julimueller / dtld_parsing Goto Github PK
View Code? Open in Web Editor NEWScripts for loading and visualizing the DriveU Traffic Light Dataset (DTLD)
Scripts for loading and visualizing the DriveU Traffic Light Dataset (DTLD)
Currently, I cannot download from http://www.traffic-light-data.com/.
Can I download the dataset please?
i am trying to run and load the dataset but get the error: cannot connect to X server
. i am running load_dtld.py
with the proper path CLAs. i am currently loading only the berlin dataset, and i have changed the path
and disp_path
in the yaml file to point to the correct image location (based on the output it seems to be correct?). am i missing something?
Opening DriveuDatabase from File: data/dtld/Berlin_all.yml
data/dtld/Berlin/Berlin1/2015-04-17_10-50-05/DE_BBBR667_2015-04-17_10-50-13-633939_k0.tiff
...
Intrinsic Matrix:
[[2.29051e+03 0.00000e+00 1.06694e+03]
[0.00000e+00 2.29051e+03 4.77152e+02]
[0.00000e+00 0.00000e+00 1.00000e+00]]
Extrinsic Matrix:
[[ 0.0037 -0.0453 0.999 2.105 ]
[-0.9998 0.0188 0.0047 0.049 ]
[-0.0189 -0.9988 -0.0452 0.919 ]]
Projection Matrix:
[[2.26969958e+03 0.00000000e+00 1.05129465e+03 0.00000000e+00]
[0.00000000e+00 2.26969958e+03 4.58462746e+02 0.00000000e+00]
[0.00000000e+00 0.00000000e+00 1.00000000e+00 0.00000000e+00]]
Rectification Matrix:
[[ 9.99999e-01 -1.18600e-03 6.77000e-04]
[ 1.18100e-03 9.99972e-01 7.35600e-03]
[-6.86000e-04 -7.35500e-03 9.99973e-01]]
Distortion Matrix:
[[-0.036004 0. 0. 0. 0. ]]
: cannot connect to X server
python 3.6
Ubuntu 16.04
Hello,
Firstly, thank you for your amazing work. I am currently working on DTLD for my thesis. As mentioned in the title, I need to calculate real distance by using disparity images. Finding the depth is straightforward with focal length, baseline, and disparity matrix (considering parallel camera setup). However, I could not figure out how to calculate the 3D location of a point from the depth information. In OpenCV, there is the function cv2.reprojectImageTo3D(disparity_image, Q) where it requires 4x4 Q matrix (projection transformation matrix) and according to documentation, it can be obtained by cv2.stereoRectify(), but this one requires the following:
cameraMatrix1 – First camera matrix.
cameraMatrix2 – Second camera matrix.
distCoeffs1 – First camera distortion parameters.
distCoeffs2 – Second camera distortion parameters.
imageSize – Size of the image used for stereo calibration.
R – Rotation matrix between the coordinate systems of the first and the second cameras.
T – Translation vector between coordinate systems of the cameras.
Checking the calibration data published, I see that I need intrinsic matrix and distortion coefficients for the right camera too.
Could you help me about this task? Thank you very much.
python3 load_dtld.py --label_file /DriveU/dtld_data/v2.0/DTLD_all.json --calib_dir /DriveU/dtld_parsing/calibration --data_base_dir /DriveU/dtld_data
2021-12-19 17:23:08.352 INFO driveu_dataset - open: Opening DriveuDatabase from file: /DriveU/dtld_data/v2.0/DTLD_all.json Traceback (most recent call last): File "load_dtld.py", line 119, in <module> main(parse_args()) File "load_dtld.py", line 61, in main intrinsic_left = calibration.load_intrinsic_matrix( File "/DriveU/dtld_parsing/python/dtld_parsing/calibration.py", line 262, in load_intrinsic_matrix matrix = self.load_calibration_matrix(path) File "/DriveU/dtld_parsing/python/dtld_parsing/calibration.py", line 249, in load_calibration_matrix data = yaml.load(infile) TypeError: load() missing 1 required positional argument: 'Loader'
I have received the email that contain the download link, but the url was missing.
Hi. Is there a way to convert the DriveU dtld to YOLO format?
Thank you in advance
Hi,
I suspect there is something I'm doing wrong, but in the datasets all the ..._k0.tiff
images are black.
Is there something I'm supposed to do to them first so that I can see them?
Thanks.
Why is the image I downloaded is .tiff, and there is no color, not RGB.
How can I get RGB color images?
Hi Julian, I'm working on a fork of this repo to convert the dataset to Tensorflow records and had a quick question regarding calibration. Are the RGB (non-stereo) images provided pre-rectified or do we need to do that manually using the intrinsics provided? I don't see much warping in the sample images but I want to make sure that Tensorflow is ingesting properly rectified data.
EDIT: Looking through the python code, it seems that the bounding box coordinates are rectified using opencv but the images themselves are not. Would I be correct in assuming that the bounding boxes are unrectified and the images themselves are rectified? That would be a little counter-intuitive.
Hello,
Thank you for your work on parsing the dataset, and also for such a great dataset.
I was wondering how we need to create a label map for training using TensorFlow. TensorFlow requires a label map, which namely maps each of the used labels to an integer values. This label map is used both by the training and detection processes.
An example of it is below, assuming dataset contains three labels:
item {
id: 1
name: 'red'
}
item {
id: 2
name: 'green'
}
item {
id: 3
name: 'yellow'
}
I am bit confused about if we need to put all the labels, given we have a lot of attributes in the dataset or what could be the possible workaround? Any help is much appreciated.
Kindly help in finding bounding box of traffic light using gps latitude and longitude
When trying to run "python setup.py install" it gives me this error:
Traceback (most recent call last):
File "setup.py", line 1, in
from setuptools import setup, find_packages
ImportError: No module named setuptools
Saw that some modules were updated to Python 3.
Shouldn't we use the command "python3 setup.py install" instead in order to run it with python 3?
Hi, i got this problem during visualization of images. I did everything according to instructions:
python3 load_dtld.py --label_file Berlin_all.yml --calib_dir /dtld_parsing-master/calibration --data_base_dir /Berlin/
For some time everything was going well, i think:
2020-04-23 14:15:12.976 INFO load_dtld - main: Intrinsic Matrix:
[[2290.51 0. 1066.94 ]
[ 0. 2290.51 477.152]
[ 0. 0. 1. ]]
2020-04-23 14:15:12.977 INFO load_dtld - main: Extrinsic Matrix:
[[ 0.0037 -0.0453 0.999 2.105 ]
[-0.9998 0.0188 0.0047 0.049 ]
[-0.0189 -0.9988 -0.0452 0.919 ]]
2020-04-23 14:15:12.978 INFO load_dtld - main: Projection Matrix:
[[2269.699585 0. 1051.294655 0. ]
[ 0. 2269.699585 458.462746 0. ]
[ 0. 0. 1. 0. ]]
2020-04-23 14:15:12.979 INFO load_dtld - main: Rectification Matrix:
[[ 0.999999 -0.001186 0.000677]
[ 0.001181 0.999972 0.007356]
[-0.000686 -0.007355 0.999973]]
2020-04-23 14:15:12.980 INFO load_dtld - main: Distortion Matrix:
[[-0.036004 0. 0. 0. 0. ]]
But then i got this error:
Traceback (most recent call last):
File "load_dtld.py", line 106, in <module>
main(parse_args())
File "load_dtld.py", line 76, in main
img_disp = img.visualize_disparity_image()
File "/traffic_lights/dtld_parsing-master/python/dtld_parsing/driveu_dataset.py", line 206, in visualize_disparity_image
img = self.get_disparity_image()
File "/traffic_lights/dtld_parsing-master/python/dtld_parsing/driveu_dataset.py", line 189, in get_disparity_image
img[img == 65535] = 0
TypeError: 'NoneType' object does not support item assignment
Do you have any advises for me? Some image didn't find or..?
Hello,
I am trying to load the images from this dataset in natural colors. I use the following code:
img_file = str(image_path)
img = cv2.imread(img_file, cv2.IMREAD_UNCHANGED)
img = cv2.cvtColor(img, cv2.COLOR_BAYER_GB2BGR)
img = np.right_shift(img, 4)
img = img.astype(np.uint8)
plt.figure(figsize=(20,20))
plt.imshow(img)
The "image_path" variable contains the path to one image ending with "k0.tiff". Unfortunately, when I display the images there seems to be a different color setting, as you can see in the attached image (yellow colors are showed as bluish).
Thank you for any help!
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