Food Depth Senet154
Trained 8 epochs on every 3. frame, batch 8, AMP. Encoder: timm legacysenet154 (stem pool0 included in Esenet). modelsenet.pth — final clean statedict (no module. prefix) checkpointlast.pth — resume checkpoint (model...
Source du modèle
- Type
- Other
- Taille du fichier
- 601 MB–1,76 GB
- Version
- vCheckpoint last
- Mis à jour
- 10 oct. 2026
- Source
- Hugging Face
Description de la source
SENet-154 monocular depth (Hu et al. 2018 architecture) — NYU-Depth V2
Trained 8 epochs on every 3. frame, batch 8, AMP.
Encoder: timm legacy_senet154 (stem pool0 included in E_senet).
model_senet.pth— final clean state_dict (nomodule.prefix)checkpoint_last.pth— resume checkpoint (model + optimizer + scaler + history)
Load with the matching architecture from the training notebook.
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Sources
1 sourceVérifié 10 oct.
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2 extraits--- license: mit tags: [depth-estimation, nyu-depth-v2, senet154, pytorch] --- # SENet-154 monocular depth (Hu et al. 2018 architecture) — NYU-Depth V2 Trained 8 epochs on every 3. frame, batch 8, AMP. Encoder: timm `legacy_senet154` (stem pool0 included in E_senet). - `model_senet.pth` — final clean state_dict (no `module.` prefix) - `checkpoint_last.pth` — resume checkpoint (model + optimizer + scaler + history) Load with the matching architecture from the training notebook.
Source context: 0 downloads · 0 likes · Pipeline depth-estimation · Repo arunapb/food-depth-senet154
