├── .gitignore ├── LICENSE ├── README.md ├── data ├── img │ ├── aps_00.gif │ ├── ev_00.gif │ └── schema_framework.png ├── noise_neg_0.1lux.npy ├── noise_neg_161lux.npy ├── noise_neg_3klux.mat ├── noise_neg_3klux.npy ├── noise_pos_0.1lux.npy ├── noise_pos_161lux.npy ├── noise_pos_3klux.mat └── noise_pos_3klux.npy ├── examples └── 00_video_2_events │ ├── 0_get_video_youtube.py │ ├── 1_example_video_to_events.py │ └── 2_make_video.py ├── simuDVSICNS_Linux.yml ├── simuDVSICNS_Windows.yml └── src ├── arbiter.py ├── dat_files.py ├── dvs_sensor.py ├── event_buffer.py └── event_display.py /.gitignore: -------------------------------------------------------------------------------- 1 | 2 | .DS_Store 3 | .idea/* 4 | src/__pycache__/* 5 | /data/hummingbird_video.mp4 6 | /examples/00_video_2_events/outputs/ 7 | -------------------------------------------------------------------------------- /LICENSE: -------------------------------------------------------------------------------- 1 | GNU GENERAL PUBLIC LICENSE 2 | Version 3, 29 June 2007 3 | 4 | Copyright (C) 2007 Free Software Foundation, Inc. 5 | Everyone is permitted to copy and distribute verbatim copies 6 | of this license document, but changing it is not allowed. 7 | 8 | Preamble 9 | 10 | The GNU General Public License is a free, copyleft license for 11 | software and other kinds of works. 12 | 13 | The licenses for most software and other practical works are designed 14 | to take away your freedom to share and change the works. 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It is safest 630 | to attach them to the start of each source file to most effectively 631 | state the exclusion of warranty; and each file should have at least 632 | the "copyright" line and a pointer to where the full notice is found. 633 | 634 | 635 | Copyright (C) 636 | 637 | This program is free software: you can redistribute it and/or modify 638 | it under the terms of the GNU General Public License as published by 639 | the Free Software Foundation, either version 3 of the License, or 640 | (at your option) any later version. 641 | 642 | This program is distributed in the hope that it will be useful, 643 | but WITHOUT ANY WARRANTY; without even the implied warranty of 644 | MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the 645 | GNU General Public License for more details. 646 | 647 | You should have received a copy of the GNU General Public License 648 | along with this program. If not, see . 649 | 650 | Also add information on how to contact you by electronic and paper mail. 651 | 652 | If the program does terminal interaction, make it output a short 653 | notice like this when it starts in an interactive mode: 654 | 655 | Copyright (C) 656 | This program comes with ABSOLUTELY NO WARRANTY; for details type `show w'. 657 | This is free software, and you are welcome to redistribute it 658 | under certain conditions; type `show c' for details. 659 | 660 | The hypothetical commands `show w' and `show c' should show the appropriate 661 | parts of the General Public License. Of course, your program's commands 662 | might be different; for a GUI interface, you would use an "about box". 663 | 664 | You should also get your employer (if you work as a programmer) or school, 665 | if any, to sign a "copyright disclaimer" for the program, if necessary. 666 | For more information on this, and how to apply and follow the GNU GPL, see 667 | . 668 | 669 | The GNU General Public License does not permit incorporating your program 670 | into proprietary programs. If your program is a subroutine library, you 671 | may consider it more useful to permit linking proprietary applications with 672 | the library. If this is what you want to do, use the GNU Lesser General 673 | Public License instead of this License. But first, please read 674 | . 675 | 676 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # IEBCS 2 | ICNS Event Based Camera Simulator 3 | 4 | The code base has been recently cut down to a maintainable reference python implementation. For now, if you want the blender interoperability or the C++ implementation, download a previous version of this repository at your own risk. 5 | 6 | This repository contains: 7 | * /data/: Stores distributions used to sample the noise of the sensor and other resources. 8 | * /examples/: An example of loading frames, and passing them as input to the simulator. 9 | 10 | This Figure summarizes the differences with others tools, such as 11 | [ESIM](https://github.com/uzh-rpg/rpg_esim) and 12 | [V2E](https://github.com/SensorsINI/v2e): 13 | 14 | ![alt text](data/img/schema_framework.png) 15 | 16 | ## -- Requirements -- 17 | 18 | Tested with Python 3.12. 19 | 20 | Create a virtual environment using conda: 21 | ``` 22 | pip install opencv-python 23 | pip install tqdm 24 | ``` 25 | 26 | Additional requirements: 27 | * yt-dlp: example 00 downloads a video from youtube. 28 | ``` 29 | pip install yt-dlp 30 | ``` 31 | 32 | ## -- Examples -- 33 | 34 | ### 00: Video -> events 35 | 36 | Simulate events from a video. 37 | 38 | The example sets up a sensor with the following parameters: 39 | * latency = 100 μs 40 | * jitter = 10 μs 41 | * refractory period = 100 μs 42 | * time constant log front-end = 40 μs 43 | * positive/negative log threshold = 0.4 44 | * threshold noise = 0.01 45 | * The noise is sampled from 2 distributions acquired with a real sensor under 161lux. 46 | drawing 47 | drawing 48 | 49 | The artifacts are due to the low framerate compared to the speed of the wings. This can be improved by using high frame rate video, or by generating intermediate frames. 50 | 51 | To use, first make sure your working directory is: 52 | ``` 53 | examples/00_video_to_events 54 | ``` 55 | 56 | Then run the python files contained within this directory in order. 57 | A video showing events, as well as the event file in binary format, should be generated within the `./output` directory. -------------------------------------------------------------------------------- /data/img/aps_00.gif: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/neuromorphicsystems/IEBCS/8fdab5c3d078435d091fa8a94ad657e1fedf0c59/data/img/aps_00.gif -------------------------------------------------------------------------------- /data/img/ev_00.gif: -------------------------------------------------------------------------------- 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https://raw.githubusercontent.com/neuromorphicsystems/IEBCS/8fdab5c3d078435d091fa8a94ad657e1fedf0c59/data/noise_pos_3klux.npy -------------------------------------------------------------------------------- /examples/00_video_2_events/0_get_video_youtube.py: -------------------------------------------------------------------------------- 1 | 2 | import yt_dlp 3 | 4 | URLS = ['https://www.youtube.com/watch?v=RtUQ_pz5wlo'] 5 | 6 | def format_selector(ctx): 7 | """ Select the best video and the best audio that won't result in an mkv. 8 | NOTE: This is just an example and does not handle all cases """ 9 | 10 | # formats are already sorted worst to best 11 | formats = ctx.get('formats')[::-1] 12 | 13 | # acodec='none' means there is no audio 14 | best_video = next(f for f in formats 15 | if f['vcodec'] != 'none' and f['acodec'] == 'none') 16 | 17 | 18 | # These are the minimum required fields for a merged format 19 | yield { 20 | 'format_id': f'{best_video["format_id"]}', 21 | 'ext': best_video['ext'], 22 | 'requested_formats': [best_video], 23 | # Must be + separated list of protocols 24 | 'protocol': f'{best_video["protocol"]}', 25 | } 26 | 27 | 28 | ydl_opts = { 29 | 'format': format_selector, 30 | 'outtmpl': {'default': '../../data/hummingbird_video.%(ext)s'}, 31 | } 32 | 33 | with yt_dlp.YoutubeDL(ydl_opts) as ydl: 34 | ydl.download(URLS) -------------------------------------------------------------------------------- /examples/00_video_2_events/1_example_video_to_events.py: -------------------------------------------------------------------------------- 1 | # Joubert Damien, 03-02-2020 - updated by AvS 22-02-2024 2 | """ 3 | Script converting a video into events. 4 | The framerate of the video might not be the real framerate of the original video. 5 | The user specifies this parameter at the beginning. 6 | Please run get_video_youtube.py before executing this script. 7 | """ 8 | import cv2 9 | import sys 10 | sys.path.append("../../src") 11 | from event_buffer import EventBuffer 12 | from dvs_sensor import DvsSensor 13 | from event_display import EventDisplay 14 | from arbiter import SynchronousArbiter, BottleNeckArbiter, RowArbiter 15 | from tqdm import tqdm 16 | import os 17 | 18 | if not os.path.exists("./outputs"): 19 | os.mkdir("./outputs") 20 | 21 | filename = "../../data/hummingbird_video.mp4" 22 | th_pos = 0.4 # ON threshold = 50% (ln(1.5) = 0.4) 23 | th_neg = 0.4 # OFF threshold = 50% 24 | th_noise= 0.01 # standard deviation of threshold noise 25 | lat = 100 # latency in us 26 | tau = 40 # front-end time constant at 1 klux in us 27 | jit = 10 # temporal jitter standard deviation in us 28 | bgnp = 0.1 # ON event noise rate in events / pixel / s 29 | bgnn = 0.01 # OFF event noise rate in events / pixel / s 30 | ref = 100 # refractory period in us 31 | dt = 1000 # time between frames in us 32 | time = 0 33 | 34 | cap = cv2.VideoCapture(filename) 35 | 36 | # Initialise the DVS sensor 37 | dvs = DvsSensor("MySensor") 38 | dvs.initCamera(int(cap.get(cv2.CAP_PROP_FRAME_WIDTH)), int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT)), 39 | lat=lat, jit = jit, ref = ref, tau = tau, th_pos = th_pos, th_neg = th_neg, th_noise = th_noise, 40 | bgnp=bgnp, bgnn=bgnn) 41 | # To use the measured noise distributions, uncomment the following line 42 | dvs.init_bgn_hist("../../data/noise_pos_161lux.npy", "../../data/noise_neg_161lux.npy") 43 | 44 | # Skip the first 50 frames of the video to remove video artifacts 45 | for i in range(50): 46 | ret, im = cap.read() 47 | 48 | # Convert the image from uint8, such that 255 = 1e4, representing 10 klux 49 | im = cv2.cvtColor(im, cv2.COLOR_RGB2LUV)[:, :, 0] / 255.0 * 1e4 50 | 51 | # Set as the initial condition of the sensor 52 | dvs.init_image(im) 53 | 54 | # Create the event buffer 55 | ev_full = EventBuffer(1) 56 | 57 | # Create the arbiter - optional, pick from one below 58 | # ea = BottleNeckArbiter(0.01, time) # This is a mock arbiter 59 | # ea = RowArbiter(0.01, time) # Old arbiter that handles rows in random order 60 | ea = SynchronousArbiter(0.1, time, im.shape[0]) # DVS346-like arbiter 61 | 62 | # Create the display 63 | render_timesurface = 1 64 | ed = EventDisplay("Events", 65 | cap.get(cv2.CAP_PROP_FRAME_WIDTH), 66 | cap.get(cv2.CAP_PROP_FRAME_HEIGHT), 67 | dt, 68 | render_timesurface) 69 | 70 | if cap.isOpened(): 71 | # Loop over num_frames frames 72 | num_frames = 50 73 | for frame in tqdm(range(num_frames), desc="Converting video to events"): 74 | # Get frame from the video 75 | ret, im = cap.read() 76 | if im is None: 77 | break 78 | # Convert the image from uint8, such that 255 = 1e4, representing 10 klux 79 | im = cv2.cvtColor(im, cv2.COLOR_RGB2LUV)[:, :, 0] / 255.0 * 1e4 80 | # Calculate the events 81 | ev = dvs.update(im, dt) 82 | # Simulate the arbiter 83 | # num_produced = ev.i 84 | # ev = ea.process(ev, dt) 85 | # num_released = ev.i 86 | # statistics for the arbiter 87 | # print("{} produced, {} released".format(num_produced, num_released)) 88 | # Display the events 89 | ed.update(ev, dt) 90 | # Add the events to the buffer for the full video 91 | ev_full.increase_ev(ev) 92 | 93 | cap.release() 94 | # Save the events to a .dat file 95 | ev_full.write('outputs/ev_{}_{}_{}_{}_{}_{}.dat'.format(lat, jit, ref, tau, th_pos, th_noise)) -------------------------------------------------------------------------------- /examples/00_video_2_events/2_make_video.py: -------------------------------------------------------------------------------- 1 | """ 2 | Make video of the events 3 | """ 4 | import cv2 5 | import numpy as np 6 | import sys 7 | sys.path.append("../../src") 8 | from dat_files import load_dat_event 9 | 10 | fourcc = cv2.VideoWriter_fourcc('M', 'J', 'P', 'G') 11 | filename = './outputs/ev_100_10_100_40_0.4_0.01.dat' 12 | ts, x, y, p = load_dat_event(filename) 13 | res = [1920, 1080] 14 | out = cv2.VideoWriter('{}.avi'.format(filename[:-4]), fourcc, 20.0, (res[0], res[1])) 15 | tw = 1000 16 | img = np.zeros((res[1], res[0]), dtype=float) 17 | tsurface = np.zeros((res[1], res[0]), dtype=np.int64) 18 | indsurface = np.zeros((res[1], res[0]), dtype=np.int8) 19 | 20 | for t in range(ts[0], ts[-1], tw): 21 | # Get events in the current time window 22 | ind = np.where((ts > t) & (ts < t + tw)) 23 | 24 | # Create a matrix holding the time stamps of the events 25 | tsurface[:, :] = 0 26 | tsurface[y[ind], x[ind]] = t + tw 27 | 28 | # And another holding their polarity (use -1 for OFF events) 29 | indsurface[y[ind], x[ind]] = 2.0 * p[ind] - 1 30 | 31 | # Find which pixels to process 32 | ind = np.where(tsurface > 0) 33 | 34 | # And update the image 35 | img[:, :] = 125 36 | img[ind] = 125 + indsurface[ind] * np.exp(-(t + tw - tsurface[ind].astype(np.float32))/ (tw/30)) * 125 37 | 38 | # Convert to color and display 39 | img_c = cv2.cvtColor(img.astype(np.uint8), cv2.COLOR_GRAY2BGR) 40 | img_c = cv2.putText(img_c, '{} us'.format(t + tw), (0, 20), cv2.FONT_HERSHEY_SIMPLEX, 0.5, 41 | (255, 255, 255)) 42 | img_c = cv2.applyColorMap(img_c, cv2.COLORMAP_VIRIDIS) 43 | cv2.imshow("debug", img_c) 44 | cv2.waitKey(1) 45 | 46 | # Write video to file 47 | out.write(img_c) 48 | out.release() -------------------------------------------------------------------------------- /simuDVSICNS_Linux.yml: -------------------------------------------------------------------------------- 1 | name: IEBCS 2 | channels: 3 | - conda-forge 4 | dependencies: 5 | - zstd=1.5.5 6 | - xz=5.2.6 7 | - xorg-libxau=1.0.11 8 | - unicodedata2=15.0.0 9 | - tornado=6.3.3 10 | - python=3.10.12 11 | - pthread-stubs=0.4 12 | - pillow=10.0.1 13 | - pandas=2.1.1 14 | - openssl=3.1.3 15 | - openjpeg=2.5.0 16 | - numpy=1.26.0 17 | - matplotlib-base=3.5.3 18 | - matplotlib=3.5.3 19 | - loris=0.5.3 20 | - llvm-openmp=16.0.6 21 | - libzlib=1.2.13 22 | - libxcb=1.15 23 | - libwebp-base=1.3.2 24 | - libtiff=4.6.0 25 | - libssh2=1.11.0 26 | - libsqlite=3.43.0 27 | - libopenblas=0.3.24 28 | - libjpeg-turbo=2.1.5.1 29 | - libgfortran5=13.2.0 30 | - libgfortran 31 | - libev=4.33 32 | - libedit=3.1.20221030 33 | - libdeflate=1.18 34 | - libcurl=8.3.0 35 | - libbrotlienc=1.1.0 36 | - libbrotlidec=1.1.0 37 | - libbrotlicommon=1.1.0 38 | - libaec=1.0.6 39 | - lerc=4.0.0 40 | - lcms2=2.15 41 | - krb5=1.21.2 42 | - kiwisolver=1.4.5 43 | - hdf5=1.14.2 44 | - h5py=3.9.0 45 | - fonttools=4.42.1 46 | - cached-property=1.5.2 47 | - c-ares=1.19.1 48 | - brotli-bin=1.1.0 49 | - brotli=1.1.0 50 | - pip 51 | - pip: 52 | - aedat==2.0.2 53 | - bpy==3.6.0 54 | - build==1.0.3 55 | - charset-normalizer==3.2.0 56 | - cython==3.0.2 57 | - idna==3.4 58 | - mathutils==3.3.0 59 | - opencv-python==4.8.0.76 60 | - pyproject-hooks==1.0.0 61 | - python-mnist==0.7 62 | - requests==2.31.0 63 | - tomli==2.0.1 64 | - urllib3==2.0.4 65 | - zstandard==0.21.0 66 | 67 | -------------------------------------------------------------------------------- /simuDVSICNS_Windows.yml: -------------------------------------------------------------------------------- 1 | name: IEBCS 2 | channels: 3 | - conda-forge 4 | - defaults 5 | dependencies: 6 | - brotli=1.1.0 7 | - bzip2=1.0.8 8 | - c-ares=1.19.1 9 | - ca-certificates=2023.7.22 10 | - cached-property=1.5.2 11 | - cycler=0.11.0 12 | - fonttools=4.42.1 13 | - freetype=2.12.1 14 | - h5py=3.9.0 15 | - hdf5=1.14.2 16 | - kiwisolver=1.4.5 17 | - krb5=1.21.2 18 | - lcms2=2.15 19 | - lerc=4.0.0 20 | - libaec=1.0.6 21 | - libbrotlicommon=1.1.0 22 | - libbrotlidec=1.1.0 23 | - libbrotlienc=1.1.0 24 | - libcurl=8.3.0 25 | - libdeflate=1.18 26 | - libexpat=2.5.0 27 | - libffi=3.4.2 28 | - libjpeg-turbo=2.1.5.1 29 | - libpng=1.6.39 30 | - libsqlite=3.43.0 31 | - libssh2=1.11.0 32 | - libtiff=4.6.0 33 | - libwebp-base=1.3.2 34 | - libzlib=1.2.13 35 | - loris=0.5.3 36 | - matplotlib=3.5.3 37 | - numpy=1.26.0 38 | - openjpeg=2.5.0 39 | - openssl=3.1.3 40 | - pandas=2.1.1 41 | - pillow=10.0.1 42 | - pytz=2023.3.post1 43 | - setuptools=68.2.2 44 | - six=1.16.0 45 | - tk=8.6.12 46 | - tornado=6.3.3 47 | - tqdm=4.66.1 48 | - tzdata=2023c 49 | - wheel=0.41.2 50 | - xz=5.2.6 51 | - zstd=1.5.5 52 | - pip: 53 | - aedat==2.0.2 54 | - bpy==3.6.0 55 | - build==1.0.3 56 | - charset-normalizer==3.2.0 57 | - cython==3.0.2 58 | - idna==3.4 59 | - opencv-python==4.8.0.76 60 | - pyproject-hooks==1.0.0 61 | - python-mnist==0.7 62 | - requests==2.31.0 63 | - tomli==2.0.1 64 | - urllib3==2.0.4 65 | - zstandard==0.21.0 66 | - mathutils==3.3.0 67 | -------------------------------------------------------------------------------- /src/arbiter.py: -------------------------------------------------------------------------------- 1 | import numpy as np 2 | from event_buffer import EventBuffer 3 | 4 | 5 | class BottleNeckArbiter(): 6 | """Simple bottleneck arbiter - doesn't match anything in the real world""" 7 | # t_per_event = 0.1 # Time spent to process one event (us) 8 | # ev_acc = EventBuffer(0) # Events accumulated 9 | # time = 0 # Current time (us) 10 | 11 | def __init__(self, t_per_event, time): 12 | """ Initialise the arbiter 13 | Args: 14 | t_per_event: # Time spent to process one event (us) 15 | time: starting time (us) 16 | """ 17 | self.t_per_event = t_per_event 18 | self.time = time 19 | self.ev_acc = EventBuffer(0) 20 | 21 | def process(self, new_ev, dt): 22 | """ 23 | Args: 24 | new_event: incomming events as EventBuffer 25 | dt: time since the last update (us) 26 | """ 27 | tps_process = float(self.t_per_event) * (self.ev_acc.i + new_ev.i) 28 | self.time = self.time + dt 29 | release_ev = EventBuffer(0) 30 | if tps_process == 0: 31 | return release_ev 32 | self.ev_acc.increase_ev(new_ev) 33 | nb_event_pross = min(self.ev_acc.i, int(dt / tps_process)) 34 | delta = 0 35 | if self.ev_acc.ts[0] < self.time - dt: 36 | delta = self.time - dt - self.ev_acc.ts[0] 37 | release_ev.add_array( 38 | self.ev_acc.ts[:nb_event_pross] + delta + tps_process * np.arange(0, nb_event_pross, 1), 39 | self.ev_acc.y[:nb_event_pross], 40 | self.ev_acc.x[:nb_event_pross], 41 | self.ev_acc.p[:nb_event_pross] 42 | ) 43 | self.ev_acc.remove_elt(nb_event_pross) 44 | return release_ev 45 | 46 | 47 | class RowArbiter(): 48 | """The row arbiter is a simple arbiter, processing events row by row.""" 49 | # t_per_event = 0.1 # Time spent to process one event (us) 50 | # ev_acc = EventBuffer(0) # Events accumulated 51 | # time = 0 # Current time (us) 52 | def __init__(self, t_per_event, time): 53 | """ Initialise the arbiter 54 | Args: 55 | t_per_event: # Time spent to process one event (us) 56 | time: starting time (us) 57 | """ 58 | self.t_per_event = t_per_event 59 | self.time = time 60 | self.ev_acc = EventBuffer(0) 61 | 62 | def process(self, new_ev, dt): 63 | """ 64 | Args: 65 | new_event: incomming events as EventBuffer 66 | dt: time since the last update (us) 67 | """ 68 | tps_process = float(self.t_per_event) * (self.ev_acc.i + new_ev.i) 69 | self.time = self.time + dt 70 | release_ev = EventBuffer(0) 71 | if tps_process == 0: 72 | return release_ev 73 | self.ev_acc.increase_ev(new_ev) 74 | nb_event_pross = int(dt / tps_process) 75 | i = 0 76 | delta = 0 77 | if self.ev_acc.ts[0] < self.time - dt: 78 | delta = self.time - dt - self.ev_acc.ts[0] 79 | while self.ev_acc.i > 0 and self.ev_acc.ts[0] <= self.time and nb_event_pross > i: 80 | i += 1 81 | ind = np.where((self.ev_acc.y == self.ev_acc.y[0]) & (self.ev_acc.ts <= self.time)) 82 | ts_inter = np.full(ind[0].shape, self.ev_acc.ts[0] + delta + tps_process * i) 83 | release_ev.add_array(ts_inter, self.ev_acc.y[ind], self.ev_acc.x[ind], self.ev_acc.p[ind]) 84 | self.ev_acc.remove_row(self.ev_acc.y[0], -1) 85 | return release_ev 86 | 87 | 88 | class SynchronousArbiter(): 89 | """Synchronous row arbiter - based on DAVIS346 arbiter""" 90 | # clock_period = 0.001 # Clock's period (us) 91 | # ev_acc = EventBuffer(0) # Events accumulated 92 | # time = 0 # Current time (us) 93 | # cur_row = 0 # current row processed 94 | # max_row= 200 # Number of rows in sensor 95 | def __init__(self, clock_period, time, max_row): 96 | """ Initialise the arbiter 97 | Args: 98 | max_row: number of rows 99 | clock_period: # Clock's period (us) 100 | time: starting time (us) 101 | """ 102 | self.clock_period = clock_period 103 | self.time = time 104 | self.cur_row = 0 105 | self.max_row = max_row 106 | self.ev_acc = EventBuffer(0) 107 | 108 | def process(self, new_ev, dt): 109 | """ 110 | Args: 111 | new_event: incomming events as EventBuffer 112 | dt: time since the last update (us) 113 | """ 114 | rows_to_process = int(dt // self.clock_period) 115 | t_max = self.time + dt 116 | release_ev = EventBuffer(0) 117 | self.ev_acc.increase_ev(new_ev) 118 | 119 | times = self.time + np.arange(1, rows_to_process + 1) * self.clock_period 120 | rows = np.mod(np.arange(self.cur_row + 1, self.cur_row + rows_to_process + 1), self.max_row) 121 | 122 | for time, row in zip(times, rows): 123 | self.time = time 124 | self.cur_row = row 125 | mask = (self.ev_acc.y[:self.ev_acc.i] == row) & (self.ev_acc.ts[:self.ev_acc.i] < time) 126 | 127 | if np.any(mask): 128 | ts_inter = np.full(np.sum(mask), time) 129 | release_ev.add_array( 130 | ts_inter, self.ev_acc.y[:self.ev_acc.i][mask], 131 | self.ev_acc.x[:self.ev_acc.i][mask], 132 | self.ev_acc.p[:self.ev_acc.i][mask] 133 | ) 134 | self.ev_acc.remove_row(row, time) 135 | 136 | if self.ev_acc.i == 0: 137 | break 138 | 139 | self.time = t_max 140 | return release_ev -------------------------------------------------------------------------------- /src/dat_files.py: -------------------------------------------------------------------------------- 1 | import numpy as np 2 | import struct 3 | from datetime import datetime 4 | 5 | def load_dat_event(filename, start=0, stop=-1, display=False): 6 | """ Load .dat events from file. 7 | Args: 8 | filename: Path of the .dat file 9 | start: starting timestamp (us) 10 | stop: if different than -1, last timestamp 11 | display: display file info 12 | Returns: 13 | ts, x, y, pol numpy arrays of timestamps, positions, and polarities 14 | """ 15 | f = open(filename, 'rb') 16 | if f == -1: 17 | print("The file does not exist") 18 | return 19 | else: 20 | if display: print("Load DAT Events: " + filename) 21 | l = f.readline() 22 | all_lines = l 23 | while l[0] == 37: 24 | p = f.tell() 25 | if display: print(l) 26 | l = f.readline() 27 | all_lines = all_lines + l 28 | # f.close() 29 | all_lines = str(all_lines) 30 | # f = open(filename, 'rb') 31 | f.seek(p, 0) 32 | evType = np.uint8(f.read(1)[0]) 33 | evSize = np.uint8(f.read(1)[0]) 34 | p = f.tell() 35 | l_last = f.tell() 36 | if start > 0: 37 | t = np.uint32(struct.unpack(" 0: 45 | t = np.uint32(struct.unpack(" 0: 61 | v = int(all_lines[ind+8]) 62 | if v >= 2: 63 | x_mask = np.uint32(0x00007FF) 64 | y_mask = np.uint32(0x0FFFC000) 65 | pol_mask = np.uint32(0x10000000) 66 | x_shift = 0 67 | y_shift = 14 68 | pol_shift = 28 69 | else: 70 | x_mask = np.uint32(0x00001FF) 71 | y_mask = np.uint32(0x0001FE00) 72 | pol_mask = np.uint32(0x00020000) 73 | x_shift = 0 74 | y_shift = 9 75 | pol_shift = 17 76 | x = data[1::2] & x_mask 77 | x = x >> x_shift 78 | y = data[1::2] & y_mask 79 | y = y >> y_shift 80 | pol = data[1::2] & pol_mask 81 | pol = pol >> pol_shift 82 | if len(ts) > 0: 83 | if display: 84 | print("First Event: ", ts[0], " us") 85 | print("Last Event: ", ts[-1], " us") 86 | print("Number of Events: ", ts.shape[0]) 87 | return ts, x, y, pol 88 | 89 | 90 | def write_event_dat(filename, ts, x, y, pol, 91 | event_type='dvs', width=None, height=None): 92 | """ Write the events in a .DAT file 93 | The file header begins with %, then event type (one byte uint8) and event lenght 94 | (one byte uint8), then the data are stores ts (4 bytes uint32) and x-y-pol (4 bytes uint32) 95 | Args: 96 | filename: path of the file to create 97 | ts: stimestamp 98 | x, y: positions of the pixels 99 | p: polarities (0 or 1) 100 | """ 101 | f = open(filename, 'wb') 102 | if f == -1: 103 | print("Cannot open the file") 104 | return 105 | if event_type in ['dvs', 'cd', 'td']: 106 | f.write(bytes("% Data file containing DVS events.\n", encoding='utf8')) 107 | elif event_type in ['aps', 'em']: 108 | f.write(bytes("% Data file containing EM events.\n", encoding='utf8')) 109 | else: 110 | raise Exception("Specify a valid event type: 'dvs', 'cd', 'td', 'aps' or 'em'") 111 | 112 | f.write(bytes("% Version 2\n", encoding='utf8')) 113 | f.write(bytes("% Date " + str(datetime.now().replace(microsecond=0)) + '\n', encoding='utf8')) 114 | 115 | if width is None: 116 | width = x.max() + 1 117 | if height is None: 118 | height = y.max() + 1 119 | f.write(bytes("% Height " + str(height) + '\n', encoding='utf8')) 120 | f.write(bytes("% Width " + str(width) + '\n', encoding='utf8')) 121 | 122 | f.write(bytes(np.uint8([0]))) # Event Type 123 | f.write(bytes(np.uint8([8]))) # Event length 124 | arr = np.zeros(2 * ts.shape[0], dtype=np.uint32) 125 | arr[::2] = ts 126 | x_mask = np.uint32(0x00007FF) 127 | y_mask = np.uint32(0x0FFFC000) 128 | pol_mask = np.uint32(0x10000000) 129 | x_shift = 0 130 | y_shift = 14 131 | pol_shift = 28 132 | buf = np.array(x, dtype=np.uint32) << x_shift 133 | arr[1::2] += x_mask & buf 134 | buf = np.array(y, dtype=np.uint32) << y_shift 135 | arr[1::2] += y_mask & buf 136 | buf = np.array(pol, dtype=np.uint32) << pol_shift 137 | arr[1::2] += pol_mask & buf 138 | arr.tofile(f) 139 | f.close() 140 | 141 | if __name__ == '__main__': 142 | ts, x, y, pol = load_dat_event("ev_100_10_100_300_0.3_0.01.dat", start=0, stop=-1, display=True) 143 | print(ts.shape) 144 | -------------------------------------------------------------------------------- /src/dvs_sensor.py: -------------------------------------------------------------------------------- 1 | # Damien JOUBERT 17-01-2020 - Updated by AvS 23-02-2024 2 | import numpy as np 3 | from event_buffer import EventBuffer 4 | from tqdm import tqdm 5 | 6 | # Global variables 7 | # Log bin for the noise distributions 8 | bins = [] 9 | for dec in range(-3, 5, 1): 10 | bins.append(np.arange(10 ** dec, 10 ** (dec + 1), 10 ** dec)) 11 | bins = np.array(bins) 12 | FREQ = bins.reshape(bins.shape[0] * bins.shape[1]) 13 | 14 | # Noise generation methods 15 | NOISE_FREQ = 1 # Pixels have the same +/- noise frequency but with different phases 16 | NOISE_MEASURE = 2 # Pixels have a noise distribution measured in one lighting conditions 17 | 18 | 19 | class DvsSensor: 20 | """ Class to initialise and simulate the DVS sensor """ 21 | # shape = (50, 50) # Size of the imager 22 | # m_th_pos = 0.2 # Mean positive sensitivity (%) 23 | # m_th_neg = -0.2 # Mean negative sensitivity (%) 24 | # m_th_noise = 0.02 # Mean reset noise standard deviation of the transistor (%) 25 | # m_latency = 100 # Mean Latency (us) 26 | # tau = 100 # Time constant (us) of the logarithmic part at 1 klux 27 | # m_jitter = 30 # Mean jitter (us) 28 | # m_bgn_pos = 0.1 # Mean positive background frequency (Hz) 29 | # m_bgn_neg = 0.01 # Mean negative background frequency (Hz) 30 | # m_bgn_pos_per = np.uint64(1e6 / m_bgn_pos) # Mean positive background period (us) 31 | # m_bgn_neg_per = np.uint64(1e6 / m_bgn_neg) # Mean negative background period (us) 32 | # ref = 50 # Refractory period (us) 33 | # time = 0 # Time of the internal counter (us) 34 | # noise_model = NOISE_FREQ # Model of noise used 35 | # last_v = np.zeros(shape, dtype=np.double) # Voltage of each pixel during the last reset 36 | # cur_v = np.zeros(shape, dtype=np.double) # Voltage of each pixel at the time t 37 | # cur_th_pos = np.zeros(shape, dtype=np.double) # Current Positive Threshold 38 | # cur_th_neg = np.zeros(shape, dtype=np.double) # Current Negative Threshold 39 | # cur_ref = np.zeros(shape, dtype=np.uint64) # Time when the pixel will have to be reset 40 | # bgn_pos_next = np.zeros(shape, dtype=np.uint64) # Next expected positive noise event 41 | # bgn_neg_next = np.zeros(shape, dtype=np.uint64) # Next expected negative noise event 42 | # bgn_hist_pos = np.zeros((1, 1, 45), dtype=float) # Positive noise cumulative distributions 43 | # bgn_hist_neg = np.zeros((1, 1, 45), dtype=float) # Negative noise cumulative distributions 44 | # time_px = np.zeros(shape, dtype=np.uint64) # Time t at the pixel (us) 45 | # tau_p = np.zeros(shape, dtype=np.double) # Time constant of each pixel (us) 46 | 47 | def __init__(self, name): 48 | """ Init the sensor by creating the Blender Camera 49 | Args: 50 | name: string to identify the sensor 51 | """ 52 | self.name = name 53 | 54 | def set_shape(self, x, y): 55 | """ Set the shape of the sensor 56 | Args: 57 | x, y: size of the imager 58 | """ 59 | self.shape = (x, y) 60 | 61 | def initCamera(self, x, y, lat, jit, ref, tau, th_pos, th_neg, th_noise, bgnp, bgnn): 62 | """ Set the properties of the DVS sensor 63 | 64 | In this version the sensor positive and negative event's properties are symmetrical 65 | Args: 66 | th_pos: Mean threshold (log change) 67 | th_neg: Mean threshold (log change) 68 | th_n: Threshold noise (log change) 69 | lat: asymptotic (infinite contrast) latency (us) 70 | tau: Time constant of the log conversion (us) 71 | jit: asymptotic jitter (us) 72 | bgn: Mean frequency of the noise (Hz) 73 | """ 74 | self.shape = (x, y) 75 | self.m_th_pos = th_pos 76 | self.m_th_neg = -th_neg 77 | self.m_th_noise = th_noise 78 | self.m_latency = lat 79 | self.tau = tau 80 | self.m_jitter = jit 81 | self.m_bgn_pos = bgnp 82 | self.m_bgn_neg = bgnn 83 | self.m_bgn_pos_per = np.uint64(1e6 / bgnp) 84 | self.m_bgn_neg_per = np.uint64(1e6 / bgnn) 85 | self.ref = ref 86 | self.shape = (self.shape[1], self.shape[0]) 87 | self.last_v = np.zeros(self.shape, dtype=np.double) 88 | self.cur_v = np.zeros(self.shape, dtype=np.double) 89 | self.cur_ref = np.zeros(self.shape, dtype=np.uint64) 90 | self.time_px = np.zeros(self.shape, dtype=np.uint64) 91 | self.tau_p = np.zeros(self.shape, dtype=np.double) 92 | self.cur_ref[:] = np.iinfo(np.uint64).max 93 | self.init_bgn() 94 | self.init_thresholds() 95 | self.time = 0 96 | 97 | def init_bgn(self): 98 | """ Initialise the phases of the background noise 99 | This noise model does not include noise differences between pixel: every pixel will fire noise events a the 100 | same frequency but with a random phase 101 | """ 102 | self.noise_model = NOISE_FREQ 103 | self.bgn_pos_next = np.array(np.random.randint(0, self.m_bgn_pos_per, self.shape), dtype=np.uint64) 104 | self.bgn_neg_next = np.array(np.random.randint(0, self.m_bgn_neg_per, self.shape), dtype=np.uint64) 105 | 106 | def init_bgn_hist(self, filename_noise_pos, filename_noise_neg): 107 | """ Load measured distributions of the noise, 108 | Pick randomly one noise distribution for each pixel and Initialise also randomly the phases of the 109 | background noise 110 | Args: 111 | filename_noise_pos: path of the positive noise's filename 112 | filename_noise_neg: path of the negative noise's filename 113 | """ 114 | self.noise_model = NOISE_MEASURE 115 | noise_pos = np.load(filename_noise_pos) 116 | noise_pos = np.reshape(noise_pos, (noise_pos.shape[0] * noise_pos.shape[1], noise_pos.shape[2])) 117 | if len(noise_pos) == 0: 118 | print(filename_noise_pos, " is not correct") 119 | return 120 | noise_neg = np.load(filename_noise_neg) 121 | noise_neg = np.reshape(noise_neg, (noise_neg.shape[0] * noise_neg.shape[1], noise_neg.shape[2])) 122 | if len(noise_neg) == 0: 123 | print(filename_noise_neg, " is not correct") 124 | return 125 | 126 | # Load histogram and Update next noise event 127 | self.bgn_hist_pos = np.zeros((self.shape[0] * self.shape[1], 72), dtype=float) 128 | self.bgn_hist_neg = np.zeros((self.shape[0] * self.shape[1], 72), dtype=float) 129 | self.bgn_pos_next = np.zeros((self.shape[0], self.shape[1]), dtype=np.uint64) 130 | self.bgn_neg_next = np.zeros((self.shape[0], self.shape[1]), dtype=np.uint64) 131 | 132 | # Pick two spectra for each pixel (one for ON and one for OFF events) 133 | id_n = np.random.uniform(0, noise_neg.shape[0], size=(self.shape[0] * self.shape[1])).astype(int) 134 | id_p = np.random.uniform(0, noise_pos.shape[0], size=(self.shape[0] * self.shape[1])).astype(int) 135 | self.bgn_hist_pos = noise_pos[id_p, :] 136 | self.bgn_hist_neg = noise_neg[id_n, :] 137 | 138 | # Normalise noise spectra 139 | s_p = np.sum(self.bgn_hist_pos, axis=1) 140 | s_n = np.sum(self.bgn_hist_neg, axis=1) 141 | id_p = np.where(s_p == 0) 142 | self.bgn_hist_pos[id_p, 0] = 1 143 | id_n = np.where(s_n == 0) 144 | self.bgn_hist_neg[id_n, 0] = 1 145 | id_p = np.where(s_p > 0) 146 | self.bgn_hist_pos[id_p, :] = self.bgn_hist_pos[id_p, :] / \ 147 | np.repeat(self.bgn_hist_pos[id_p, -2].reshape((1, id_p[0].shape[0], 1)), 148 | self.bgn_hist_pos.shape[1], 149 | axis=2) 150 | id_n = np.where(s_n > 0) 151 | self.bgn_hist_neg[id_n, :] = self.bgn_hist_neg[id_n, :] / \ 152 | np.repeat(self.bgn_hist_neg[id_n, -2].reshape((1, id_n[0].shape[0], 1)), 153 | self.bgn_hist_neg.shape[1], 154 | axis=2) 155 | 156 | # Draw the next noise event time for each pixel 157 | for x in tqdm(range(0, self.shape[0], 1), desc="Noise Init"): 158 | for y in range(0, self.shape[1], 1): 159 | self.bgn_pos_next[x, y] = np.uint64(self.get_next_noise(x, y, 1) * np.random.uniform(0, 1)) 160 | self.bgn_neg_next[x, y] = np.uint64(self.get_next_noise(x, y, 0) * np.random.uniform(0, 1)) 161 | 162 | def init_thresholds(self): 163 | """ Initialise the thresholds of the comparators 164 | The positive and negative threshold share the same noise, which can be changed if necessary 165 | """ 166 | self.cur_th_pos = np.clip(np.array(np.random.normal(self.m_th_pos, self.m_th_noise, self.shape), 167 | dtype=np.double), 0, 1000) 168 | self.cur_th_neg = np.clip(np.array(np.random.normal(self.m_th_neg, self.m_th_noise, self.shape), 169 | dtype=np.double), -1000, 0) 170 | 171 | def init_image(self, img): 172 | """ Initialise the first flux values of the sensor 173 | Args: 174 | img: image whose greylevel corresponds to a radiometric value 175 | It is assumed the maximum radiometric value is 1e6 176 | """ 177 | if img.shape[1] != self.shape[1] or img.shape[0] != self.shape[0]: 178 | print("Error: the size of the image doesn't match with the sensor ") 179 | return 180 | self.last_v = np.log(img + 1) 181 | self.cur_v = np.log(img + 1) 182 | self.tau_p = self.tau * 1e3 / (img + 1) 183 | self.time_px[:, :] = 0 184 | self.time = 0 185 | 186 | def check_noise(self, dt, img_l): 187 | """ Generate event packet of noise 188 | Check if the time at each pixel crossed a next noise event threshold during the update 189 | In this method, every pixel has the same noise rate. 190 | Args: 191 | dt: delay between to images (us) 192 | img_l: log value of the input image 193 | Returns: 194 | A packet of events of type EventBuffer 195 | """ 196 | ind_pos_noise = np.where(self.time + dt > self.bgn_pos_next) 197 | ind_neg_noise = np.where(self.time + dt > self.bgn_neg_next) 198 | pk_noise = EventBuffer(len(ind_pos_noise[0]) + len(ind_neg_noise[0])) 199 | if len(ind_pos_noise[0]) > 0: 200 | pk_noise.add_array(self.bgn_pos_next[ind_pos_noise], ind_pos_noise[0], ind_pos_noise[1], 1) 201 | self.time_px[ind_pos_noise] = self.bgn_pos_next[ind_pos_noise] 202 | self.bgn_pos_next[ind_pos_noise] += self.m_bgn_pos_per 203 | self.cur_v[ind_pos_noise] = img_l[ind_pos_noise] 204 | self.last_v[ind_pos_noise] = img_l[ind_pos_noise] 205 | if len(ind_neg_noise[0]) > 0: 206 | pk_noise.add_array(self.bgn_neg_next[ind_neg_noise], ind_neg_noise[0], ind_neg_noise[1], 0) 207 | self.time_px[ind_neg_noise] = self.bgn_neg_next[ind_neg_noise] 208 | self.bgn_neg_next[ind_neg_noise] += self.m_bgn_neg_per 209 | self.cur_v[ind_neg_noise] = img_l[ind_neg_noise] 210 | self.last_v[ind_neg_noise] = img_l[ind_neg_noise] 211 | pk_noise.sort() 212 | return pk_noise 213 | 214 | def check_noise_hist(self, dt, img_l): 215 | """ Generate event packet of noise 216 | Check if the time at each pixel crossed a next noise event threshold during the update 217 | This method uses a measured noise distribution for each pixel 218 | Args: 219 | dt: delay between two updates (us) 220 | img_l: logarithmic value of the input image 221 | Returns: 222 | A packet of events of type EventBuffer 223 | """ 224 | ind_pos_noise = np.where(self.time + dt > self.bgn_pos_next) 225 | ind_neg_noise = np.where(self.time + dt > self.bgn_neg_next) 226 | pk_noise = EventBuffer(len(ind_pos_noise[0]) + len(ind_neg_noise[0])) 227 | if len(ind_pos_noise[0]) > 0: 228 | pk_noise.add_array(self.bgn_pos_next[ind_pos_noise], ind_pos_noise[0], ind_pos_noise[1], 1) 229 | self.time_px[ind_pos_noise] = self.bgn_pos_next[ind_pos_noise] 230 | self.cur_v[ind_pos_noise] = img_l[ind_pos_noise] 231 | self.last_v[ind_pos_noise] = img_l[ind_pos_noise] 232 | for i in range(0, len(ind_pos_noise[0]), 1): 233 | self.bgn_pos_next[ind_pos_noise[0][i], ind_pos_noise[1][i]] += \ 234 | self.get_next_noise(ind_pos_noise[1][i], ind_pos_noise[0][i], 1) 235 | if len(ind_neg_noise[0]) > 0: 236 | pk_noise.add_array(self.bgn_neg_next[ind_neg_noise], ind_neg_noise[0], ind_neg_noise[1], 0) 237 | self.time_px[ind_neg_noise] = self.bgn_neg_next[ind_neg_noise] 238 | self.cur_v[ind_neg_noise] = img_l[ind_neg_noise] 239 | self.last_v[ind_neg_noise] = img_l[ind_neg_noise] 240 | for i in range(0, len(ind_neg_noise[0]), 1): 241 | self.bgn_neg_next[ind_neg_noise[0][i], ind_neg_noise[1][i]] += \ 242 | self.get_next_noise(ind_neg_noise[1][i], ind_neg_noise[0][i], 0) 243 | pk_noise.sort() 244 | return pk_noise 245 | 246 | def get_next_noise(self, x, y, pol): 247 | """ Updates the next noise event 248 | Take a value between 0 and 1 and find the delay of the next noise event 249 | Args: 250 | x, y: coordinate of the pixel 251 | pol: polarity of the noise 252 | Returns: 253 | the delay of the next noise event in us 254 | """ 255 | val = np.random.uniform(0, 1) 256 | pos = y * self.shape[0] + x 257 | if pol == 1: 258 | ind = np.where(self.bgn_hist_pos[pos, :] >= val) 259 | next = FREQ[ind[0][0]] 260 | else: 261 | ind = np.where(self.bgn_hist_neg[pos, :] >= val) 262 | next = FREQ[ind[0][0]] 263 | return np.uint64(1e6 / next) 264 | 265 | def get_latency(self, time_end, last_v, cur_th, cur_v, img_l, time_px): 266 | """ Obtain the latency of the pixel 267 | Method: Linearly interpolates the time when it crosses the threshold 268 | and add the constant latency of the comparator stage. 269 | Args: 270 | time_end: time of the change (us) 271 | last_v: voltage at the last spike (np.array) 272 | cur_th: threshold (np.array) 273 | cur_v: voltage at time_px (np.array) 274 | last_v: voltage during the last spike (np.array) 275 | Returns: 276 | np.array of the latencies in us 277 | """ 278 | return np.uint64((last_v + cur_th - cur_v) / (img_l - cur_v) * (time_end - time_px) + \ 279 | np.random.normal(self.m_latency, self.m_jitter, last_v.shape[0])) 280 | 281 | def get_latency_tau(self, cur_th, cur_v, img_l, tau_p): 282 | """ Obtain the latency of the pixel 283 | Method: First order low pass filter interpolation of the time when 284 | it crosses the threshold and add the constant latency of the 285 | comparator stage 286 | Args: 287 | last_v: voltage at the last spike 288 | cur_th: threshold 289 | cur_v: voltage at time_px 290 | tau_p: time constants of the pixels 291 | Returns: 292 | np.array of the latencies in us 293 | """ 294 | amp = np.divide(cur_th - cur_v, img_l - cur_v) 295 | jit = np.sqrt(self.m_jitter ** 2 + np.power(self.m_th_noise * tau_p / (img_l - cur_v), 2)) 296 | t_ev = np.random.normal(self.m_latency - tau_p*np.log(1 - amp), jit) 297 | return np.uint64(np.clip(t_ev, 0, 10000)) 298 | 299 | def update(self, img, dt): 300 | """ Update the sensor with a nef irradiance's frame 301 | Follow the ICNS model 302 | Args: 303 | img: radiometric value in the focal plane 304 | dt: delay between the frame and the last one (us) 305 | Returns: 306 | EventBuffer of the created events 307 | """ 308 | if img.shape[1] != self.shape[1] or img.shape[0] != self.shape[0]: 309 | print("Error: the size of the image doesn't match with the sensor ") 310 | return 311 | 312 | # Convert in the log domain 313 | img_l = np.array(img, dtype=np.double) 314 | ind = np.where(img > 0) 315 | if len(ind[0]) == 0: 316 | print("ERROR: update: flux image with only zeros") 317 | return 318 | img_l[ind] = np.log(img[ind] + 1) 319 | 320 | # Update time constants - self.tau defined at 1 klux 321 | self.tau_p[ind] = self.tau * 1e3 / (img[ind] + 1) 322 | 323 | # Update refractory and reset pixels 324 | ind_ref = np.where(self.cur_ref < self.time + dt) 325 | px_delta_ref = np.array(self.cur_ref[ind_ref] - self.time, dtype=float) 326 | if len(ind_ref[0]) > 0: 327 | # Calculate voltage at the reset time (end of refractory period) 328 | self.last_v[ind_ref] = self.cur_v[ind_ref] + (img_l[ind_ref] - self.cur_v[ind_ref]) * \ 329 | (1 - np.exp(-px_delta_ref / self.tau_p[ind_ref])) 330 | # End the refractory period 331 | self.time_px[ind_ref] = self.cur_ref[ind_ref] 332 | self.cur_ref[ind_ref] = np.iinfo(np.uint64).max 333 | # And update the reference voltage for these pixels 334 | self.cur_v[ind_ref] = self.last_v[ind_ref] 335 | 336 | # Get noise events and reset pixels 337 | if self.noise_model == NOISE_FREQ: 338 | pk_noise = self.check_noise(dt, img_l) 339 | else: 340 | pk_noise = self.check_noise_hist(dt, img_l) 341 | 342 | # Calculate voltage change at the end of the frame 343 | px_delta_t = np.array(self.time + dt - self.time_px[ind], dtype=float) 344 | target = np.zeros(img_l.shape) 345 | target[ind] = self.cur_v[ind] + (img_l[ind] - self.cur_v[ind]) * \ 346 | (1 - np.exp(-px_delta_t / self.tau_p[ind])) 347 | dif = target - self.last_v 348 | 349 | # Check in which pixels the change is larger than the thresholds 350 | ind_pos = np.where((dif > self.cur_th_pos) & (self.cur_ref == np.iinfo(np.uint64).max)) 351 | ind_neg = np.where((dif < self.cur_th_neg) & (self.cur_ref == np.iinfo(np.uint64).max)) 352 | 353 | # Generate events for these pixels 354 | pk = EventBuffer(0) 355 | while len(ind_pos[0]) + len(ind_neg[0]) > 0: 356 | pk.increase(len(ind_pos[0]) + len(ind_neg[0])) 357 | 358 | # ON events 359 | if len(ind_pos[0]) > 0: 360 | # Get event times 361 | # Use this for first order interpolation 362 | t_event = self.get_latency_tau( 363 | self.last_v[ind_pos] + self.cur_th_pos[ind_pos], 364 | self.cur_v[ind_pos], 365 | img_l[ind_pos], 366 | self.tau_p[ind_pos] 367 | ) 368 | # Or this for linear interpolation 369 | # t_event = self.get_latency(self.time + dt, 370 | # self.last_v[ind_pos], 371 | # self.cur_th_pos[ind_pos], 372 | # self.cur_v[ind_pos], 373 | # img_l[ind_pos], 374 | # self.time_px[ind_pos] 375 | # ) 376 | # Add to the event buffer 377 | pk.add_array(self.time_px[ind_pos] + t_event, ind_pos[0], ind_pos[1], 1) 378 | # Update the threshold with noise 379 | self.cur_th_pos[ind_pos] = np.clip( 380 | np.random.normal(self.m_th_pos, self.m_th_noise, len(ind_pos[0])), 381 | 0, 382 | 1000 383 | ) 384 | # Start the refractory period for those pixels that fired 385 | self.cur_ref[ind_pos] = self.time_px[ind_pos] + t_event + self.ref 386 | 387 | # OFF events 388 | if len(ind_neg[0]) > 0: 389 | # Get event times 390 | # Use this for first order interpolation 391 | t_event = self.get_latency_tau( 392 | self.last_v[ind_neg] + self.cur_th_neg[ind_neg], 393 | self.cur_v[ind_neg], 394 | img_l[ind_neg], 395 | self.tau_p[ind_neg] 396 | ) 397 | # Or this for linear interpolation 398 | # t_event = self.get_latency(self.time + dt, 399 | # self.last_v[ind_neg], 400 | # self.cur_th_neg[ind_neg], 401 | # self.cur_v[ind_neg], 402 | # img_l[ind_neg], 403 | # self.time_px[ind_neg] 404 | # ) 405 | # Add to the event buffer 406 | pk.add_array(self.time_px[ind_neg] + t_event, ind_neg[0], ind_neg[1], 0) 407 | # Update the threshold with noise 408 | self.cur_th_neg[ind_neg] = np.clip( 409 | np.random.normal(self.m_th_neg, self.m_th_noise, len(ind_neg[0])), 410 | -1000, 411 | 0 412 | ) 413 | # Start the refractory period for those pixels that fired 414 | self.cur_ref[ind_neg] = self.time_px[ind_neg] + t_event + self.ref 415 | 416 | # Check if any of these refractory periods finish before the end of the frame 417 | ind_ref = np.where(self.cur_ref < self.time + dt) 418 | px_delta_ref = np.array(self.cur_ref[ind_ref]-self.time_px[ind_ref], dtype=float) 419 | if len(ind_ref[0]) > 0: 420 | # Calculate voltage at the reset time (end of refractory period) 421 | self.last_v[ind_ref] = self.cur_v[ind_ref] + (img_l[ind_ref] - self.cur_v[ind_ref]) * \ 422 | (1 - np.exp(-px_delta_ref / self.tau_p[ind_ref])) 423 | # End the refractory period 424 | self.time_px[ind_ref] = self.cur_ref[ind_ref] 425 | self.cur_ref[ind_ref] = np.iinfo(np.uint64).max 426 | # And update the reference voltage for these pixels 427 | self.cur_v[ind_ref] = self.last_v[ind_ref] 428 | 429 | # Now check if there are any new threshold crossings since the previous event 430 | dif = np.zeros((self.shape[0], self.shape[1])) 431 | px_delta_ref = np.array(self.time + dt - self.time_px[ind_ref], dtype=float) 432 | target[ind_ref] = self.cur_v[ind_ref] + (img_l[ind_ref] - self.cur_v[ind_ref]) * \ 433 | (1 - np.exp(-px_delta_ref / self.tau_p[ind_ref])) 434 | dif[ind_ref] = target[ind_ref] - self.last_v[ind_ref] 435 | ind_pos = np.where(dif > self.cur_th_pos) 436 | ind_neg = np.where(dif < self.cur_th_neg) 437 | # Repeat this loop until no more threshold crossings are found 438 | 439 | # Update pixel voltages at end of frame 440 | px_delta_t = np.array(self.time + dt - self.time_px[ind], dtype=float) 441 | self.cur_v[ind] = self.cur_v[ind] + (img_l[ind] - self.cur_v[ind]) * \ 442 | (1 - np.exp(-px_delta_t / self.tau_p[ind])) 443 | 444 | # Update simulation time 445 | self.time += dt 446 | self.time_px[:] = self.time 447 | 448 | # Merge noise and signal events and sort by time 449 | pk_end = EventBuffer(0) 450 | pk_end.merge(pk, pk_noise) 451 | pk_end.sort() 452 | 453 | return pk_end 454 | 455 | 456 | 457 | -------------------------------------------------------------------------------- /src/event_buffer.py: -------------------------------------------------------------------------------- 1 | import numpy 2 | import numpy as np 3 | from dat_files import write_event_dat 4 | 5 | 6 | class EventBuffer(): 7 | """ Structure to handle a buffer of dvs events """ 8 | x = 0 # Array of x values 9 | y = 0 # Array of y values 10 | ts = 0 # Array of timestamps values (us) 11 | p = 0 # Array of polarity values (0 negative, 1 positive) 12 | i = 0 # Position of the next event 13 | 14 | def __init__(self, size): 15 | """ Resize the buffers 16 | Args: 17 | size: size of the new buffer, Minimum: 1 18 | """ 19 | if size == 0: 20 | size = 1 21 | self.x = np.zeros(size, dtype=np.uint16) 22 | self.y = np.zeros(size, dtype=np.uint16) 23 | self.p = np.zeros(size, dtype=np.uint8) 24 | self.ts = np.zeros(size, dtype=np.uint64) 25 | self.i = 0 26 | 27 | def get_x(self): 28 | return self.x[:self.i] 29 | 30 | def get_y(self): 31 | return self.y[:self.i] 32 | 33 | def get_p(self): 34 | return self.p[:self.i] 35 | 36 | def get_ts(self): 37 | return self.ts[:self.i] 38 | 39 | def increase(self, nsize): 40 | """ Increase the size of a buffer to self.shape[0] size + nsize 41 | Args: 42 | nsize: number of free space elements to add 43 | """ 44 | prev_shape = self.x.shape[0] 45 | x = np.zeros(prev_shape + nsize, dtype=np.uint16) 46 | y = np.zeros(prev_shape + nsize, dtype=np.uint16) 47 | p = np.zeros(prev_shape + nsize, dtype=np.uint8) 48 | ts = np.zeros(prev_shape + nsize, dtype=np.uint64) 49 | x[:prev_shape] = self.x 50 | y[:prev_shape] = self.y 51 | p[:prev_shape] = self.p 52 | ts[:prev_shape] = self.ts 53 | self.x = x 54 | self.y = y 55 | self.p = p 56 | self.ts = ts 57 | 58 | def remove_time(self, t_min, t_max): 59 | """ 60 | Only keep events between t_min and t_max 61 | """ 62 | ind = np.where((self.ts < t_min) | (self.ts > t_max)) 63 | self.x = np.delete(self.x, ind) 64 | self.y = np.delete(self.y, ind) 65 | self.ts = np.delete(self.ts, ind) 66 | self.p = np.delete(self.p, ind) 67 | self.i = self.ts.shape[0] 68 | 69 | def remove_elt(self, nsize): 70 | """ 71 | Remove the nsize first elements 72 | """ 73 | if self.i - nsize < 0: 74 | nsize = self.i 75 | ind = np.arange(0, nsize, 1) 76 | self.x = np.delete(self.x, ind) 77 | self.y = np.delete(self.y, ind) 78 | self.ts = np.delete(self.ts, ind) 79 | self.p = np.delete(self.p, ind) 80 | self.i = self.i - nsize 81 | 82 | def remove_ev(self, p): 83 | """ 84 | Remove the event at the position p 85 | """ 86 | if self.i <= p: 87 | return 88 | self.x = np.delete(self.x, p) 89 | self.y = np.delete(self.y, p) 90 | self.ts = np.delete(self.ts, p) 91 | self.p = np.delete(self.p, p) 92 | self.i -= 1 93 | 94 | def remove_row(self, r, t): 95 | """ 96 | Remove the event in row r at time t 97 | """ 98 | if t == -1: 99 | ind = np.where((self.y == r) & (self.ts > 0)) 100 | else: 101 | ind = np.where((self.y == r) & (self.ts < t) & (self.ts > 0)) 102 | self.x = np.delete(self.x, ind) 103 | self.y = np.delete(self.y, ind) 104 | self.ts = np.delete(self.ts, ind) 105 | self.p = np.delete(self.p, ind) 106 | self.i -= ind[0].shape[0] 107 | 108 | def increase_ev(self, ev): 109 | """ Extend the event buffer with another event buffer 110 | If ev can be inserted into self, ev inserted, if not, increase the size of a buffer to original 111 | self.shape[0] + ev.shape[0] 112 | Args: 113 | ev: the EventBuffer added 114 | """ 115 | if len(self.x) > 0 and not ev is None: 116 | if self.i + ev.x.shape[0] > self.x.shape[0] - 1: 117 | prev_shape = self.x.shape[0] 118 | x = np.zeros(prev_shape + ev.ts.shape[0], dtype=np.uint16) 119 | y = np.zeros(prev_shape + ev.ts.shape[0], dtype=np.uint16) 120 | p = np.zeros(prev_shape + ev.ts.shape[0], dtype=np.uint8) 121 | ts = np.zeros(prev_shape + ev.ts.shape[0], dtype=np.uint64) 122 | x[:self.i] = self.x[:self.i] 123 | y[:self.i] = self.y[:self.i] 124 | p[:self.i] = self.p[:self.i] 125 | ts[:self.i] = self.ts[:self.i] 126 | x[self.i:self.i + ev.x.shape[0]] = ev.x 127 | y[self.i:self.i + ev.x.shape[0]] = ev.y 128 | p[self.i:self.i + ev.x.shape[0]] = ev.p 129 | ts[self.i:self.i + ev.x.shape[0]] = ev.ts 130 | self.x = x 131 | self.y = y 132 | self.p = p 133 | self.ts = ts 134 | else: 135 | self.x[self.i:self.i + ev.i] = ev.x[:ev.i] 136 | self.y[self.i:self.i + ev.i] = ev.y[:ev.i] 137 | self.p[self.i:self.i + ev.i] = ev.p[:ev.i] 138 | self.ts[self.i:self.i + ev.i] = ev.ts[:ev.i] 139 | self.i += ev.i 140 | 141 | def copy(self, i1, ep, i2): 142 | """ Copy the i2 th event of the EventBuffer ep in to the i1 th position 143 | Args: 144 | i1: self will have a new event in i1 145 | ep: EventBuffer where the event comes from 146 | i2: i2th event from ep is takem 147 | """ 148 | if i1 < len(self.x): 149 | self.x[i1] = ep.x[i2] 150 | self.y[i1] = ep.y[i2] 151 | self.ts[i1] = ep.ts[i2] 152 | self.p[i1] = ep.p[i2] 153 | self.i = i1 + 1 154 | 155 | def merge(self, ep1, ep2): 156 | """ Resize the EventBuffer and merge into the two EventBuffers ep1 nd ep2, sorted by their timestamps 157 | Args: 158 | ep1, ep2: eventBuffer 159 | """ 160 | self.__init__(len(ep1.x) + len(ep2.x)) 161 | i1 = 0 162 | i2 = 0 163 | for j in range(0, ep1.i + ep2.i, 1): 164 | if i1 == ep1.i: 165 | self.copy(j, ep2, i2) 166 | i2 += 1 167 | elif i2 == ep2.i: 168 | self.copy(j, ep1, i1) 169 | i1 += 1 170 | else: 171 | if ep1.ts[i1] < ep2.ts[i2]: 172 | self.copy(j, ep1, i1) 173 | i1 += 1 174 | else: 175 | self.copy(j, ep2, i2) 176 | i2 += 1 177 | self.i = ep1.i + ep2.i 178 | 179 | def sort(self): 180 | """ Sort the EventBuffer according to its timestamp """ 181 | ind = np.argsort(self.ts[:self.i]) 182 | self.ts[:self.i] = self.ts[:self.i][ind] 183 | self.x[:self.i] = self.x[:self.i][ind] 184 | self.y[:self.i] = self.y[:self.i][ind] 185 | self.p[:self.i] = self.p[:self.i][ind] 186 | 187 | def add(self, ts, y, x, p): 188 | """ 189 | Add an event (ts, x, y, p) to the EventBuffer (push strategy) 190 | If y == -1, if means that x[0] contains the x position and x[1] the y position. 191 | Args: 192 | ts, y, x, p: new event array 193 | """ 194 | if self.x.shape[0] == self.i: 195 | self.increase(1000) 196 | self.add(ts, y, x, p) 197 | else: 198 | self.ts[self.i] = ts 199 | self.x[self.i] = x 200 | self.y[self.i] = y 201 | self.p[self.i] = p 202 | self.i += 1 203 | 204 | def add_array(self, ts, y, x, p, inc=1000): 205 | """ 206 | Add n events (ts, x, y, p) to the EventBuffer (push strategy) 207 | Args: 208 | ts, y, x, p: new event array 209 | inc: increment size 210 | """ 211 | s = len(ts) 212 | if s > len(self.ts) - self.i: 213 | self.increase(inc) 214 | self.add_array(ts, y, x, p) 215 | else: 216 | self.ts[self.i:self.i + s] = ts 217 | self.x[self.i:self.i + s] = x 218 | self.y[self.i:self.i + s] = y 219 | self.p[self.i:self.i + s] = p 220 | self.i += s 221 | 222 | def write(self, filename, width=None, height=None): 223 | """ Write the events into a .dat file 224 | Args: 225 | filename: path of the file 226 | """ 227 | # sort events to have a monotonically timestamps 228 | self.sort() 229 | write_event_dat(filename, self.ts[:self.i], self.x[:self.i], self.y[:self.i], self.p[:self.i], 230 | event_type='dvs', width=width, height=height) 231 | -------------------------------------------------------------------------------- /src/event_display.py: -------------------------------------------------------------------------------- 1 | import numpy as np 2 | import cv2 3 | 4 | 5 | class EventDisplay(): 6 | """ Structure to handle the thread created by OpenCV to render an image """ 7 | name = "test" # Name of the window 8 | time = 0 # Internal counter of the display (us) 9 | last_frame = 0 # Time of the last frame 10 | frametime = 100000 # Time to refresh the display (us) 11 | time_surface = np.zeros((10, 10), dtype=np.uint64) # Timestamp of the last event in the focal plane 12 | pol_surface = np.zeros((10, 10), dtype=np.uint8) # Polarity of the last event in the focal plane 13 | im = np.zeros((10, 10, 3), dtype=np.uint8) # Image to render 14 | render = 0 # 0: binary image, 1: ts 15 | render_tau = 40000 # tau decay of the time surface (us) 16 | display_time = True 17 | 18 | def __init__(self, name, dx, dy, frametime, render=0): 19 | """ Initialize the Display by reseting the internal timer of the structure and providing the right size of 20 | buffers 21 | Args: 22 | name: name of the windows 23 | dy dx: size of the data 24 | frametime: delay between two frames (us) 25 | render: rendering method: 0 = binary, 1 = timesurface 26 | """ 27 | self.name = name 28 | self.time = 0 29 | self.last_frame = 0 30 | self.frametime = frametime 31 | self.time_surface = np.zeros((int(dy), int(dx)), dtype=np.uint64) 32 | self.pol_surface = np.zeros((int(dy), int(dx)), dtype=np.uint8) 33 | self.im = np.zeros((int(dy), int(dx), 3), dtype=np.uint8) 34 | self.render = 0 35 | self.render_tau = 3 * frametime 36 | 37 | def reset(self): 38 | """ Reset timers and buffers to 0 """ 39 | self.time = 0 40 | self.last_frame = 0 41 | self.time_surface[:] = 0 42 | self.pol_surface[:] = 0 43 | 44 | def update(self, pk, dt): 45 | """ During the time dt, the EventBuffer was created. This function adds these events to the structure and 46 | triggers a display if needed 47 | Args: 48 | pk: EventBuffer 49 | dt: delay since the last update 50 | """ 51 | self.time_surface[pk.y[:pk.i], pk.x[:pk.i]] = pk.ts[:pk.i] 52 | self.pol_surface[pk.y[:pk.i], pk.x[:pk.i]] = pk.p[:pk.i] 53 | self.time += dt 54 | self.last_frame += dt 55 | if self.last_frame > self.frametime: 56 | self.last_frame = 0 57 | self.im[:] = 125 58 | if self.render == 0: 59 | ind = np.where((self.time_surface > self.time - self.frametime) & (self.time_surface <= self.time)) 60 | self.im[:, :, 0][ind] = self.pol_surface[ind]*255 61 | self.im[:, :, 1][ind] = self.pol_surface[ind]*255 62 | self.im[:, :, 2][ind] = self.pol_surface[ind]*255 63 | if self.render == 1: 64 | self.im[:, :, 0] = (self.pol_surface * 2 - 1) * 125 * np.exp(-(self.time - self.time_surface.astype(np.double)) / self.render_tau) 65 | if self.display_time: self.im = cv2.putText(self.im, '{} s'.format(self.time / 1e6), (0, 20), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (255, 0, 255)) 66 | cv2.imshow(self.name, self.im) 67 | cv2.waitKey(10) 68 | 69 | 70 | 71 | --------------------------------------------------------------------------------