torch/lib/libgomp-d22c30c5.so.1: cannot allocate memory in static TLS block

I installed YoloV5 on my jetson nano. I wanted to execute my object detection code when this error appeared: python3.8/site-packages/torch/lib/libgomp-d22c30c5.so.1: cannot allocate memory in static TLS block.

To fix the problem I tried to put in the bashrc:

export LD_PRELOAD=/usr/lib/aarch64-linux-gnu/libgomp.so.1

It didn't work

Do you have another idea?

Here is my code:

import cv2
import numpy as np
from elements.yolo import OBJ_DETECTION

Object_classes = ['person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'traffic light',
            'fire hydrant', 'stop sign', 'parking meter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow',
            'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee',
            'skis', 'snowboard', 'sports ball', 'kite', 'baseball bat', 'baseball glove', 'skateboard', 'surfboard',
            'tennis racket', 'bottle', 'wine glass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple',
            'sandwich', 'orange', 'broccoli', 'carrot', 'hot dog', 'pizza', 'donut', 'cake', 'chair', 'couch',
            'potted plant', 'bed', 'dining table', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cell phone',
            'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddy bear',
            'hair drier', 'toothbrush' ]

Object_colors = list(np.random.rand(80,3)*255)
Object_detector = OBJ_DETECTION('weights/yolov5s.pt', Object_classes)

def gstreamer_pipeline(
    capture_width=1280,
    capture_height=720,
    display_width=1280,
    display_height=720,
    framerate=60,
    flip_method=0,
    ):
    return (
        "nvarguscamerasrc ! "
        "video/x-raw(memory:NVMM), "
        "width=(int)%d, height=(int)%d, "
        "format=(string)NV12, framerate=(fraction)%d/1 ! "
        "nvvidconv flip-method=%d ! "
        "video/x-raw, width=(int)%d, height=(int)%d, format=(string)BGRx ! "
        "videoconvert ! "
        "video/x-raw, format=(string)BGR ! appsink"
        % (
        capture_width,
        capture_height,
        framerate,
        flip_method,
        display_width,
        display_height,
      )
    )



print(gstreamer_pipeline(flip_method=0))
cap = cv2.VideoCapture(gstreamer_pipeline(flip_method=0), cv2.CAP_GSTREAMER)
if cap.isOpened():
    window_handle = cv2.namedWindow("CSI Camera", cv2.WINDOW_AUTOSIZE)

    while cv2.getWindowProperty("CSI Camera", 0) >= 0:
        ret, frame = cap.read()
        if ret:
        
            objs = Object_detector.detect(frame)

        
            for obj in objs:
           
                label = obj['label']
                score = obj['score']
                [(xmin,ymin),(xmax,ymax)] = obj['bbox']
                color = Object_colors[Object_classes.index(label)]
                frame = cv2.rectangle(frame, (xmin,ymin), (xmax,ymax), color, 2)   
                frame = cv2.putText(frame, f'{label} ({str(score)})', (xmin,ymin), cv2.FONT_HERSHEY_SIMPLEX , 0.75, color, 1, cv2.LINE_AA)

                cv2.imshow("CSI Camera", frame)
           keyCode = cv2.waitKey(30)
           if keyCode == ord('q'):
                break
cap.release()
cv2.destroyAllWindows()

else: print("Unable to open camera")

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