[Documentation] Nvidia style edits to surgical scene reconstruction #1329
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Signed-off-by: meg miranda <mmiranda@nvidia.com>
Greptile SummaryThis PR applies NVIDIA style guide edits to the surgical scene reconstruction README, improving clarity and organization throughout. Major Improvements:
Issue Found:
Confidence Score: 4/5
Important Files Changed
Sequence DiagramsequenceDiagram
participant User
participant HoloHub CLI
participant Docker
participant Training Pipeline
participant Dataset
participant Model
participant Holoscan Pipeline
participant Visualization
User->>HoloHub CLI: ./holohub run surgical_scene_recon train
HoloHub CLI->>Docker: Build/Launch Container
Docker->>Dataset: Load EndoNeRF pulling_soft_tissues
Dataset-->>Training Pipeline: RGB + Depth + Masks + Poses
Training Pipeline->>Model: Stage 1 - Coarse (Static Gaussians)
Model-->>Training Pipeline: Base 3D Gaussians (~30k-50k points)
Training Pipeline->>Model: Stage 2 - Fine (Temporal Deformation)
Model-->>Training Pipeline: Deformation Network + Optimized Gaussians
Training Pipeline->>Model: Save Checkpoint
Model-->>Training Pipeline: fine_best_psnr.pt
User->>HoloHub CLI: ./holohub run surgical_scene_recon render
HoloHub CLI->>Holoscan Pipeline: Initialize Operators
Holoscan Pipeline->>Dataset: EndoNeRFLoaderOp - Load Poses/Timestamps
Holoscan Pipeline->>Model: GsplatLoaderOp - Load Checkpoint
loop Real-time Rendering (>30 FPS)
Dataset-->>Holoscan Pipeline: Camera Pose + Time
Model-->>Holoscan Pipeline: Deformed Gaussians
Holoscan Pipeline->>Holoscan Pipeline: GsplatRenderOp - Render Frame
Holoscan Pipeline->>Visualization: HolovizOp - Display
Holoscan Pipeline->>Holoscan Pipeline: ImageSaverOp - Save (Optional)
end
Visualization-->>User: Real-time 3D Tissue Reconstruction
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Note Other AI code review bot(s) detectedCodeRabbit has detected other AI code review bot(s) in this pull request and will avoid duplicating their findings in the review comments. This may lead to a less comprehensive review. WalkthroughRewrote and reorganized Changes
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Actionable comments posted: 1
🤖 Fix all issues with AI agents
In @applications/surgical_scene_recon/README.md:
- Line 23: The README contains a grammatical typo: change the phrase "uses
cases" to "use cases" on the affected sentence (line with "It is ideal for uses
cases, such as:") so it reads "It is ideal for use cases, such as:"; update that
exact wording in applications/surgical_scene_recon/README.md.
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🔇 Additional comments (3)
applications/surgical_scene_recon/README.md (3)
3-5: Clarify intent of the two opening paragraphs.Lines 3 and 5 now convey nearly identical information—both describe real-time 3D surgical reconstruction with Gaussian Splatting and temporal deformation. After restructuring to emphasize the end-to-end pipeline, one of these appears redundant.
Verify whether both paragraphs serve a distinct purpose (e.g., detailed vs. summary) or if one should be removed for clarity.
96-107: Dataset setup instructions are clear and complete.The restructured dataset setup (lines 96–107) with numbered steps, inline code blocks, and explicit path placeholders is an improvement. The symlink warning on Line 109 is important context that is appropriately positioned.
41-41: All external links and documentation references in the README are properly formatted and valid. The relative path to the HoloHub glossary (../../README.md#Glossary) is correct, and the glossary section exists in the root README. The file appropriately references and uses HoloHub glossary terms for project-specific locations as required.
…to the training section, the duplication bothered me Signed-off-by: meg miranda <mmiranda@nvidia.com>
Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com> Signed-off-by: megnvidia <mmiranda@nvidia.com>
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Greptile Overview
Greptile Summary
This PR applies NVIDIA style guide edits to the surgical scene reconstruction README, improving formatting, organization, and readability.
Key improvements:
- Enhanced document structure with clearer section headings and better organization
- Improved Quick Start instructions with numbered lists and better code block formatting
- Standardized terminology and punctuation throughout
- Added more descriptive section titles (e.g., "Pulling Soft Tissues Dataset" instead of "Data")
- Refined technical descriptions and explanations
Issues found:
- Line 23: Typo "uses cases" should be "use cases"
- Line 52: Inaccurate term "virtual surgical training" should be "model training"
- Line 143: Incorrect technical description of Temporal Deformation Network references MRI data interpolation instead of surgical tissue deformation
- Line 5: Redundant sentence that duplicates the introduction
- Line 135: Inconsistent capitalization of "Gaussian"
Confidence Score: 3/5
- This PR has some style improvements but contains a critical technical inaccuracy and several smaller issues that should be fixed
- Score reflects that while most changes are beneficial style edits, there is a significant technical error (incorrect TGN model description on line 143), a typo, and inaccurate terminology that could confuse users
- The README.md file needs attention, specifically line 143 which contains incorrect technical information about the Temporal Deformation Network
Important Files Changed
File Analysis
| Filename | Score | Overview |
|---|---|---|
| applications/surgical_scene_recon/README.md | 3/5 | Style guide edits to improve clarity and consistency; found typo, inaccurate terminology, and incorrect technical description |
Sequence Diagram
sequenceDiagram
participant Author as PR Author
participant File as README.md
participant Review as Documentation Review
participant User as End User
Author->>File: Apply NVIDIA style guide edits
Author->>File: Restructure sections and headings
Author->>File: Improve Quick Start formatting
Author->>File: Enhance dataset documentation
Author->>File: Standardize terminology
Note over File: Introduced typo: "uses cases"
Note over File: Added inaccurate term: "virtual surgical training"
Note over File: Added incorrect TGN description
Note over File: Redundant sentence on line 5
Review->>File: Identify style improvements
Review->>File: Detect typo on line 23
Review->>File: Find terminology issue on line 52
Review->>File: Catch technical error on line 143
Review->>File: Note inconsistencies
File->>User: Improved readability & organization
File->>User: Better Quick Start instructions
File->>User: Clearer dataset setup steps
Note over Review: Requires fixes before merge
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Greptile Overview
Greptile Summary
This PR applies NVIDIA style guide edits to the surgical scene reconstruction README, improving formatting, organization, and readability throughout the documentation.
Major changes:
- Restructured introduction section with clearer feature descriptions
- Enhanced Quick Start section with numbered lists and better command formatting
- Improved dataset documentation with detailed download and setup instructions
- Standardized section headings and terminology throughout
- Reformatted code blocks and citation sections for consistency
Issues found:
- Line 143 contains a critical technical inaccuracy: describes the Temporal Deformation Network as a "Temporal Generative Network (TGN)" for "missing MRI data," which is incorrect for this surgical endoscopy application
- Line 5 introduces redundant content that duplicates line 3
- Inconsistent code block indentation in Step 3 (line 54)
- Terminology errors: "3D Gaussian" should be "3D Gaussians" (line 135), "Gaussian functions" should be "Gaussians" (line 243)
Confidence Score: 3/5
- This PR requires revisions before merging due to technical inaccuracies in the documentation
- Score of 3 reflects that while most style improvements are beneficial, there is a critical technical error at line 143 that misrepresents the Temporal Deformation Network functionality, terminology errors that could confuse readers, and formatting inconsistencies that should be addressed before merging
- Pay close attention to line 143 (incorrect TGN description), line 135 (terminology), and line 243 (terminology)
Important Files Changed
File Analysis
| Filename | Score | Overview |
|---|---|---|
| applications/surgical_scene_recon/README.md | 3/5 | Style guide improvements with some formatting inconsistencies and one critical technical inaccuracy about the Temporal Deformation Network (line 143) |
Sequence Diagram
sequenceDiagram
participant User
participant PR as Pull Request Review
participant Doc as README.md
participant StyleGuide as NVIDIA Style Guide
User->>PR: Submit style edits PR
PR->>Doc: Apply formatting changes
Doc->>Doc: Restructure sections
Doc->>Doc: Improve Quick Start formatting
Doc->>Doc: Standardize terminology
Doc->>Doc: Enhance readability
PR->>StyleGuide: Validate against style guide
StyleGuide-->>PR: Check formatting consistency
StyleGuide-->>PR: Check technical accuracy
Note over Doc: Issues found:<br/>- Redundant line 5<br/>- Inconsistent indentation<br/>- Inaccurate TGN description<br/>- Terminology errors
PR->>User: Return review feedback
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Actionable comments posted: 1
🤖 Fix all issues with AI agents
In @applications/surgical_scene_recon/README.md:
- Around line 126-150: The opening sentence of the Temporal Deformation Network
(TGN) description incorrectly references MRI data; update the sentence that
currently reads "Temporal Generative Network (TGN) model generates data that
integrates bidirectional deformation estimation with temporal prediction to
interpolate missing MRI data and forecast future frames" to instead state that
the TGN interpolates missing endoscopic frames and forecasts future frames using
EndoNeRF endoscopic data (RGB images + stereo depth + camera poses), keeping the
rest of the TGN details (HexPlane 4D grid, MLP decoder,
input/output/training/inference) unchanged.
🧹 Nitpick comments (1)
applications/surgical_scene_recon/README.md (1)
156-157: Minor grammar refinement: "where" clause construction.Lines 156–157 use grammatically awkward constructions:
- "The Coarse Stage where the application learns..."
- "The Fine Stage where a temporal deformation network model is added..."
These read more naturally as "In the Coarse Stage, the application learns..." or "The Coarse Stage: the application learns..."
This is a minor stylistic improvement; the meaning is clear as written.
✏️ Proposed improvements
- 1. The Coarse Stage where the application learns the base static Gaussian models without deformation. - 2. The Fine Stage where a temporal deformation network model is added for dynamic tissue modeling. + 1. **Coarse Stage:** The application learns the base static Gaussian models without deformation. + 2. **Fine Stage:** A temporal deformation network model is added for dynamic tissue modeling.
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🔇 Additional comments (2)
applications/surgical_scene_recon/README.md (2)
12-28: Past comment resolved: Use cases typo fixed.Line 23 correctly shows "use cases" (was flagged as "uses cases" in previous review). Feature additions ("Tool Removal," "End-to-End Training") and restructured use cases are clear and well-organized.
131-139: Past comment resolved: "Degree 3" terminology clarified.Line 138 now explains "Degree 3 (16 coefficients per gaussian for view-dependent color)" which directly addresses the previous comment asking "what is 'degree 3'?" The explanation is clear and technical.
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My intuition is telling me that the later half of this README has some content that we might not really care to keep, but I can't make those choices without discussion and feedback from a subject matter expert. I did more formatting changes on this article than I had originally intended. These readme's span the gray are between user guide and readme content. I probably leaned more toward user guide formatting style with this. We may not want that. |
Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com> Signed-off-by: megnvidia <mmiranda@nvidia.com>
Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com> Signed-off-by: megnvidia <mmiranda@nvidia.com>
Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com> Signed-off-by: megnvidia <mmiranda@nvidia.com>
Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com> Signed-off-by: megnvidia <mmiranda@nvidia.com>
Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com> Signed-off-by: megnvidia <mmiranda@nvidia.com>
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Greptile Overview
Greptile Summary
This PR applies style guide edits to the surgical scene reconstruction README, improving formatting, organization, and readability. However, it introduces a critical factual error in the Temporal Deformation Network description.
Key Issues:
- Critical: Line 142 contains incorrect description stating the model "integrates bidirectional deformation estimation with temporal prediction to interpolate missing MRI data and forecast future frames" - this application uses surgical endoscopy video for tissue reconstruction, not MRI data
- Terminology inconsistency: Line 134 changed "3D Gaussians" (plural) to "3D Gaussian" (singular), but the architecture uses multiple Gaussian primitives (the original plural form was correct)
Positive Changes:
- Improved section organization and heading structure
- Better formatting with numbered lists and consistent indentation
- Clearer Quick Start instructions with step-by-step guidance
- Enhanced dataset setup documentation with verification steps
- More detailed training pipeline explanation
Confidence Score: 2/5
- This PR has a critical factual error that misrepresents the application's functionality and must be corrected before merging
- Score reflects one critical factual error (TGN description mentions MRI instead of surgical video) and one terminology inconsistency (Gaussians plural→singular). While the style improvements are beneficial, the factual inaccuracy about the model's purpose is misleading and needs correction
- applications/surgical_scene_recon/README.md requires attention - specifically line 142 (critical factual error) and line 134 (terminology correction)
Important Files Changed
File Analysis
| Filename | Score | Overview |
|---|---|---|
| applications/surgical_scene_recon/README.md | 2/5 | Style guide edits to README with one critical factual error about Temporal Deformation Network (mentions MRI instead of surgical video) and one terminology inconsistency (singular vs plural Gaussians) |
Sequence Diagram
sequenceDiagram
participant User
participant PR as Pull Request
participant README as README.md
participant Review as Code Review
User->>PR: Submit style guide edits
PR->>README: Apply formatting changes
Note over README: Reorganize sections<br/>Update headings<br/>Improve clarity
PR->>README: Update model descriptions
Note over README: ⚠️ Incorrect TGN description<br/>(MRI vs surgical video)
PR->>README: Standardize terminology
Note over README: ⚠️ Change "Gaussians" to "Gaussian"<br/>(plural to singular)
Review->>README: Identify factual error
Review->>README: Identify terminology issue
Review->>User: Request corrections
Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com> Signed-off-by: megnvidia <mmiranda@nvidia.com>
Signed-off-by: meg miranda <mmiranda@nvidia.com>
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Signed-off-by: meg miranda <mmiranda@nvidia.com>
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Actionable comments posted: 1
🤖 Fix all issues with AI agents
In `@applications/surgical_scene_recon/README.md`:
- Around line 42-43: The README contains broken anchor links using
'#pulling-soft-tissues-dataset'; update both occurrences in the listed items to
the correct anchor that matches the actual heading "Obtaining the Pulling Soft
Tissues Dataset" (use '#obtaining-the-pulling-soft-tissues-dataset' or the
repository's generated slug for that heading) so the links point to the real
section.
🧹 Nitpick comments (2)
applications/surgical_scene_recon/README.md (2)
129-147: Consider standardizing bullet point style for consistency.The model descriptions use mixed styles—some bullets are key-value pairs ("Architecture: X"), while others are sentence fragments ("Spherical Harmonics of degree 3"). While technically clear, standardizing to one style would improve readability.
📋 Example standardization
Option 1: All as key-value pairs
- Architecture: 3D Gaussians with learned position, scale, rotation, opacity, and color - Initialization: Multi-frame point cloud (~30,000-50,000 points from all frames) - Renderer: `gsplat` library (CUDA-accelerated differentiable rasterization) - Color Representation: Spherical Harmonics of degree 3 (16 coefficients per Gaussian) - Resolution: 640×512 pixels (RGB, three channels)Option 2: All as complete sentences
- Uses 3D Gaussians with learned position, scale, rotation, opacity, and color - Initializes from multi-frame point cloud (~30,000-50,000 points from all frames) - Renders using `gsplat` library (CUDA-accelerated differentiable rasterization) - Employs Spherical Harmonics of degree 3 (16 coefficients per Gaussian for view-dependent color) - Outputs at 640×512 pixel resolution (RGB, three channels)
163-171: Simplify the training pipeline list for better readability.The training pipeline steps (lines 165-171) have some awkward phrasing and inconsistent grammar. Consider rephrasing for clarity and consistency.
✍️ Proposed refinement
-The **training pipeline** (`gsplat_train.py`) runs in the following order: - -1. Data Loading using EndoNeRF parser loads RGB, depth, masks, and poses. -2. Initialization uses Multi-frame point cloud (~30k points). -3. Training happens in two stages: - - Coarse - - Fine -4. Optimization is done by the Adam (Adaptive Moment Estimation) optimizer with batch-size scaled learning rates. -5. Regularization, for depth loss, TV loss, and masking losses, is performed on the data. +The **training pipeline** (`gsplat_train.py`) runs in the following order: + +1. **Data Loading:** EndoNeRF parser loads RGB, depth, masks, and poses. +2. **Initialization:** Multi-frame point cloud (~30k points). +3. **Two-Stage Training:** + - Coarse stage (static Gaussians) + - Fine stage (with deformation) +4. **Optimization:** Adam optimizer with batch-size scaled learning rates. +5. **Regularization:** Depth loss, TV loss, and masking losses.
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🧠 Learnings (2)
📓 Common learnings
Learnt from: CR
Repo: nvidia-holoscan/holohub PR: 0
File: CONTRIBUTING.md:0-0
Timestamp: 2025-12-18T16:19:45.117Z
Learning: Applies to **/(@(operators|applications|workflows|gxf_extensions))/**/README.md : Every application and operator must include a comprehensive README.md file with purpose, usage, requirements, examples, and architecture information
📚 Learning: 2025-12-18T16:19:45.117Z
Learnt from: CR
Repo: nvidia-holoscan/holohub PR: 0
File: CONTRIBUTING.md:0-0
Timestamp: 2025-12-18T16:19:45.117Z
Learning: Applies to **/(@(operators|applications|workflows|gxf_extensions|tutorials))/**/README.md : README.md should use HoloHub glossary terms when referring to project-specific locations and concepts
Applied to files:
applications/surgical_scene_recon/README.md
🪛 markdownlint-cli2 (0.18.1)
applications/surgical_scene_recon/README.md
42-42: Link fragments should be valid
(MD051, link-fragments)
43-43: Link fragments should be valid
(MD051, link-fragments)
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🔇 Additional comments (3)
applications/surgical_scene_recon/README.md (3)
1-28: Strong technical introduction with comprehensive feature coverage.The rewritten introduction effectively emphasizes the key technologies (Holoscan SDK, 3D Gaussian Splatting, temporal deformation networks) and provides clear use cases. The feature list is well-structured and informative.
67-123: Excellent dataset documentation with clear setup instructions.The expanded dataset section provides comprehensive details including contents, download locations, setup steps, and structure verification. The warning about physical paths vs. symlinks (line 108) is crucial for Docker users and appropriately emphasized.
189-313: Well-structured technical documentation in the remaining sections.The pipeline architecture diagram, requirements, testing instructions, performance metrics, troubleshooting guide, and citations are all clearly presented and technically accurate. The troubleshooting section is particularly helpful with specific causes and solutions for common issues.
✏️ Tip: You can disable this entire section by setting review_details to false in your review settings.
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Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com> Signed-off-by: Bruce Hashemian <3968947+bhashemian@users.noreply.github.com>
Signed-off-by: meg miranda <mmiranda@nvidia.com>
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style guide edits to the surgical scene reconstruction readme.
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