Instructions to use chabdullah0566/Omnivision_Classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use chabdullah0566/Omnivision_Classifier 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://chabdullah0566/Omnivision_Classifier") - Notebooks
- Google Colab
- Kaggle
Omnivision_Classifier
Model Description
An advanced Computer Vision model trained to classify 30 highly overlapping classes from the CIFAR-100 dataset using ConvNeXtTiny.
Files in this Repository
best_model.keras: The trained Keras model weights.class_names.json: List of the 30 selected classes.model_comparison.csv: A CSV file comparing the performance metrics of different models.
Trained Classes (30)
Fruits & Vegetables, Large Carnivores, Large Omnivores, Small Mammals, Vehicles, People.
- Downloads last month
- 7