View depth_from_single_img.txt
code running https://berak.pythonanywhere.com/ | |
run get_model.sh to download the pretrained 'unet.onnx' | |
wsgi.py is a webserver, receiving images of indoor scenes and sending back depth images. | |
up.html is the main webpage |
View flow.prototxt
input: "img0" | |
input: "img1" | |
input_shape { | |
dim: 1 | |
dim: 3 | |
dim: 720 | |
dim: 1280 | |
} | |
input_shape { | |
dim: 1 |
View mulim.cpp
#include <iostream> | |
#include <opencv2/opencv.hpp> | |
using namespace cv; | |
using namespace std; | |
using namespace cv; | |
using namespace std; | |
int main(int argc, char** argv) { | |
string folder = "c:/data/dnn/tcnn/"; |
View mace.cpp
// images from | |
// https://drive.google.com/drive/folders/19tcwtgXRqyRxcNcfmyqUoBPM78mvfD9n?usp=sharing | |
int main(int argc, char **argv) { | |
Ptr<MACE> mace = MACE::create(); | |
vector<string> fn; | |
glob("face",fn); | |
for (int i=0; i<fn.size(); i++) { | |
vector<Mat> train_img; |
View pyopencv_generated_funcs.h
static PyObject* pyopencv_cv_solvePnPGeneric(PyObject* , PyObject* args, PyObject* kw) | |
{ | |
using namespace cv; | |
{ | |
PyObject* pyobj_objectPoints = NULL; | |
Mat objectPoints; | |
PyObject* pyobj_imagePoints = NULL; | |
Mat imagePoints; | |
PyObject* pyobj_cameraMatrix = NULL; |
View div.cpp
Mat m1(3,3,CV_32FC3,Scalar(3,2,1)); | |
Mat m2; | |
cout << m1 << endl << m2 << endl; | |
Mat n = m1/m2; | |
cout << n << endl; | |
divide(1,m1,n); | |
cout << n << endl; | |
View ar.cpp
#include <fstream> | |
#include <iostream> | |
#include <sstream> | |
#include <opencv2/dnn.hpp> | |
#include <opencv2/imgproc.hpp> | |
#include <opencv2/highgui.hpp> | |
using namespace cv; |
View batch.py
# colab - install latest | |
# !pip install opencv-python==4.1.0.25 | |
import torch | |
import torch.nn as nn | |
import torchvision | |
import numpy as np | |
import cv2 |
View landmarks.py
# this is a travis related oddity, ignore ... | |
import sys | |
sys.path.append('/home/travis/build/berak/tt/ocv/lib/python2.7/dist-packages/') | |
import cv2, numpy as np | |
img = cv2.imread("david2.jpg",0) | |
cas = cv2.CascadeClassifier("haarcascade_frontalface_alt2.xml") | |
faces = cas.detectMultiScale(img, 1.5, 5) | |
print("faces",faces) |
View fbox.cpp
#include <opencv2/dnn.hpp> | |
#include <opencv2/opencv.hpp> | |
using namespace cv; | |
using namespace cv::dnn; | |
using namespace std; | |
int main(int argc, char **argv) | |
{ | |
String modelTxt = "c:/data/mdl/faceboxes/deploy.prototxt"; |
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