Instructions to use lakshitha1629/Canine-Skin-Image-Classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use lakshitha1629/Canine-Skin-Image-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://lakshitha1629/Canine-Skin-Image-Classifier") - Notebooks
- Google Colab
- Kaggle
Canine Skin Image Classifier
This repository mirrors the Keras checkpoint and labels from the Pet Disease Detection GitHub project. The project's notebook uses it to classify dog images as CanineImpetigo or CanineLupus.
Files
keras_model.h5: original Keras model fromKeras AI Part/keras_model.h5(2.45 MB)labels.txt: class index 0 = CanineImpetigo; class index 1 = CanineLupus
Input and output
The source notebook resizes an RGB image to 224 ร 224, converts it to a float32 array, and normalizes pixel values with (pixel / 127.0) - 1. It feeds an array of shape (1, 224, 224, 3) into the model and interprets output index 1 above 0.5 as CanineLupus. This description follows the source code; independent inference testing has not been performed here.
Limitations
The source repository does not document the training images' provenance, dataset size, evaluation metrics, or performance on independent images. This is a project demonstration and must not be used to diagnose an animal or choose treatment. Consult a veterinarian for health decisions. Keras/HDF5 model loading may depend on the library versions used when the file was saved.
Original files: checkpoint ยท labels.
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