From 76921cc22e2ba9632fa85227b1a10b1f90ffa80b Mon Sep 17 00:00:00 2001 From: supitalp Date: Mon, 16 Sep 2019 14:35:03 +0200 Subject: [PATCH] Created Simulating events from a video (markdown) --- Simulating-events-from-a-video.md | 85 +++++++++++++++++++++++++++++++ 1 file changed, 85 insertions(+) create mode 100644 Simulating-events-from-a-video.md diff --git a/Simulating-events-from-a-video.md b/Simulating-events-from-a-video.md new file mode 100644 index 0000000..7f773a2 --- /dev/null +++ b/Simulating-events-from-a-video.md @@ -0,0 +1,85 @@ +In this tutorial, we will show how to use ESIM to simulate events from a given video. + +### Overview + +An overview of the conversion method is shown in the diagram below. First, we will extract the individual frames from the input video in a folder. Second, we will run ESIM, providing the image folder as an input to simulate events. +Finally, we will see how to visualize the simulated events using the `dvs_renderer` node. + +[[https://github.com/uzh-rpg/rpg_esim/blob/master/event_camera_simulator/img/overview_video_to_events.png]] + +### (Optional) Download an example video + +As an example input video, we will use this [nice video](https://youtu.be/THA_5cqAfCQ) from National Geographic, which shows a running cheetah recorded at 1200 frames per second with a Phantom camera. + +- Create a working folder: +``` +mkdir -p /tmp/cheetah_example +cd /tmp/cheetah_example +``` +- Download the video from YouTube using `youtube-dl` (`pip install youtube-dl`): +``` +youtube-dl https://youtu.be/THA_5cqAfCQ -o cheetah +``` + +- Cut the part of the video that is relevant. In our case, we will cut the slow motion part from `2'07` to `2'47''`: +``` +ffmpeg -i cheetah.mkv -ss 00:02:07 -t 00:00:40 -async 1 -strict -2 cheetah_cut.mkv +``` + +- Optionally, resize the video to a smaller size for faster processing. Here, we will resize the video to a width of `640`: +``` +ffmpeg -i cheetah_cut.mkv -vf scale=640:-1 -crf 0 cheetah_sd.mkv +``` + +### Pre-process the video for ESIM + +- Export the video to a sequence of individual frames in the `frames` folder: +``` +mkdir frames +ffmpeg -i cheetah_sd.mkv frames/frames_%010d.png +``` + +- Finally, create an `images.csv` file in the `frames` folder, which will be necessary for ESIM. Each line of this file contains the image timestamp and path in the format: `timestamp_in_nanoseconds,frames_xxxxx.png`: +``` +roscd esim_ros +python scripts/generate_stamps_file.py -i /tmp/cheetah_example/frames -r 1200.0 +``` +where `-i` specifies the path to the folder containing the frames, and `-r` specifies the input video framerate (`1200 fps` in our case). + +### Simulate events with ESIM + +``` +rosrun esim_ros esim_node \ + --data_source=2 \ + --path_to_output_bag=/tmp/out.bag \ + --path_to_data_folder=/tmp/cheetah_example/frames \ + --ros_publisher_frame_rate=60 \ + --exposure_time_ms=10.0 + --use_log_image=1 \ + --log_eps=0.1 \ + --contrast_threshold_pos=0.15 \ + --contrast_threshold_neg=0.15 \ +``` + +If you get an error message: `Could not find ROS master`, open a new terminal, and start a `roscore` as follows: `roscore`. + +#### Explanation of the parameters + + - `--data_source=2`: tells ESIM to read from a folder containing images. ESIM will look for an `images.csv` file describing the timestamps of the images to read. + - `--path_to_data_folder`: path to the folder where the frames and the `images.csv` file are located. + - `--path_to_output_bag`: the generated data (events and frames) will be saved into a rosbag at this location + - `--ros_publisher_frame_rate`: frame rate of the simulated APS (frame) sensor (in frames per second). + - `--exposure_time_ms`: exposure time of the simulated APS (frame) sensor (in milliseconds). + - `--use_log_image=1`: tells ESIM to operate in the log-intensity domain. This means each input image will be converted to log, as follows: `L = ln(I / 255 + eps)`, where `eps` is set via the `--log_eps` parameter. + - `--contrast_threshold_pos` and `--contrast_threshold_neg`: values of the positive (resp. negative) contrast threshold. A lower value means a higher sensitivity (more events). A higher value means a lower sensitivity (less events). + +### Visualizing the simulated event data + +After running ESIM as shown in the previous section, all the simulated data is saved in a rosbag (at `/tmp/out.bag` in our example). +To visualize the events, you can open a new terminal, and start the `dvs_renderer` node as follows: +``` +rosrun dvs_renderer dvs_renderer events:=/cam0/events +``` + +Then, you can play the saved rosbag: `rosbag play /tmp/out.bag`. +Finally, you can visualize the simulated events by opening `rqt_image_view` (in another terminal): `rqt_image_view /dvs_rendering`.