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others/event_utils/visualize_flow.py 0 → 100644
View file @ a75d2bda
import argparse
import os
import pandas as pd
import glob
import numpy as np
import cv2 as cv
from lib.data_formats.read_events import read_memmap_events, read_h5_events_dict
if __name__ == "__main__":
"""
Quick demo
"""
parser = argparse.ArgumentParser()
parser.add_argument("path", help="events path")
parser.add_argument("flow_path", help="flow path")
parser.add_argument("--output_path", type=str, default="/tmp/visualization", help="Where to save image outputs")
parser.add_argument('--plot_method', default='between_frames', type=str,
help='which method should be used to visualize',
choices=['between_frames', 'k_events', 't_seconds'])
parser.add_argument('--w_width', type=float, default=0.01,
help='new plot is formed every t seconds (required if voxel_method is t_seconds)')
parser.add_argument('--sw_width', type=float,
help='sliding_window size in seconds (required if voxel_method is t_seconds)')
parser.add_argument("--num_bins", type=int, default=6, help="How many bins voxels should have.")
parser.add_argument('--show_plot', action='store_true', help='If true, will also display the plot in an interactive window.\
Useful for selecting the desired orientation.')
parser.add_argument("--num_show", type=int, default=-1, help="How many events to show per plot. If -1, show all events.")
parser.add_argument("--event_size", type=float, default=2, help="Marker size of the plotted events")
parser.add_argument("--ts_scale", type=int, default=10000, help="Scales the time axis. Only applicable for mayavi rendering.")
parser.add_argument("--elev", type=float, default=0, help="Elevation of plot")
parser.add_argument("--azim", type=float, default=45, help="Azimuth of plot")
parser.add_argument("--stride", type=int, default=1, help="Downsample stride for plotted images.")
parser.add_argument("--skip_frames", type=int, default=1, help="Amount of frames to place per plot.")
parser.add_argument("--start_frame", type=int, default=0, help="On which frame to start.")
parser.add_argument('--hide_skipped', action='store_true', help='Do not draw skipped frames into plot.')
parser.add_argument('--hide_events', action='store_true', help='Do not draw events')
parser.add_argument('--hide_frames', action='store_true', help='Do not draw frames')
parser.add_argument('--show_axes', action='store_true', help='Draw axes')
parser.add_argument("--num_compress", type=int, default=0, help="How many events to draw compressed. If 'auto'\
will automatically determine.", choices=['value', 'auto'])
parser.add_argument('--compress_front', action='store_true', help='If set, will put the compressed events at the _start_\
of the event volume, rather than the back.')
parser.add_argument('--invert', action='store_true', help='If the figure is for a black background, you can invert the \
colors for better visibility.')
parser.add_argument("--crop", type=str, default=None, help="Set a crop of both images and events. Uses 'imagemagick' \
syntax, eg for a crop of 10x20 starting from point 30,40 use: 10x20+30+40.")
parser.add_argument("--renderer", type=str, default="matplotlib", help="Which renderer to use (mayavi is faster)", choices=["matplotlib", "mayavi"])
args = parser.parse_args()
events = read_h5_events_dict(args.path)
xs = events['xs']
ys = events['ys']
ts = events['ts']
ps = events['ps']
t0 = ts[0]
ts = ts-t0
frames = [np.flip(np.flip(x/255., axis=0), axis=1) for x in events['frames']]
frame_ts = events['frame_timestamps'][1:]-t0
frame_end = events['frame_event_indices'][1:]
frame_start = np.concatenate((np.array([0]), frame_end))
frame_idx = np.stack((frame_end, frame_start[0:-1]), axis=1)
ys = frames[0].shape[0]-ys
xs = frames[0].shape[1]-xs
flow_paths = sorted(glob.glob(os.path.join(args.flow_path, "*.npy")))
flow_img_paths = sorted(glob.glob(os.path.join(args.flow_path, "*.png")))
flow_ts = pd.read_csv(os.path.join(args.flow_path, "timestamps.txt"), delimiter=" ", names=["fname", "timestamp"])
flow_ts = np.array(flow_ts["timestamp"])
#flows = [-np.flip(np.flip(np.load(fp), axis=1), axis=2) for fp in flow_paths]
flows = [-np.load(fp) for fp in flow_paths]
flow_imgs = [cv.imread(fi) for fi in flow_img_paths]
print("Loaded {} flow, {} img, {} ts".format(len(flows), len(flow_imgs), len(flow_ts)))
if args.plot_method == 'between_frames':
if args.renderer == "mayavi":
print(args.renderer)
pass
elif args.renderer == "matplotlib":
from lib.visualization.draw_flow import plot_between_frames
plot_between_frames(xs, ys, ts, ps, flows, flow_imgs, flow_ts, args)
print(args.renderer)
pass
elif args.plot_method == 'k_events':
print(args.renderer)
pass
elif args.plot_method == 't_seconds':
if args.renderer == "mayavi":
print(args.renderer)
pass
elif args.renderer == "matplotlib":
print(args.renderer)
pass
others/event_utils/visualize_voxel.py 0 → 100644
View file @ a75d2bda
import argparse
import os
import numpy as np
from lib.visualization.draw_event_stream import plot_between_frames
from lib.data_formats.read_events import read_memmap_events, read_h5_events_dict
def plot_events_sliding(xs, ys, ts, ps, args, frames=None, frame_ts=None):
if dt is None:
dt = (ts[-1]-ts[0])/10
sdt = dt/10
print("Using dt={}, sdt={}".format(dt, sdt))
if frames is not None:
sensor_size = frames[0].shape
else:
sensor_size = [max(ys), max(xs)]
if len(frame_ts.shape) == 2:
frame_ts = frame_ts[:,1]
for i, t0 in enumerate(tqdm(np.arange(ts[0], ts[-1]-dt, sdt))):
te = t0+dt
eidx0 = np.searchsorted(ts, t0)
eidx1 = np.searchsorted(ts, te)
fidx0 = np.searchsorted(frame_ts, t0)
fidx1 = np.searchsorted(frame_ts, te)
#print("{}:{} = {}".format(frame_ts[fidx0], ts[eidx0], fidx0))
wxs, wys, wts, wps = xs[eidx0:eidx1], ys[eidx0:eidx1], ts[eidx0:eidx1], ps[eidx0:eidx1],
if fidx0 == fidx1:
wframes=[]
wframe_ts=[]
else:
wframes = frames[fidx0:fidx1]
wframe_ts = frame_ts[fidx0:fidx1]
save_path = os.path.join(args.output_path, "frame_{:010d}.png".format(i))
plot_events(wxs, wys, wts, wps, save_path=save_path, num_show=args.num_show, event_size=args.event_size,
imgs=args.wframes, img_ts=args.wframe_ts, show_events=args.show_events, azim=args.azim,
elev=args.elev, show_frames=args.show_frames, crop=args.crop, compress_front=args.compress_front,
invert=args.invert, num_compress=args.num_compress, show_plot=args.show_plot, img_size=args.sensor_size,
show_axes=args.show_axes)
if __name__ == "__main__":
"""
Quick demo
"""
parser = argparse.ArgumentParser()
parser.add_argument("path", help="memmap events path")
parser.add_argument("--output_path", type=str, default="/tmp/visualization", help="Where to save image outputs")
parser.add_argument('--plot_method', default='between_frames', type=str,
help='which method should be used to visualize',
choices=['between_frames', 'k_events', 't_seconds'])
parser.add_argument('--k', type=int,
help='new plot is formed every k events (required if voxel_method is k_events)')
parser.add_argument('--sliding_window_w', type=int,
help='sliding_window size (required if voxel_method is k_events)')
parser.add_argument('--t', type=float,
help='new plot is formed every t seconds (required if voxel_method is t_seconds)')
parser.add_argument('--sliding_window_t', type=float,
help='sliding_window size in seconds (required if voxel_method is t_seconds)')
parser.add_argument("--num_bins", type=int, default=6, help="How many bins voxels should have.")
parser.add_argument('--show_plot', action='store_true', help='If true, will also display the plot in an interactive window.\
Useful for selecting the desired orientation.')
parser.add_argument("--num_show", type=int, default=-1, help="How many events to show per plot. If -1, show all events.")
parser.add_argument("--event_size", type=float, default=2, help="Marker size of the plotted events")
parser.add_argument("--elev", type=float, default=20, help="Elevation of plot")
parser.add_argument("--azim", type=float, default=-25, help="Azimuth of plot")
parser.add_argument("--stride", type=int, default=1, help="Downsample stride for plotted images.")
parser.add_argument("--skip_frames", type=int, default=1, help="Amount of frames to place per plot.")
parser.add_argument("--start_frame", type=int, default=0, help="On which frame to start.")
parser.add_argument('--hide_skipped', action='store_true', help='Do not draw skipped frames into plot.')
parser.add_argument('--hide_events', action='store_true', help='Do not draw events')
parser.add_argument('--hide_frames', action='store_true', help='Do not draw frames')
parser.add_argument('--show_axes', action='store_true', help='Draw axes')
parser.add_argument("--num_compress", type=int, default=0, help="How many events to draw compressed. If 'auto'\
will automatically determine.", choices=['value', 'auto'])
parser.add_argument('--compress_front', action='store_true', help='If set, will put the compressed events at the _start_\
of the event volume, rather than the back.')
parser.add_argument('--invert', action='store_true', help='If the figure is for a black background, you can invert the \
colors for better visibility.')
parser.add_argument("--crop", type=str, default=None, help="Set a crop of both images and events. Uses 'imagemagick' \
syntax, eg for a crop of 10x20 starting from point 30,40 use: 10x20+30+40.")
args = parser.parse_args()
if os.path.isdir(args.path):
events = read_memmap_events(args.path)
ts = events['t'][:].squeeze()
t0 = ts[0]
ts = ts-t0
frames = (events['images'][args.start_frame+1::])/255
frame_idx = events['index'][args.start_frame::]
frame_ts = events['frame_stamps'][args.start_frame+1::]-t0
start_idx = np.searchsorted(ts, frame_ts[0])
print("Starting from frame {}, event {}".format(args.start_frame, start_idx))
xs = events['xy'][:,0]
ys = events['xy'][:,1]
ts = ts[:]
ps = events['p'][:]
print("Have {} frames".format(frames.shape))
else:
events = read_h5_events_dict(args.path)
xs = events['xs']
ys = events['ys']
ts = events['ts']
ps = events['ps']
t0 = ts[0]
ts = ts-t0
frames = [np.flip(x/255., axis=0) for x in events['frames']]
frame_ts = events['frame_timestamps'][1:]-t0
frame_end = events['frame_event_indices'][1:]
frame_start = np.concatenate((np.array([0]), frame_end))
frame_idx = np.stack((frame_end, frame_start[0:-1]), axis=1)
ys = frames[0].shape[0]-ys
plot_between_frames(xs, ys, ts, ps, frames, frame_idx, args, plttype='voxel')
others/rpg_vid2e/.gitignore 0 → 100644
View file @ a75d2bda
example/
pretrained_models/
esim_py/build/
esim_py/*.egg*
esim_torch/build/
esim_torch/src/*.egg*
.vscode/
*.swp
*.pyc
log/*
split*
__pycache__
dataset/
rosbag_dataset/
*.ckpt
.idea/
others/rpg_vid2e/.gitmodules 0 → 100644
View file @ a75d2bda
[submodule "esim_py/pybind11"]
path = esim_py/pybind11
url = https://github.com/pybind/pybind11.git
others/rpg_vid2e/LICENSE 0 → 100644
View file @ a75d2bda
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others/rpg_vid2e/README.md 0 → 100644
View file @ a75d2bda
# Video to Events: Recycling Video Datasets for Event Cameras
<p align="center">
<a href="https://youtu.be/uX6XknBGg0w">
<img src="http://rpg.ifi.uzh.ch/data/VID2E/thumb.png" alt="Video to Events" width="600"/>
</a>
</p>
This repository contains code that implements
video to events conversion as described in Gehrig et al. CVPR'20 and the used dataset. The paper can be found [here](http://rpg.ifi.uzh.ch/docs/CVPR20_Gehrig.pdf)
If you use this code in an academic context, please cite the following work:
[Daniel Gehrig](https://danielgehrig18.github.io/), [Mathias Gehrig](https://magehrig.github.io/), [Javier Hidalgo-Carrió](https://jhidalgocarrio.github.io/), [Davide Scaramuzza](http://rpg.ifi.uzh.ch/people_scaramuzza.html), "Video to Events: Recycling Video Datasets for Event Cameras", The Conference on Computer Vision and Pattern Recognition (CVPR), 2020
```bibtex
@InProceedings{Gehrig_2020_CVPR,
author = {Daniel Gehrig and Mathias Gehrig and Javier Hidalgo-Carri\'o and Davide Scaramuzza},
title = {Video to Events: Recycling Video Datasets for Event Cameras},
booktitle = {{IEEE} Conf. Comput. Vis. Pattern Recog. (CVPR)},
month = {June},
year = {2020}
}
```
## News
* We now support frame interpolation done by [FILM](https://github.com/google-research/frame-interpolation).
* We release a web app and interactive demo which generates events and converts your webcam to events. Try it out [here](web_app/README.md).
* We now also release new python bindings for esim with GPU support.
Details are [here](esim_torch/README.md)
## Web App and Interactive Demo
Try out our the interactive demo and webcam support [here](web_app/README.md).
## Dataset
The synthetic N-Caltech101 dataset, as well as video sequences used for event conversion can be found [here](http://rpg.ifi.uzh.ch/data/VID2E/ncaltech_syn_images.zip). For each sample of each class it contains events in the form `class/image_%04d.npz` and images in the form `class/image_%05d/images/image_%05d.png`, as well as the corresponding timestamps of the images in `class/image_%04d/timestamps.txt`.
## Installation
Clone the repo *recursively with submodules*
```bash
git clone git@github.com:uzh-rpg/rpg_vid2e.git --recursive
```
## Installation
First download the [FILM](https://github.com/google-research/frame-interpolation) checkpoint, and move it to the current root
```bash
wget https://rpg.ifi.uzh.ch/data/VID2E/pretrained_models.zip -O /tmp/temp.zip
unzip /tmp/temp.zip -d rpg_vid2e/
rm -rf /tmp/temp.zip
```
make sure to install the following
* [Anaconda Python 3.9](https://www.anaconda.com/products/individual)
* [CUDA Toolkit 11.2.1](https://developer.nvidia.com/cuda-11.2.1-download-archive)
* [cuDNN 8.1.0](https://developer.nvidia.com/rdp/cudnn-download)
```bash
conda create --name vid2e python=3.9
conda activate vid2e
pip install -r rpg_vid2e/requirements.txt
conda install -y -c conda-forge pybind11 matplotlib
conda install -y pytorch torchvision torchaudio cudatoolkit=11.3 -c pytorch
```
Build the python bindings for ESIM
```bash
pip install rpg_vid2e/esim_py/
```
Build the python bindings with GPU support with
```bash
pip install rpg_vid2e/esim_torch/
```
## Adaptive Upsampling
*This package provides code for adaptive upsampling with frame interpolation based on [Super-SloMo](https://people.cs.umass.edu/~hzjiang/projects/superslomo/)*
Consult the [README](upsampling/README.md) for detailed instructions and examples.
## esim\_py
*This package exposes python bindings for [ESIM](http://rpg.ifi.uzh.ch/docs/CORL18_Rebecq.pdf) which can be used within a training loop.*
For detailed instructions and example consult the [README](esim_py/README.md)
## esim\_torch
*This package exposes python bindings for [ESIM](http://rpg.ifi.uzh.ch/docs/CORL18_Rebecq.pdf) with GPU support.*
For detailed instructions and example consult the [README](esim_torch/README.md)
## Example
To run an example, first upsample the example videos
```bash
device=cpu
# device=cuda:0
python upsampling/upsample.py --input_dir=example/original --output_dir=example/upsampled --device=$device
```
This will generate upsampling/upsampled with in the `example/upsampled` folder. To generate events, use
```bash
python esim_torch/generate_events.py --input_dir=example/upsampled \
--output_dir=example/events \
--contrast_threshold_neg=0.2 \
--contrast_threshold_pos=0.2 \
--refractory_period_ns=0
```
others/rpg_vid2e/esim_py/CMakeLists.txt 0 → 100644
View file @ a75d2bda
cmake_minimum_required(VERSION 3.3)
project(esim_py)
find_package(pybind11 REQUIRED)
find_package(OpenCV REQUIRED)
find_package(Eigen3 REQUIRED NO_MODULE)
find_package(Boost COMPONENTS system filesystem REQUIRED)
set(CMAKE_POSITION_INDEPENDENT_CODE ON)
set(CMAKE_CXX_STANDARD 11)
include_directories(include ${EIGEN3_INCLUDE_DIR} ${OpenCV_INCLUDE_DIRS} ${Boost_INCLUDE_DIRS})
add_library(libesim STATIC src/esim.cpp)
pybind11_add_module(esim_py src/bindings.cpp)
target_link_libraries(esim_py PRIVATE libesim ${OpenCV_LIBS} ${Boost_FILESYSTEM_LIBRARY} ${BOOST_SYSTEM_LIBRARY} Boost::filesystem Boost::system Eigen3::Eigen pybind11::embed)
others/rpg_vid2e/esim_py/README.md 0 → 100644
View file @ a75d2bda
# esym\_py
This package exposes python bindings for ESIM which can be used within a training loop.
To test out if the installation was successful you can run
```bash
python tests/test.py
```
which should print a message if completed sucessfully.
The currently supported functions are listed in the example below:
```python
import esim_py
# constructor
esim = esim_py.EventSimulator(
contrast_threshold_pos, # contrast thesholds for positive
contrast_threshold_neg, # and negative events
refractory_period, # minimum waiting period (in sec) before a pixel can trigger a new event
log_eps, # epsilon that is used to numerical stability within the logarithm
use_log, # wether or not to use log intensity
)
# setter, useful within a training loop
esim.setParameters(contrast_threshold_pos, contrast_threshold_neg, refractory_period, log_eps, use_log)
# generate events from a sequence of images
events_from_images = esim.generateFromFolder(
path_to_image_folder, # absolute path to folder that stores images in numbered order
path_to_timestamps # absolute path to timestamps file containing one timestamp (in secs) for each
)
# generate events from a video
events_from_video = esim.generateFromVideo(
path_to_video_file, # absolute path to video storing images
path_to_timestamps # absolute path to timestamps file
)
# generate events from list of images and timestamps
events_list_of_images = esim.generateFromStampedImageSequence(
list_of_image_files, # list of absolute paths to images
list_of_timestamps # list of timestamps in ascending order
)
```
The example script `tests/plot_virtual_events.py` plots virtual events that are generated from images in `tests/data/images` with varying positive and negative contrast thresholds. To call it you need some additional pip packages:
```bash
pip install numpy matplotlib
python tests/plot_virtual_events.py
```
others/rpg_vid2e/esim_py/include/esim.h 0 → 100644
View file @ a75d2bda
#pragma once
#include <vector>
#include <boost/filesystem.hpp>
#include <Eigen/Core>
#include <opencv2/core/core.hpp>
struct Event
{
Event(int x, int y, double t, int polarity)
: x_(x), y_(y), t_(t), polarity_(polarity)
{}
bool operator<(Event& other)
{
return t_ < other.t_;
}
int x_, y_;
double t_;
int polarity_;
};
/*
* The EventSimulator takes as input a sequence of stamped images,
* assumed to be sampled at a "sufficiently high" framerate,
* and simulates the principle of operation of an idea event camera
* with a constant contrast threshold C.
* Pixel-wise intensity values are linearly interpolated in time.
*
* The pixel-wise voltages are reset with the values from the first image
* which is passed to the simulator.
*/
class EventSimulator
{
public:
EventSimulator(float contrast_threshold_pos,
float contrast_threshold_neg,
float refractory_period,
float log_eps,
bool use_log_img);
Eigen::MatrixXd generateFromFolder(std::string image_folder, std::string timestamps_file_path);
Eigen::MatrixXd generateFromVideo(std::string video_path, std::string timestamps_file_path);
Eigen::MatrixXd generateFromStampedImageSequence(std::vector<std::string> image_paths, std::vector<double> timestamps);
void setParameters(float contrast_threshold_pos,
float contrast_threshold_neg,
float refractory_period,
float log_eps,
bool use_log_img)
{
contrast_threshold_pos_ = contrast_threshold_pos;
contrast_threshold_neg_ = contrast_threshold_neg;
refractory_period_ = refractory_period;
log_eps_ = log_eps;
use_log_img_ = use_log_img;
}
private:
Eigen::MatrixXd vec_to_eigen_matrix(std::vector<Event>& events_vec)
{
Eigen::MatrixXd events(events_vec.size(), 4);
for (int i=0; i<events_vec.size(); i++)
{
Event& event = events_vec[i];
events(i,0) = event.x_;
events(i,1) = event.y_;
events(i,2) = event.t_;
events(i,3) = event.polarity_;
}
return events;
}
void imageCallback(const cv::Mat& img, double time, std::vector<Event>& events);
void init(const cv::Mat &img, double time);
void read_directory_from_path(const std::string& name, std::vector<std::string>& v)
{
boost::filesystem::path p(name);
boost::filesystem::directory_iterator start(p);
boost::filesystem::directory_iterator end;
auto path_leaf_string = [](const boost::filesystem::directory_entry& entry) -> std::string {return entry.path().string();};
std::transform(start, end, std::back_inserter(v), path_leaf_string);
std::sort(v.begin(), v.end());
}
float contrast_threshold_pos_;
float contrast_threshold_neg_;
float refractory_period_;
float log_eps_;
bool use_log_img_;
bool is_initialized_;
double current_time_;
cv::Mat ref_values_;
cv::Mat last_img_;
cv::Mat last_event_timestamp_;
int image_height_;
int image_width_;
};
others/rpg_vid2e/esim_py/setup.py 0 → 100644
View file @ a75d2bda
import os
import platform
import re
import subprocess
import sys
from distutils.version import LooseVersion
from setuptools import setup, Extension
from setuptools.command.build_ext import build_ext
class CMakeExtension(Extension):
def __init__(self, name, sourcedir=''):
super().__init__(name, sources=[])
self.sourcedir = os.path.abspath(sourcedir)
class CMakeBuild(build_ext):
def run(self):
try:
out = subprocess.check_output(['cmake', '--version'])
except OSError:
raise RuntimeError("CMake must be installed to build the following extensions: " +
", ".join(e.name for e in self.extensions))
if platform.system() == "Windows":
cmake_version = LooseVersion(re.search(r'version\s*([\d.]+)', out.decode()).group(1))
if cmake_version < '3.1.0':
raise RuntimeError("CMake >= 3.1.0 is required on Windows")
for ext in self.extensions:
self.build_extension(ext)
def build_extension(self, ext):
extdir = os.path.abspath(os.path.dirname(self.get_ext_fullpath(ext.name)))
cmake_args = ['-DCMAKE_LIBRARY_OUTPUT_DIRECTORY=' + extdir,
'-DPYTHON_EXECUTABLE=' + sys.executable]
cfg = 'Debug' if self.debug else 'Release'
build_args = ['--config', cfg]
cmake_args += ['-DCMAKE_BUILD_TYPE=' + cfg]
build_args += ['--', '-j']
env = os.environ.copy()
env['CXXFLAGS'] = '{} -DVERSION_INFO=\\"{}\\"'.format(env.get('CXXFLAGS', ''),
self.distribution.get_version())
if not os.path.exists(self.build_temp):
os.makedirs(self.build_temp)
subprocess.check_call(['cmake', ext.sourcedir] + cmake_args, cwd=self.build_temp, env=env)
subprocess.check_call(['cmake', '--build', '.'] + build_args, cwd=self.build_temp)
setup(
name='esim_py',
version='0.0.1',
author='Daniel Gehrig',
author_email='daniel.gehrig18@gmail.com',
description='Python bindings for ESIM.',
long_description='',
ext_modules=[CMakeExtension('esim_py')],
cmdclass=dict(build_ext=CMakeBuild),
zip_safe=False,
)
others/rpg_vid2e/esim_py/src/bindings.cpp 0 → 100644
View file @ a75d2bda
#include <esim.h>
#include <pybind11/eigen.h>
#include <pybind11/pybind11.h>
#include <pybind11/stl.h>
namespace py = pybind11;
PYBIND11_MODULE(esim_py, m) {
m.doc() = "ESIM bindings";
py::class_<EventSimulator>(m, "EventSimulator")
.def(py::init<float,float,float,float,bool>())
.def("generateFromFolder", &EventSimulator::generateFromFolder, py::return_value_policy::reference_internal)
.def("generateFromVideo", &EventSimulator::generateFromVideo, py::return_value_policy::reference_internal)
.def("generateFromStampedImageSequence", &EventSimulator::generateFromStampedImageSequence, py::return_value_policy::reference_internal)
.def("setParameters", &EventSimulator::setParameters);
}
\ No newline at end of file
others/rpg_vid2e/esim_py/src/esim.cpp 0 → 100644
View file @ a75d2bda
#include <esim.h>
#include <fstream>
#include <iostream>
#include <algorithm>
#include <opencv2/core/eigen.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/imgproc/imgproc.hpp>
EventSimulator::EventSimulator(float contrast_threshold_pos,
float contrast_threshold_neg,
float refractory_period,
float log_eps,
bool use_log_img)
: contrast_threshold_pos_(contrast_threshold_pos), contrast_threshold_neg_(contrast_threshold_neg),
refractory_period_(refractory_period), log_eps_(log_eps), use_log_img_(use_log_img), is_initialized_(false)
{
}
Eigen::MatrixXd EventSimulator::generateFromVideo(std::string video_path, std::string timestamps_file_path)
{
std::ifstream timestamps_file(timestamps_file_path);
if(!timestamps_file.is_open())
throw std::runtime_error("unable to open the file " + timestamps_file_path);
cv::VideoCapture cap(video_path);
if ( !cap.isOpened() )
throw std::runtime_error("Cannot open the video file " + video_path);
std::string time_str;
double time;
std::vector<Event> events_vec;
cv::Mat img, log_img;
while (cap.read(img))
{
img.convertTo(img, CV_32F, 1.0/255);
cv::Mat log_img = img;
if (use_log_img_)
cv::log(img+log_eps_, log_img);
std::getline(timestamps_file, time_str);
time = std::stod(time_str);
imageCallback(log_img, time, events_vec);
}
// reset state to generate new events
is_initialized_ = false;
return vec_to_eigen_matrix(events_vec);
}
Eigen::MatrixXd EventSimulator::generateFromStampedImageSequence(std::vector<std::string> image_paths, std::vector<double> timestamps)
{
// check that timestamps are ascending
if (image_paths.size() != timestamps.size())
throw std::runtime_error("Number of image paths and number of timestamps should be equal. Got " + std::to_string(image_paths.size()) + " and " + std::to_string(timestamps.size()));
cv::Mat img, log_img;
double time;
std::vector<Event> events_vec;
for (int i=0; i<timestamps.size(); i++)
{
if ((i < timestamps.size()-1) && timestamps[i+1]<timestamps[i])
throw std::runtime_error("Timestamps must be sorted in ascending order.");
img = cv::imread(image_paths[i], cv::IMREAD_GRAYSCALE);
if(img.empty())
throw std::runtime_error("unable to open the image " + image_paths[i]);
img.convertTo(img, CV_32F, 1.0/255);
cv::Mat log_img = img;
if (use_log_img_)
cv::log(img+log_eps_, log_img);
time = timestamps[i];
imageCallback(log_img, time, events_vec);
}
// reset state to generate new events
is_initialized_ = false;
return vec_to_eigen_matrix(events_vec);
}
Eigen::MatrixXd EventSimulator::generateFromFolder(std::string image_folder, std::string timestamps_file_path)
{
std::vector<std::string> image_files;
read_directory_from_path(image_folder, image_files);
std::ifstream timestamps_file(timestamps_file_path);
if(!timestamps_file.is_open())
throw std::runtime_error("unable to open the file " + timestamps_file_path);
std::string time_str;
double time;
std::vector<Event> events_vec;
cv::Mat img, log_img;
for (const std::string& file : image_files)
{
img = cv::imread(file, cv::IMREAD_GRAYSCALE);
if(img.empty())
throw std::runtime_error("unable to open the image " + file);
img.convertTo(img, CV_32F, 1.0/255);
cv::Mat log_img = img;
if (use_log_img_)
cv::log(img+log_eps_, log_img);
std::getline(timestamps_file, time_str);
time = std::stod(time_str);
imageCallback(log_img, time, events_vec);
}
// reset state to generate new events
is_initialized_ = false;
return vec_to_eigen_matrix(events_vec);
}
void EventSimulator::init(const cv::Mat &img, double time)
{
is_initialized_ = true;
last_img_ = img;
ref_values_ = img;
last_event_timestamp_ = cv::Mat::zeros(img.size[0], img.size[1], CV_64F);
current_time_ = time;
image_width_ = img.size[1];
image_height_ = img.size[0];
}
void EventSimulator::imageCallback(const cv::Mat& img, double time, std::vector<Event>& events)
{
cv::Mat preprocessed_img = img;
if(!is_initialized_)
{
init(preprocessed_img, time);
return;
}
std::vector<Event> new_events;
static constexpr double kTolerance = 1e-6;
double delta_t = time - current_time_;
for (int y = 0; y < image_height_; ++y)
{
for (int x = 0; x < image_width_; ++x)
{
float& itdt = preprocessed_img.at<float>(y, x);
float& it = last_img_.at<float>(y, x);
float& prev_cross = ref_values_.at<float>(y, x);
if (std::fabs (it - itdt) > kTolerance)
{
float pol = (itdt >= it) ? +1.0 : -1.0;
float C = (pol > 0) ? contrast_threshold_pos_ : contrast_threshold_neg_;
float curr_cross = prev_cross;
bool all_crossings = false;
do
{
curr_cross += pol * C;
if ((pol > 0 && curr_cross > it && curr_cross <= itdt)
|| (pol < 0 && curr_cross < it && curr_cross >= itdt))
{
const double edt = (curr_cross - it) * delta_t / (itdt - it);
const double t = current_time_ + edt;
const double last_stamp_at_xy = last_event_timestamp_.at<double>(y,x);
const double dt = t - last_stamp_at_xy;
if(last_stamp_at_xy == 0 || dt >= refractory_period_)
{
new_events.emplace_back(x, y,t,pol);
last_event_timestamp_.at<double>(y,x) = t;
}
ref_values_.at<float>(y,x) = curr_cross;
}
else
{
all_crossings = true;
}
} while (!all_crossings);
} // end tolerance
} // end for each pixel
}
current_time_ = time;
last_img_ = preprocessed_img; // it is now the latest image
// need to sort the new events before inserting
std::sort(new_events.begin(), new_events.end());
events.insert(events.end(), new_events.begin(), new_events.end());
}
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