ivder

Train
./darknet detector train data/obj.data cfg/obj.cfg darknet53.conv.74 -map

Test
./darknet detector test data/obj.data cfg/obj.cfg backup/obj_last.weights

Test Multiple from test.txt
./darknet detector test data/obj.data cfg/obj.cfg backup/obj_6000.weights -i 0 -thresh 0.25 -dont_show -ext_output < data/obj/test.txt > detected.txt

Test C++

ivder

import cv2
import numpy as np
 
cap = cv2.VideoCapture("test.MP4")
out = cv2.VideoWriter('out.mp4', 0x7634706d, 20.0, (960,540))

if (cap.isOpened()==False):
    print("Error reading video")
 
while (cap.isOpened()):

ivder

/*
Terminal gstreamer pipeline

GoPro - UVC
gst-launch-1.0 v4l2src device="/dev/video1" ! "video/x-raw,width=1920,height=1080,format=YUY2" ! nvvidconv ! 'video/x-raw(memory:NVMM),format=NV12' ! nvvidconv ! xvimagesink

E-cons camera
gst-launch-1.0 v4l2src device="/dev/video1" ! "video/x-raw,width=1920,height=1080,format=UYVY" ! nvvidconv ! 'video/x-raw(memory:NVMM),format=NV12' ! nvoverlaysink

Jetson on board camera

ivder

#include <iostream>
#include <iomanip>
#include <string>
#include <vector>
#include <queue>
#include <fstream>
#include <thread>
#include <future>
#include <atomic>
#include <mutex>         // std::mutex, std::unique_lock

ivder

#pragma once
#include "CommonDef.h"
#include "Utils.h"
#include <string>

typedef std::pair<string, float> Prediction;

class ClassificationWithIntelContext;

class ClassificationWithIntel {

ivder

#include "ClassificationWithIntel.h"
#include "IntelClassification.h"

using namespace IntelVINOLib;

class ClassificationWithIntelContext
{
public:
	ClassificationWithIntelContext() {}
	~ClassificationWithIntelContext() {}

ivder

import sys
import os

from google.cloud import automl_v1beta1
from google.cloud.automl_v1beta1.proto import service_pb2


def get_prediction(content, project_id, model_id):
  prediction_client = automl_v1beta1.PredictionServiceClient()

ivder

import os
import pandas as pd

data_folders = next(os.walk('.'))[1]

filenames = [os.listdir(f) for f in data_folders]

files_dict = dict(zip(data_folders, filenames))
base_gcs_path = 'gs://sunlit-cove-237107-vcm/Damage/'

ivder

import cv2
import numpy as np

cap = cv2.VideoCapture('test.mp4')
#cap = cv2.VideoCapture(0) #tried using webcam and works
count = 0
while cap.isOpened():
    ret,frame = cap.read()
    cv2.imshow('window-name',frame)
   

ivder

import cv2
import numpy as np

# Input image
input = cv2.imread('0.jpg')

# Get input size
width, height, _ = input.shape
# Desired "pixelated" size
w, h = (64, 64)