The repo for "Metric3D: Towards Zero-shot Metric 3D Prediction from A Single Image" and "Metric3Dv2: A Versatile Monocular Geometric Foundation Model..." - Metric3D/requirements_v2.txt at main · YvanYin/Metric3D
v1.0.1 6a915d0 更新: ONNX模型:去掉ONNX中的归一化操作和尾部无效节点。 config_u16.json 微调。Assets 3 models.tar.gz 212 MB 2025-02-11T13:59:00Z Source code (zip) 2025-02-08T09:17:35Z Source code (tar.gz) 2025-02-08T09:17:35Z ...
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colors = np.array(color_img).reshape(-1, 3) / 255.0 # Create the point cloud and save it to the output directory out_dir = "Applications/vis_point_cloud" os.makedirs(out_dir, exist_ok=True) pcd = o3d.geometry.PointCloud()
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53D10Contact metric manifoldcontact strongly pseudo-convex CR-manifoldnull SasakianD-homothetically fixedinfinitesimal $${\\varphi}$$ φ -transformationinfinitesimal harmonic transformationWe prove that if a vector field V on a contact metric manifold \\({M(\\varphi, \\xi, \\eta, g)}\\) of...
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meters. The advantage of predicting metric depth is the practical utility for many downstream applications in computer vision and robotics, such as mapping, planning, navigation, object recognition, 3D reconstruction, and image editing. However, training a single metric depth estimation model across ...