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YashasSamaga /
Last active November 9, 2020 13:45
import requests
import numpy as np
import matplotlib.pyplot as plt
r = requests.get('')
data = r.json()
#include <iostream>
#include <cuda_runtime.h>
#include <cublas_v2.h>
#define CHECK_CUDA(cond) check_cuda(cond, __LINE__)
YashasSamaga / main.cpp
Last active April 13, 2022 08:27
YOLOv4 OpenCV Performance Evaluation
// g++ -I/usr/local/include/opencv4/ main.cpp -lopencv_core -lopencv_imgproc -lopencv_dnn -lopencv_imgcodecs -O3 -std=c++17 -lstdc++fs
#include <iostream>
#include <queue>
#include <iterator>
#include <sstream>
#include <fstream>
#include <iomanip>
#include <chrono>
#include <cuda_runtime.h>
#include <random>
#include <iostream>
struct relu_grad
__device__ float operator()(float x) { return x > 0; }
#include <cuda_runtime.h>
#include <iostream>
#include <algorithm>
#include <random>
__global__ void relu(float* output, const float* input, unsigned int* sign32, int n)
int i = blockIdx.x * blockDim.x + threadIdx.x;
YashasSamaga /
Last active June 14, 2020 08:26
Performance comparision of different mish implementations
#include "mish.hpp"
#include <cuda_runtime.h>
#include <random>
#include <iostream>
template <class Activation>
__global__ void activate_vec1(float* __restrict__ output, const float* __restrict__ input, int n)
YashasSamaga / Makefile
Last active January 19, 2023 09:25
OpenCV DNN Benchmark Code
g++ -I/usr/local/include/opencv4/ benchmark.cpp -lopencv_core -lopencv_imgproc -lopencv_dnn -lopencv_imgcodecs -O3 -std=c++17
# License: MIT. See license file in root directory
# Copyright(c) JetsonHacks (2017-2019)
# Jetson Nano
# Download the opencv_extras repository
# If you are installing the opencv testdata, ie
YashasSamaga /
Last active January 19, 2022 16:51
[UNOFFICIAL] Summary of the CUDA backend in OpenCV DNN


This gist is unofficial. It was created for personal use but have kept it public in case it would be of use to others. This document is not updated regularly and may not reflect the current status of the CUDA backend.

YashasSamaga /
Last active February 18, 2024 04:03
YOLOv4 on OpenCV DNN
import cv2
import time
COLORS = [(0, 255, 255), (255, 255, 0), (0, 255, 0), (255, 0, 0)]
class_names = []
with open("classes.txt", "r") as f:
class_names = [cname.strip() for cname in f.readlines()]