Image Classification
Keras
conservation
object-detection
tiger
camera-traps
wildlife
species-classification
megadetector
Instructions to use alexvmt/TeraiNet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use alexvmt/TeraiNet with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://alexvmt/TeraiNet") - Notebooks
- Google Colab
- Kaggle
| class_names: | |
| - tiger | |
| - leopard | |
| - black_bear | |
| - other_carnivores | |
| - deer | |
| - wild_boar | |
| - buffalo | |
| - rhino | |
| - elephant | |
| - bird | |
| class_directories: | |
| - class_1 | |
| - class_2 | |
| - class_3 | |
| - class_4 | |
| - class_5 | |
| - class_6 | |
| - class_7 | |
| - class_8 | |
| - class_9 | |
| - class_10 | |
| image_size: 224 | |
| seed: 42 | |
| backbone: EfficientNetV2M | |
| preprocessing: | |
| resize: | |
| - 224 | |
| - 224 | |
| channels: rgb | |