Upload from Ropedia Academy

README.md

@@ -1,13 +1,54 @@
 ---
 license: mit
+library_name: pytorch
 tags:
 - ropedia-academy
 - educational
+- implicit-neural-representation
 ---
 
-# B_deepsdf_shape
+# Neural SDF (DeepSDF-style)
 
-Trained from scratch in **Ropedia Academy** (https://chaoyue0307.github.io/ropedia-academy/) — an educational lab. The checkpoint and full loss/eval history (`metrics.json`) are included.
+An MLP signed-distance field with an eikonal regularizer; the surface is its zero level set (marching cubes).
 
+Trained from scratch in **[Ropedia Academy](https://chaoyue0307.github.io/ropedia-academy/)** — an interactive, bilingual course on embodied & spatial AI. **Educational model:** small and quick to train; the value is the *method* and a reproducible pipeline, not a leaderboard score.
 
-![results](figure.png)
+| | |
+|---|---|
+| **Task** | implicit 3D shape |
+| **Data** | analytic torus samples |
+| **Track** | B · 3D & rendering |
+| **Notebook** | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/ChaoYue0307/ropedia-academy/blob/main/notebooks/training/B_deepsdf_shape.ipynb) |
+
+## Results
+
+| metric | value |
+|---|---|
+| l1 (final) | 0.016 |
+
+
+![figure](figure.png)
+
+## How to use
+
+```python
+import torch
+state = torch.load("model.pt", map_location="cpu")   # some labs save pose.pt / gaussians.pt / transform.pt
+# Rebuild the model class from the Ropedia Academy notebook (linked above), then:
+# model.load_state_dict(state)
+```
+
+## Files
+
+- `figure.png`
+- `metrics.json`
+- `sdf.pt`
+
+
+## Reproduce / train your own
+
+Open the [lab notebook in Colab](https://colab.research.google.com/github/ChaoYue0307/ropedia-academy/blob/main/notebooks/training/B_deepsdf_shape.ipynb) → **Runtime → GPU → Run all**, then its *Publish to the Hugging Face Hub* cell. Browse every lab in the [Ropedia Academy Labs tab](https://chaoyue0307.github.io/ropedia-academy/labs).
+
+
+---
+*Part of the [Ropedia Academy](https://chaoyue0307.github.io/ropedia-academy/) trained-model collection.*

metrics.json

@@ -2,47 +2,47 @@
   "l1": [
     [
       0,
-      0.09738403558731079
+      0.0619
     ],
     [
       150,
-      0.004130750894546509
+      0.0245
     ],
     [
       300,
-      0.003667763201519847
+      0.0196
     ],
     [
       450,
-      0.00297424360178411
+      0.018
     ],
     [
       600,
-      0.00217777700163424
+      0.0191
     ],
     [
       750,
-      0.002252743812277913
+      0.0182
     ],
     [
       900,
-      0.0018030456267297268
+      0.0176
     ],
     [
       1050,
-      0.0018078343709930778
+      0.0168
     ],
     [
       1200,
-      0.0016836210852488875
+      0.0167
     ],
     [
       1350,
-      0.0016222801059484482
+      0.0157
     ],
     [
       1500,
-      0.0017965107690542936
+      0.016
     ]
   ]
 }

sdf.pt

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+oid sha256:5cd6f754d0b3e7805aff5e59b7e56c351b6d50f440ad6b08bee5a4b042728ced
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