GTX 970) and it works perfectly well for mw with OpenCV 4.1.1. I have compiled darknet with CUDA 10.0 and cuDNN 7.4 (for CUDA 10.0) and particulary for darknet compilation compilation, I used OpenCV 3.3 according to this link: [https://github.com/AlexeyAB/darknet].

[https://github.com/AlexeyAB/darknet]. I trained my own YOLO "YOLOv3 " model based on yolov3-tiny and used it within the following Python code:

import cv2 as cv
import numpy as np
 classFile = "obj.names" #my own class names
names or just use coco.names
with open(classFile, 'rt') as f:
 classes = f.read().rstrip('\n').split('\n')
modelConf = 'yolov3-tiny_obj.cfg'   #or just use yolov3.cfg
modelWeights = 'yolov3-tiny_obj_7000.weights' #or just use yolov3.weights
net = cv.dnn.readNetFromDarknet(modelConf, modelWeights)
net.setPreferableBackend(cv.dnn.DNN_BACKEND_OPENCV)
net.setPreferableTarget(cv.dnn.DNN_TARGET_OPENCL_FP16)
winName = "YOLOv3 + OpenCV"
cv.namedWindow(winName, cv.WINDOW_NORMAL)
cv.resizeWindow(winName, 1280, 720)

cap = cv.VideoCapture(inputFile)
while(True):
      _,frame = cap.read()
     if np.shape(frame) != ():
             blob = cv.dnn.blobFromImage(frame, 1/255, (inpWidth, inpHeight), [0,0,0],1,crop=False)

             net.setInput(blob)
             outs = net.forward(getOutputsNames(net)) #reading .name file according to extracted objects
             frameExtract(frame, outs)   #standard frame extraction. I skipped to be short.
             cv.imshow(winName, frame)
             k = cv.waitKey(1) & 0xFF
     else:
             print("Reinitialize capture device ", time.ctime())
             cap = cv.VideoCapture(inputFile)
             time.sleep(1)
             k = cv.waitKey(1) & 0xFF
     if k == 27:
            cv.destroyAllWindows()
            break

Hi! I have even older GPU chip than you mentioned (my gpu is GTX 970) and it works perfectly well for mw me with OpenCV 4.1.1. I have compiled darknet with CUDA 10.0 and cuDNN 7.4 (for CUDA 10.0) and particulary for darknet compilation, I used OpenCV 3.3 according to this link: [https://github.com/AlexeyAB/darknet]. [https://github.com/AlexeyAB/darknet] recommendation. I trained my own "YOLOv3 " model based on yolov3-tiny and used it within the following Python code:code (you can just use the standard yolo models):

import cv2 as cv
import numpy as np

classFile = "obj.names" #my own class names or just use coco.names
with open(classFile, 'rt') as f:
    classes = f.read().rstrip('\n').split('\n')
modelConf = 'yolov3-tiny_obj.cfg'   #or just use yolov3.cfg
modelWeights = 'yolov3-tiny_obj_7000.weights' #or just use yolov3.weights
net = cv.dnn.readNetFromDarknet(modelConf, modelWeights)
net.setPreferableBackend(cv.dnn.DNN_BACKEND_OPENCV)
net.setPreferableTarget(cv.dnn.DNN_TARGET_OPENCL_FP16)
winName = "YOLOv3 + OpenCV"
cv.namedWindow(winName, cv.WINDOW_NORMAL)
cv.resizeWindow(winName, 1280, 720)

cap = cv.VideoCapture(inputFile)
while(True):
      _,frame = cap.read()
     if np.shape(frame) != ():
             blob = cv.dnn.blobFromImage(frame, 1/255, (inpWidth, inpHeight), [0,0,0],1,crop=False)

             net.setInput(blob)
             outs = net.forward(getOutputsNames(net)) #reading .name file according to extracted objects
             frameExtract(frame, outs)   #standard frame extraction. I skipped to be short.
             cv.imshow(winName, frame)
             k = cv.waitKey(1) & 0xFF
     else:
             print("Reinitialize capture device ", time.ctime())
             cap = cv.VideoCapture(inputFile)
             time.sleep(1)
             k = cv.waitKey(1) & 0xFF
     if k == 27:
            cv.destroyAllWindows()
            break