CCAiM
CCAiM aims to develop an AI-powered model for classifying clouds based on ground-level photographs. The project uses image recognition techniques to identify cloud types according to the WMO International Cloud Atlas...
Fonte do modelo
- Tipo
- Other
- Tamanho do arquivo
- 37,8–42,7 MB
- Modelo base
- microsoft/resnet-18
- Versão
- vRevision 1923c87
- Atualizado
- 10 de out. de 2026
- Downloads
- 8
- Fonte
- Hugging Face
Descrição da fonte
CCAiM
overwiev
CCAiM aims to develop an AI-powered model for classifying clouds based on ground-level photographs. The project uses image recognition techniques to identify cloud types according to the WMO International Cloud Atlas classification.
GitHub
The project code for training, inference, and model evaluation is available on GitHub.
Used Datasets
- My dataset on Hugging Face
Models
| Model | Accuracy | Macro-F1 |
|---|---|---|
| V0.0.5 scratch | 27.52% | 0.123 |
| R18 V0.0.5 | 42.95% | 0.314 |
| V0.0.6 scratch | 35.57% | 0.237 |
| R18 V0.0.6 | 50.34% | 0.390 |
Old models
This models was trained when i was not understanding in neurol networks many so this model very bad.
- v_0.0.1 # first model learned by 23 photo.
- v_0.0.2 # second model learned by 42 photo.
- v_0.0.3 # model learned by 88 photo.
- V_0.0.4 # model learned by 165 photo.
Fontes
1 fonte
Fontes
1 fonteVerificado 10 de out.
Artefatos de modelo
2 artefatos
Artefatos de modelo
2 artefatosTrechos de fonte
3 trechos
Trechos de fonte
3 trechos--- license: mit pipeline_tag: image-classification tags: - 39.7M - 40M - pytorch - image-classification - climate datasets: - serbekun/CCAiM-CloudsDataset base_model: - microsoft/resnet-18 --- ## CCAiM # overwiev CCAiM aims to develop an AI-powered model for classifying clouds based on ground-level photographs. The project uses image recognition techniques to identify cloud types according to the WMO International Cloud Atlas classification. # GitHub The project code for training, inference, and model evaluation is available on [**GitHub**](https://github.com/serbekun/CCAiM). # Used Datasets - My dataset on [**Hugging Face**](https://huggingface.co/datasets/serbekun/CCAiM-CloudsDataset) # Models |Model |Accuracy |Macro-F1 | |--------------|----------|---------| |V0.0.5 scratch|27.52% |0.123 | |R18 V0.0.5 |42.95% |0.314 | |V0.0.6 scratch|35.57% |0.237 | |**R18 V0.0.6**|**50.34%**|**0.390**| ## Old models This models was trained when i was not understanding in neurol networks many so this model very bad. - v_0.0.1 # first model learned by 23 photo. - v_0.0.2 # second model learned by 42 photo. - v_0.0.3 # model learned by 88 photo. - V_0.0.4 # model learned by 165 photo.
Source context: 8 downloads · 0 likes · Pipeline image-classification · Repo serbekun/CCAiM
Source context: 14366 downloads · 0 likes · Pipeline image-classification · Repo serbekun/CCAiM
