Feature Extraction
Keras
tensorflow
deep-learning
dimensionality-reduction
clustering
computer-vision
fire-detection
fire-severity
Instructions to use AbdullahImran/Fire-Feature-Analysis with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use AbdullahImran/Fire-Feature-Analysis with Keras:
# !pip install -U keras tensorflow huggingface_hub # Keras needs TensorFlow installed to read "hf://" paths, so the tensorflow backend is selected here; # "jax" and "torch" also work for computation once TensorFlow is installed. import os os.environ["KERAS_BACKEND"] = "tensorflow" import keras model = keras.saving.load_model("hf://AbdullahImran/Fire-Feature-Analysis") - Notebooks
- Google Colab
- Kaggle
Download fire_features_effnet_tri_classification_feature_extraction.npy from AbdullahImran/Fire-Feature-Analysis: direct link, hf CLI and curl.
- Browser
- Download file 59.8 MB
-
https://huggingface.co/AbdullahImran/Fire-Feature-Analysis/resolve/main/fire_features_effnet_tri_classification_feature_extraction.npy
- Command line
-
hf download hf://AbdullahImran/Fire-Feature-Analysis/fire_features_effnet_tri_classification_feature_extraction.npy
-
curl -L -o fire_features_effnet_tri_classification_feature_extraction.npy https://huggingface.co/AbdullahImran/Fire-Feature-Analysis/resolve/main/fire_features_effnet_tri_classification_feature_extraction.npy
59.8 MB
- Xet hash:
- 5e399fe0d3154be3c475cd7a345f46fc91ca4c74ab5a50af06bf6d200b1797fc
- Size of remote file:
- 59.8 MB
- SHA256:
- e2f579ee60ed99d6167e2fc7b47def69bceb5b0ccf10edbf524b92c051553117
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.