单目深度估计算法介绍

任务

输入一张单目RGB图像，单目深度估计算法将分析场景三维结构、输出图像对应的稠密深度图

模型描述

本模型基于NeW CRFs: Neural Window Fully-connected CRFs for Monocular Depth Estimation算法，是该算法的官方模型。

技术细节请见：

NeW CRFs: Neural Window Fully-connected CRFs for Monocular Depth Estimation

Weihao Yuan, Xiaodong Gu, Zuozhuo Dai, Siyu Zhu, Ping Tan

CVPR 2022

[Project Page] |
[Paper] |
[中文解读]

如何使用

代码示例

import cv2
from modelscope.outputs import OutputKeys
from modelscope.pipelines import pipeline
from modelscope.utils.constant import Tasks
from modelscope.utils.cv.image_utils import depth_to_color


task = 'image-depth-estimation'
model_id = 'damo/cv_newcrfs_image-depth-estimation_indoor'

input_location = 'data/test/images/image_depth_estimation.jpg'
estimator = pipeline(Tasks.image_depth_estimation, model=model_id)
result = estimator(input_location)
depth_vis = result[OutputKeys.DEPTHS_COLOR]
cv2.imwrite('result.jpg', depth_vis)

适用范围

默认输入图片的摄像机参数应与训练数据集（NYUv2）保持一直, 即分辨率为640x480，内参为

518.8579,      0.0,   320
     0.0, 518.8579,   240
     0.0,      0.0,   0.0

如输入图像不一致，请将输入图片矫正为上述参数，否则会影响结果准确性

模型精度

在NYUv2上的结果为

Demo Video

Bibtex

@inproceedings{yuan2022newcrfs,
  title={NeWCRFs: Neural Window Fully-connected CRFs for Monocular Depth Estimation},
  author={Yuan, Weihao and Gu, Xiaodong and Dai, Zuozhuo and Zhu, Siyu and Tan, Ping},
  booktitle={Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition},
  pages={},
  year={2022}
}