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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...

TipoOtherVersiónCheckpoint lastCcalidad

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 (no module. prefix)
  • checkpoint_last.pth — resume checkpoint (model + optimizer + scaler + history)

Load with the matching architecture from the training notebook.

Fuentes

1 fuente
Hugging FacePrincipalVersión 070e22099127ff9c3fae7e4b4f69056a7344e2b1
huggingface.co/arunapb/food-depth-senet154/tree/070e22099127ff9c3fae7e4b4f69056a7344e2b1

Verificado 10 oct

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Artefactos del modelo

2 artefactos

checkpoint_last.pth

pth · 1,76 GB · SHA-256 759be68c3e10…fed6 · Hugging Face

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model_senet.pth

pth · 601 MB · SHA-256 2bbbf6ac6a9a…c78c · Hugging Face

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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