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...
Fuente del modelo
- Tipo
- Other
- Tamaño del archivo
- 601 MB–1,76 GB
- Versión
- vCheckpoint last
- Actualizado
- 10 oct 2026
- Fuente
- Hugging Face
Descripción de la fuente
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.
Fuentes
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Fuentes
1 fuenteVerificado 10 oct
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Artefactos del modelo
2 artefactos
Artefactos del modelo
2 artefactosExtractos de fuentes
2 extractos
Extractos de fuentes
2 extractos--- 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
