- Added `ben2_onnx.py` for BEN2 ONNX inference with preprocessing. - Introduced `da3_onnx.py` for Depth Anything 3 inference, including camera projection calculations. - Created `moge_onnx.py` for MoGe-2 ONNX inference and post-processing. - Implemented shared ONNX Runtime session helpers in `onnx_runtime.py`. - Added model synchronization script `sync_models.py` for downloading and verifying ONNX models. - Developed unit tests for BEN2, Depth Anything 3, and MoGe ONNX models to ensure functionality. - Updated `vendor.lock.toml` to remove unused artifacts.
30 lines
1.1 KiB
Markdown
30 lines
1.1 KiB
Markdown
# 输出格式
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## DA3 ONNX
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`Output Type` 提供以下结果:
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- Point Cloud (GLB):由 depth、confidence、相机参数和原图生成彩色点云
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- Depth Preview (Images):保存深度着色预览
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- Depth Data (NPZ):保存 depth、confidence、extrinsics、intrinsics 与处理后的图像
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- Textured Surface (GLB):SnapForm 根据 Prediction 构建纹理网格
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DA3 Small 与 Base 的 ONNX 图不包含 Gaussian head,因此不提供 Gaussian Splats。默认推理参数为:
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- `process_res=504`
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- `process_res_method="upper_bound_resize"`
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- `ref_view_strategy="saddle_balanced"`
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- `conf_thresh_percentile=40.0`
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- `num_max_points=1_000_000`
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- `show_cameras=True`
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相机外参与内参由模型的 camera decoder 输出恢复,不运行 ray-pose 求解器。
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## MoGe-2 ONNX
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MoGe-2 Debug 可保存原始 NPZ、depth/normal/mask maps、纹理 GLB 或彩色 PLY。Surface 输出由模型 points、mask 与 depth edge 在内部构建三角网格。
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## BEN2 ONNX
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BEN2 输出 `foreground.png`,RGB 保留原始输入,Alpha 来自 ONNX mask 并恢复到输入分辨率。
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