Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

confused with the label list #10

Closed
passion3394 opened this issue Oct 30, 2018 · 13 comments
Closed

confused with the label list #10

passion3394 opened this issue Oct 30, 2018 · 13 comments

Comments

@passion3394
Copy link

labels = [
# name id trainId category catId hasInstances ignoreInEval color
Label( 'void' , 0 , 0, 'void' , 0 , False , False , ( 0, 0, 0) ),
Label( 's_w_d' , 200 , 1 , 'dividing' , 1 , False , False , ( 70, 130, 180) ),
Label( 's_y_d' , 204 , 2 , 'dividing' , 1 , False , False , (220, 20, 60) ),
Label( 'ds_w_dn' , 213 , 3 , 'dividing' , 1 , False , True , (128, 0, 128) ),
Label( 'ds_y_dn' , 209 , 4 , 'dividing' , 1 , False , False , (255, 0, 0) ),
Label( 'sb_w_do' , 206 , 5 , 'dividing' , 1 , False , True , ( 0, 0, 60) ),
Label( 'sb_y_do' , 207 , 6 , 'dividing' , 1 , False , True , ( 0, 60, 100) ),
Label( 'b_w_g' , 201 , 7 , 'guiding' , 2 , False , False , ( 0, 0, 142) ),
Label( 'b_y_g' , 203 , 8 , 'guiding' , 2 , False , False , (119, 11, 32) ),
Label( 'db_w_g' , 211 , 9 , 'guiding' , 2 , False , True , (244, 35, 232) ),
Label( 'db_y_g' , 208 , 10 , 'guiding' , 2 , False , True , ( 0, 0, 160) ),
Label( 'db_w_s' , 216 , 11 , 'stopping' , 3 , False , True , (153, 153, 153) ),
Label( 's_w_s' , 217 , 12 , 'stopping' , 3 , False , False , (220, 220, 0) ),
Label( 'ds_w_s' , 215 , 13 , 'stopping' , 3 , False , True , (250, 170, 30) ),
Label( 's_w_c' , 218 , 14 , 'chevron' , 4 , False , True , (102, 102, 156) ),
Label( 's_y_c' , 219 , 15 , 'chevron' , 4 , False , True , (128, 0, 0) ),
Label( 's_w_p' , 210 , 16 , 'parking' , 5 , False , False , (128, 64, 128) ),
Label( 's_n_p' , 232 , 17 , 'parking' , 5 , False , True , (238, 232, 170) ),
Label( 'c_wy_z' , 214 , 18 , 'zebra' , 6 , False , False , (190, 153, 153) ),
Label( 'a_w_u' , 202 , 19 , 'thru/turn' , 7 , False , True , ( 0, 0, 230) ),
Label( 'a_w_t' , 220 , 20 , 'thru/turn' , 7 , False , False , (128, 128, 0) ),
Label( 'a_w_tl' , 221 , 21 , 'thru/turn' , 7 , False , False , (128, 78, 160) ),
Label( 'a_w_tr' , 222 , 22 , 'thru/turn' , 7 , False , False , (150, 100, 100) ),
Label( 'a_w_tlr' , 231 , 23 , 'thru/turn' , 7 , False , True , (255, 165, 0) ),
Label( 'a_w_l' , 224 , 24 , 'thru/turn' , 7 , False , False , (180, 165, 180) ),
Label( 'a_w_r' , 225 , 25 , 'thru/turn' , 7 , False , False , (107, 142, 35) ),
Label( 'a_w_lr' , 226 , 26 , 'thru/turn' , 7 , False , False , (201, 255, 229) ),
Label( 'a_n_lu' , 230 , 27 , 'thru/turn' , 7 , False , True , (0, 191, 255) ),
Label( 'a_w_tu' , 228 , 28 , 'thru/turn' , 7 , False , True , ( 51, 255, 51) ),
Label( 'a_w_m' , 229 , 29 , 'thru/turn' , 7 , False , True , (250, 128, 114) ),
Label( 'a_y_t' , 233 , 30 , 'thru/turn' , 7 , False , True , (127, 255, 0) ),
Label( 'b_n_sr' , 205 , 31 , 'reduction' , 8 , False , False , (255, 128, 0) ),
Label( 'd_wy_za' , 212 , 32 , 'attention' , 9 , False , True , ( 0, 255, 255) ),
Label( 'r_wy_np' , 227 , 33 , 'no parking' , 10 , False , False , (178, 132, 190) ),
Label( 'vom_wy_n' , 223 , 34 , 'others' , 11 , False , True , (128, 128, 64) ),
Label( 'om_n_n' , 250 , 35 , 'others' , 11 , False , False , (102, 0, 204) ),
Label( 'noise' , 249 , 255 , 'ignored' , 255 , False , True , ( 0, 153, 153) ),
Label( 'ignored' , 255 , 255 , 'ignored' , 255 , False , True , (255, 255, 255) ),
]

Firstly, thanks for your dataset, I have a question:
unlike the label list of cityscape, the label list of Apollo lane dataset is different. In my opinion, the trainId of 'void' should be 255(ignored), because it shouldn't be evaluated. Is that right?
@pengwangucla
Copy link
Contributor

pengwangucla commented Oct 30, 2018 •
edited

That is correct 255 is the ignorance id

@passion3394
Copy link
Author

@pengwangucla I understand it now, thanks.

@passion3394
Copy link
Author

@pengwangucla could you share the trainId of the lane marking? just like cityscape. Users can convert the label pixels to trainId with your label definition, but it's time-consuming.

@dingfuzhou
Copy link

dingfuzhou commented Oct 31, 2018 •
edited

@pengwangucla could you share the trainId of the lane marking? just like cityscape. Users can convert the label pixels to trainId with your label definition, but it's time-consuming.

Thanks for your question. Actually, the trainId is already included in our scripts. For detailed information, please refer to this file: /lane_segmentation/helpers/laneMarkDetection.py By the way, please take an attention, not all the classes will be evaluated.

@passion3394
Copy link
Author

@dingfuzhou I think my point is that it's better for Baidu to share the label image of trainIds,not the label color.

@passion3394
Copy link
Author

@dingfuzhou @pengwangucla I have another question, what's the baseline between the camera 5 and camera 6 of the Apollo scene dataset ? Could you give me the info, thanks very much!

@jianghe01
Copy link

@passion3394 i think you can get it from the pose.txt which is the extrinsic matrix of camera 5 and camera 6.

@passion3394
Copy link
Author

@jianghe01 thanks for your reply.
where can I get the pose.txt?

@jianghe01
Copy link

jianghe01 commented Nov 1, 2018 via email

@passion3394
Copy link
Author

@jianghe01 maybe. because I can't find the pose.txt in the apollo scene dataset. Could you please send me the pose.txt if you have at hand?

@jianghe01
Copy link

jianghe01 commented Nov 1, 2018 via email

@passion3394
Copy link
Author

@jianghe01 thank you very much. I got the answer.

@CaptainEven
Copy link

@passion3394 May i ask about the metric baseline value？

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Assignees
No one assigned
Labels
None yet
Projects
None yet
Milestone
No milestone
Development

No branches or pull requests
5 participants
@pengwangucla @dingfuzhou @CaptainEven @passion3394 @jianghe01