Method and apparatus for detecting lane line, and medium
According to the exemplary embodiments of the present disclosure, a method and apparatus for detecting a lane line, and a medium are provided. A method for generating a lane line detection model includes: detecting a lane line in an original image to generate a first image associated with the detected lane line; acquiring a second image generated based on the original image and associated with a marked lane line; generating at least one tag indicating whether the detected lane line is accurate, based on the first image and the second image; and training a classifier model for automatically identifying the lane line, based on the first image and the at least one tag. In such case, the lane line detection may be achieved in a simple and effective way.
1. A method for generating a lane line detection model, comprising:
detecting a lane line in an original image to generate a first image associated with a detected lane line;
acquiring a second image generated based on the original image and associated with marked lane line;
generating at least one tag indicating whether the detected lane line is accurate, based on the first image and the second image; and
training a classifier model for automatically identifying the lane line, based on the first image and the at least one tag.
2. The method according to claim 1 , wherein the generating a first image comprises:
performing an inverse perspective transformation on the original image; and
detecting the lane line in an inverse-perspective transformed original image, to generate the first image.
3. The method according to claim 1 , wherein the generating a first image comprises:
performing gray processing on the original image to generate a grayed original image;
binarizing the grayed original image, to generate a binary image; and
detecting the lane line in the binary image to generate the first image.
4. The method according to claim 1 , wherein the generating a first image comprises:
denoising the original image to generate a denoised image; and
detecting the lane line in the denoised image to generate the first image.
5. The method according to claim 1 , wherein the generating a first image comprises:
applying a contour detection on the original image to generate a contour of the lane line; and
generating the first image based on the contour.
6. The method according to claim 5 , wherein the generating the first image based on the contour comprises:
performing curve fitting on the contour to generate a curve representing the lane line; and
generating the first image by mapping the curve to the original image.
7. The method according to claim 1 , wherein the generating at least one tag comprises:
dividing the first image into a first set of image blocks, wherein each of the image blocks includes a portion of the detected lane line;
dividing the second image into a second set of image blocks, wherein each of the image blocks includes a portion of the marked lane line; and
generating a plurality of tags for a plurality of portions of the detected lane line by comparing corresponding image blocks in the first and second set of image blocks, wherein each of the tags indicates whether a corresponding portion of the detected lane line is accurate.
8. A method for detecting a lane line, comprising:
detecting a lane line in an original image to generate a first image associated with the detected lane line; and
inputting the first image into the classifier model according to one of claims 1 - 7 , to automatically identify the lane line.
9. An apparatus for generating a lane line detection model, comprising:
at least one processor; and
a memory storing instructions, the instructions when executed by the at least one processor, cause the at least one processor to perform operations, the operations comprising:
detecting a lane line in an original image to generate a first image associated with a detected lane line;
acquiring a second image generated based on the original image and associated with marked lane line;
generating at least one tag indicating whether the detected lane line is accurate, based on the first image and the second image; and
training a classifier model for automatically identifying the lane line, based on the first image and the at least one tag.
10. The apparatus according to claim 9 , wherein the generating a first image comprises:
performing an inverse perspective transformation on the original image; and
detecting the lane line in an inverse-perspective transformed original image, to generate the first image.
11. The apparatus according to claim 9 , wherein the generating a first image comprises:
performing gray processing on the original image to generate a grayed original image;
binarizing the grayed original image, to generate a binary image; and
detecting the lane line in the binary image to generate the first image.
12. The apparatus according to claim 1 , wherein the generating a first image comprises:
denoising the original image to generate a denoised image; and
detecting the lane line in the denoised image to generate the first image.
13. The apparatus according to claim 9 , wherein the generating a first image comprises:
applying a contour detection on the original image to generate a contour of the lane line; and
generating the first image based on the contour.
14. The apparatus according to claim 13 , wherein the generating the first image based on the contour comprises:
performing curve fitting on the contour to generate a curve representing the lane line; and
generating the first image by mapping the curve to the original image.
15. The apparatus according to claim 9 , wherein the generating at least one tag comprises:
dividing the first image into a first set of image blocks, wherein each of the image blocks includes a portion of the detected lane line;
dividing the second image into a second set of image blocks, wherein each of the image blocks includes a portion of the marked lane line; and
generating a plurality of tags for a plurality of portions of the detected lane line by comparing corresponding image blocks in the first and second set of image blocks, wherein each of the tags indicates whether a corresponding portion of the detected lane line is accurate.
16. An apparatus for detecting a lane line, comprising:
at least one processor; and
a memory storing instructions, the instructions when executed by the at least one processor, cause the at least one processor to perform the operations according to claim 8 .
17. A non-transitory computer readable storage medium storing a computer program, wherein the program, when executed by a processor, cause the processor to perform the operations according to claim 1 .
18. A non-transitory computer readable storage medium storing a computer program, wherein the program, when executed by a processor, cause the processor to perform the operations according to claim 8 .