whklwhkl

import atexit
import pickle


class Cache:

    def __init__(self, path: str):
        self.path = path
        try:
            with open(path, 'rb') as file:

whklwhkl

from threading import Thread
from queue import Queue


class threading(Thread):
    '''
```Python
@threading
def foo():
    return 42

whklwhkl

'''
################################# README #######################################
This script deploys all functions within a module (i.e. src).
Note that the typing of functions is a necessity for deployment.

For instance, we have a module defined as src.
src
├── __init__.py
└── foo.py

whklwhkl

import onnx
import onnx_graphsurgeon as gs  # https://github.com/NVIDIA/TensorRT/tree/main/tools/onnx-graphsurgeon


@gs.Graph.register()
def rebuild_hard_swish(self, *nodes):
    _add, _clip, _mul, _div = nodes
    # delete div node
    _mul.outputs = _div.outputs[:]
    _div.outputs.clear()

whklwhkl

from functools import lru_cache, partial

import numpy as np


def hds_sample(d=4):
    out = [1]
    d -= 2
    for i in range(d, -1, -1):
        theta = inv_cdf(i)(np.random.rand())

whklwhkl

apt-get install docker.io
curl -s -L https://nvidia.github.io/nvidia-docker/gpgkey | apt-key add -
distribution=$(. /etc/os-release;echo $ID$VERSION_ID)
curl -s -L https://nvidia.github.io/nvidia-docker/$distribution/nvidia-docker.list | tee /etc/apt/sources.list.d/nvidia-docker.list

apt-get update
apt-get install -y nvidia-docker2

pkill -SIGHUP dockerd
apt-get install nvidia-418

whklwhkl

# This is a pytorch implementation of the [Locating Objects Without Bounding Boxes](https://arxiv.org/pdf/1806.07564.pdf)


class WeightedHausdorffDistance(torch.nn.Module):
    def __init__(self, alpha=-5):
        """note: this distance metric takes effect when the input heatmap values are within [0,1]"""
        super().__init__()
        self.soft_min_fn = lambda x:x.pow(alpha).mean(0).mean(0).pow(1/alpha)  # alpha --> -infi ==> min_func
        
    def forward(self, heat_map, points):

whklwhkl

import cv2
import numpy as np
from PIL import Image
import os.path as osp, os

## from https://github.com/nwojke/deep_sort
import tracker
import detection
import nn_metric
##