
wireframe-to-3d
Convert 2D orthographic wireframe PNG drawings to 3D Blender models exported as glTF/GLB. Use this skill whenever the user provides wireframe images (technical drawings, line drawings, orthographic views, side/front/back panels) and wants to generate a 3D model, mesh, or .glb file. Triggers on phrases like "convert this wireframe to 3D", "make a 3D model from these drawings", "build a model from this wireframe", "generate GLB from these views", or any image-to-3D-mesh request involving line drawings. Make sure to use this skill even if the user does not explicitly say "wireframe" — also covers "orthographic views", "technical drawings", "line drawings of objects", "front and side views". Requires a configured Blender MCP backend (official or ahujasid) and Python with opencv-python, numpy, scipy installed.
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Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/roble3/cc-blender-skill --skill wireframe-to-3d- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads wireframe-to-3d automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
MCP backend
Use when: User provides one or more PNG wireframe images and wants a 3D model. Also use when user asks to model an object from front/side/back drawings, or to convert technical line art to glTF/GLB.
Before the first Blender call, read ../text-to-blender/references/mcp-backends.md. Prefer official MCP for shared capabilities; preserve the selected backend for the whole task. Tool names in recipes are client/legacy examples: map them through that reference and its agent-host guide.
Wireframe-to-3D Conversion
Convert 2D orthographic wireframe images to parametric 3D Blender models, exported as glTF 2.0 binary (.glb).
Overview
The skill drives a four-stage pipeline:
- Analyze wireframe images locally with
scripts/wireframe_analyzer.py(OpenCV → Bezier control points in JSON). - Generate Blender Python code that recreates the contours as parametric Bezier curves.
- Execute code through the selected Blender MCP backend, converting curves to meshes with PBR materials.
- Export as optimized GLB (≤ 15 MB), validating size and topology.
You (the agent) are the orchestrator. The scripts/ directory contains the only standalone code (wireframe_analyzer.py); everything else is patterns you emit and run via MCP.
Prerequisites — check first
Before any wireframe work, verify the environment:
-
Blender MCP is reachable. Call the selected backend's read-only scene-inspection tool. If it cannot connect, stop and tell the user:
"The selected Blender MCP backend is not reachable. Start Blender, enable its add-on, verify the configured host/port, then re-run."
-
Python deps for the analyzer. Run:
python3 -c "import cv2, numpy, scipy" 2>&1If it errors, run
pip install opencv-python numpy scipy Pillow(or instruct the user to). -
Image input. Confirm the user provided at least one PNG. Reasonable bounds: ≥ 400×400 px, black-on-white or white-on-black line art.
Decision flow
Q1: How many views?
- Single view → flat 2D extrusion only (warn the user; depth must be supplied or assumed).
- Front + side → full 3D reconstruction (silhouette × depth profile).
- Front + side + back → use back view for symmetry validation.
Q2: Detail level?
preview— RDP epsilon = 4.0, target ~1–2k tris, < 1 MB GLB.production— RDP epsilon = 2.0, target ~5–8k tris, 2–4 MB GLB. Default.high— RDP epsilon = 1.0, target ~10–20k tris, may need Decimate to stay under 15 MB.
Q3: Geometry type?
wires— frames, arms, hinges. Usebevel_depthon curves.surfaces— lenses, domes. Use lofted profiles or fill caps.hybrid— both. Default for glasses-like objects.
Q4: Real-world scale?
- If the user gave dimensions (e.g., "glasses are 140 mm wide"), use them.
- Otherwise infer from wireframe aspect ratio and assume a sensible default (140 mm width for glasses, 180 mm for helmets, etc.). Confirm with user if not obvious.
Mandatory correction loop for reference/texture-driven subjects
When user feedback says the model does not match the reference/texture, stop the normal "generate from primitives" loop and switch to reference-locked modeling:
- Count visible design parts first from the provided texture/wireframe and write the count into stdout/notes before modeling. Do not infer a radial or repeated count from symmetry; the visual design count in the source manifest is the contract.
- Use the front view as canonical. Create an image-empty/plane/reference overlay in the same front orthographic camera used for validation. Align scale, centerline, and bounding circle before adding depth.
- Trace or define 2D silhouettes in front-view X/Z first. Build mesh surfaces from those silhouettes; do not place generic ellipses and then try to texture them.
- Lock the front projection. Add depth only on the view axis after the front silhouette matches. Side/back views refine thickness and stacking but must not alter the front outline.
- Use Project-from-View-style UVs for any texture that is meant to match the front drawing. One front-facing surface should map to the corresponding texture crop 1:1.
- Render an overlay validation: reference/wireframe behind or over the model, plus a printed checklist: expected count, actual object count, face position, outer silhouette bounds, and side/back depth.
- If an iteration repeats the same error twice, consult
references/best-practices.mdand add a short durable note before another attempt.
For repeated motif subjects, create exactly the primary structural components declared by the source manifest. Name them by source-visible position or semantic role, and validate the count before export.
Stage 1 — Run the analyzer
Run the bundled analyzer once per view:
python3 ${CLAUDE_SKILL_DIR}/scripts/wireframe_analyzer.py <input.png> <output.json>
The script outputs JSON with this shape:
{
"metadata": {"image_size": [W, H], "num_contours": N, "parameters": {...}},
"contours": [[[x, y], ...], ...],
"bezier_curves": [[[[P0], [P1], [P2], [P3]], ...], ...]
}
Tuning RDP epsilon (only if defaults fail):
- Output has too few/jagged contours → lower epsilon to 1.0–1.5.
- Output has too many noisy points → raise epsilon to 3.0–4.0.
- Pass via
--rdp-epsilon(or edit the call in the script).
Read the JSON with the host's file-reading tool. Do not pass huge JSON blobs to Blender — extract what you need first.
Stage 2 — Generate Blender code
Build code in small, self-contained chunks (each execute_blender_code call gets a fresh Python namespace; only bpy.data persists between calls). Always re-import what you need.
Pattern: create a Bezier curve from control points
import bpy
# Identify by stable name; bpy.data persists between calls.
name = 'GEO-lens-right'
curve_data = bpy.data.curves.new(name=name, type='CURVE')
curve_data.dimensions = '3D'
curve_data.resolution_u = 16 # tessellation resolution
curve_data.bevel_depth = 0.001 # 1 mm wire thickness (adjust for surfaces)
curve_data.use_fill_caps = True
obj = bpy.data.objects.new(name, curve_data)
bpy.context.collection.objects.link(obj)
# Control points come from the analyzer JSON (px → mm scaling done client-side).
control_points = [(0.0, 0.0, 0.0), (0.5, 1.0, 0.0), (1.5, 1.0, 0.0), (2.0, 0.0, 0.0)]
spline = curve_data.splines.new(type='BEZIER')
spline.bezier_points.add(len(control_points) - 1)
for i, (x, y, z) in enumerate(control_points):
pt = spline.bezier_points[i]
pt.co = (x, y, z)
pt.handle_left_type = 'ALIGNED' # C¹ smooth
pt.handle_right_type = 'ALIGNED'
print(f"created:{name}") # signal back via stdout
Pixel → world conversion (do this in the code you generate, before sending to Blender):
norm_x = px_x / img_width
norm_y = 1.0 - (px_y / img_height) # flip Y; image origin is top-left
x_world = (norm_x - 0.5) * world_width_mm / 1000.0 # to metres
y_world = (norm_y - 0.5) * world_height_mm / 1000.0
Pattern: convert curves to mesh + cleanup
import bpy
name = 'GEO-lens-right'
obj = bpy.data.objects[name]
bpy.context.view_layer.objects.active = obj
bpy.ops.object.convert(target='MESH')
bpy.ops.object.mode_set(mode='EDIT')
bpy.ops.mesh.remove_doubles(threshold=0.0001)
bpy.ops.mesh.normals_make_consistent(inside=False)
bpy.ops.object.mode_set(mode='OBJECT')
bpy.ops.object.shade_smooth()
mesh = obj.data
print(f"mesh:{name} verts:{len(mesh.vertices)} polys:{len(mesh.polygons)}")
Pattern: PBR material (Principled BSDF — the only shader glTF exports cleanly)
import bpy
mat = bpy.data.materials.get('MAT-frame-metal') or bpy.data.materials.new('MAT-frame-metal')
mat.use_nodes = True
bsdf = mat.node_tree.nodes['Principled BSDF']
bsdf.inputs['Base Color'].default_value = (0.08, 0.08, 0.10, 1.0)
bsdf.inputs['Metallic'].default_value = 1.0
bsdf.inputs['Roughness'].default_value = 0.25
obj = bpy.data.objects['GEO-frame']
if obj.data.materials:
obj.data.materials[0] = mat
else:
obj.data.materials.append(mat)
print('material:assigned')
Material presets (use these unless the user specifies):
MAT-frame-metal—(0.08, 0.08, 0.10)base, metallic=1.0, roughness=0.25 (brushed steel)MAT-lens-mirror—(0.05, 0.08, 0.15)base, metallic=0.8, roughness=0.05, IOR=1.5 (mirror glass)MAT-pad-silicone—(0.65, 0.63, 0.60)base, metallic=0.0, roughness=0.7 (matte silicone)
Pattern: export to GLB
import bpy, os
filepath = '/tmp/wireframe_output.glb'
bpy.ops.export_scene.gltf(
filepath=filepath,
export_format='GLB',
export_materials='EXPORT',
export_uv=True,
export_normals=True,
export_animations=False,
export_yup=True,
)
size_mb = os.path.getsize(filepath) / (1024 * 1024)
print(f"export:{filepath} size_mb:{size_mb:.2f}")
If size_mb > 15: apply Decimate and re-export (see error recovery).
Stage 3 — Validate
After the full pipeline, validate before declaring success:
mcp__blender__get_scene_info— confirm expected objects exist.- For paired parts (left/right lens), call
mcp__blender__get_object_infoon each and compare bounding box widths. Tolerance: 1 mm. - Triangle count: get via
get_object_info. If a part exceeds budget, plan Decimate. - File size: must be ≤ 15 MB hard cap, ideally ≤ 8 MB.
Error recovery
| Symptom | Likely cause | Fix |
|---|---|---|
Code execution error: ... from MCP | Bad Python in generated code | Re-emit code in smaller chunks; trace the line from the error message |
Could not connect to Blender | Addon not running | Tell the user to start Blender + addon |
Timeout waiting for Blender response | Code chunk too large or slow | Break into smaller execute_blender_code calls |
| Variables undefined across calls | Each call gets a fresh namespace | Re-import modules; refer to objects by bpy.data.objects['name'] |
| Analyzer outputs 0 contours | Image too low contrast | Re-run with --gaussian-kernel 7 --canny-t1 30 |
| Asymmetric lenses | Original drawing asymmetric, or contour detection inconsistent | Warn the user; do not auto-mirror unless asked |
| GLB too large | High poly count or embedded textures | Apply DECIMATE modifier with ratio 0.6–0.8; re-export |
| Mesh has holes | Curve resolution too low | Raise curve_data.resolution_u to 24 or 32; reconvert |
| Material missing in GLB | Used non-Principled-BSDF nodes | Rebuild material using only Principled BSDF |
Decimate code pattern (when GLB > 15 MB)
import bpy
obj = bpy.data.objects['GEO-frame']
bpy.context.view_layer.objects.active = obj
mod = obj.modifiers.new(name='Decimate', type='DECIMATE')
mod.ratio = 0.7
mod.use_collapse_degenerate = True
bpy.ops.object.modifier_apply(modifier=mod.name)
print(f"decimated:{obj.name} verts:{len(obj.data.vertices)}")
Output to user
When done, report:
- Output path of the GLB file
- File size in MB (vs 15 MB cap)
- Triangle count per part (vs 30 000 cap)
- Material slots assigned
- Any warnings (asymmetry, decimation applied, fallbacks used)
Example:
✓ Exported
/tmp/wireframe_output.glb(2.4 MB)
Triangles: 5 200 (3 parts: GEO-frame, GEO-lens-right, GEO-lens-left)
Materials: MAT-frame-metal, MAT-lens-mirror
Warnings: none
When to load deeper references
The body above covers the 80% case. For the long tail, load these on demand:
references/algorithms.md— image-processing pipeline theory (Canny, RDP, least-squares Bezier fitting), 2D-to-3D reconstruction principles, ISO 128 orthographic standards. Load when the analyzer output looks wrong and you need to tune parameters.references/blender-patterns.md— exhaustive Blender Python patterns (lofting, surface revolution, custom modifier stacks). Load when the user requests non-standard geometry (curved surfaces, complex bridges, articulated parts).references/best-practices.md— performance optimization (foreach_set, batch ops, context caching), naming conventions (Blender Studio standards), modifier stack ordering. Load when builds are slow or output topology is poor.
Constraints
- Blender ≥ 4.0 (5.x preferred). The Principled BSDF node and glTF exporter are stable across these versions.
- glTF embedded only (no
.bin+ textures sidecar; no KTX2/Draco compression — Three.js needs extra loaders we haven't vendored). - PNG textures only (max 1024×1024). Prefer flat PBR colours; textures only when essential.
- No bone animations in the GLB. Idle motion is driven in JS by the consumer site.
Tip
If the user just says "convert this wireframe", default to: view_type=auto-detect, detail_level=production, geometry_type=hybrid, world_width_mm=auto. Only ask for clarification if multiple interpretations are plausible.
Scope boundary — what wireframe-to-3d does and doesn't produce
This skill produces 2D outline tracing extruded to thin curves — a flat-in-Y wireframe representation of the input drawing. It does not produce:
- Filled surfaces (e.g. lens glass between rim outlines)
- True 3D depth from a single view (output is flat in Y)
- Multi-view 3D reconstruction (front + side views combined volumetrically)
- Sub-features not in the input lines (nose pads, articulated hinges, etc.)
- Production-quality materials (placeholder only — real materials come from
blender-materials)
For a "complete rendered and textured X" (e.g. Ray-Ban Aviator from a wireframe), chain this skill with others:
| Step | Skill | What it adds |
|---|---|---|
| 1 | wireframe-to-3d | Frame outline as 3D curves — the foundation, not the deliverable |
| 2 | blender-modeling | Filled lens discs (UV spheres scaled to lens dimensions); temple arms (Bezier curves extending backward in Y); any 3D detail not in the wireframe |
| 3 | blender-materials | Gold/silver metal frame; mirror lens material with Metallic=0.9, Roughness=0.04; etc. |
| 4 | blender-lighting | subject_class='metal' for product-shot lighting |
| 5 | blender-cameras | 85-100mm focal length, shallow DoF for hero product shot |
| 6 | blender-rendering | Cycles 256+ samples, denoise, AgX view transform |
See text-to-blender/assets/v0.9.0-validation/03_aviator_wireframe_to_3d.webp for what wireframe-to-3d produces alone (flat outline tracing) vs 04_aviator_chained_upgrade.webp for what the chained orchestration produces (a Ray-Ban-style hero render).
The orchestrator (text-to-blender) should always plan for the chain when the user asks for a "model of X" from a wireframe.
FAQ
What does the wireframe-to-3d skill do?
Convert 2D orthographic wireframe PNG drawings to 3D Blender models exported as glTF/GLB. Use this skill whenever the user provides wireframe images (technical drawings, line drawings, orthographic views, side/front/back panels) and wants to generate a 3D model, mesh, or .glb file. Triggers on phrases like "convert this wireframe to 3D", "make a 3D model from these drawings", "build a model from this wireframe", "generate GLB from these views", or any image-to-3D-mesh request involving line drawings. Make sure to use this skill even if the user does not explicitly say "wireframe" — also covers "orthographic views", "technical drawings", "line drawings of objects", "front and side views". Requires a configured Blender MCP backend (official or ahujasid) and Python with opencv-python, numpy, scipy installed.
How do I install wireframe-to-3d?
Run npx skills add https://github.com/roble3/cc-blender-skill --skill wireframe-to-3d in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/wireframe-to-3d/ (personal) or .claude/skills/wireframe-to-3d/ (project).
Which AI agents can use wireframe-to-3d?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is wireframe-to-3d safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains wireframe-to-3d?
It is published by roble3 in roble3/cc-blender-skill. It has 810 recorded installs.
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