Image Classification
Keras
LiteRT
TF-Keras
Safetensors
English
efficientnetv2-s
efficientnetv2
fgic
transfer-learning
gem-pooling
focal-loss
swa
grad-cam
calibration
temperature-scaling
computer-vision
tensorflow.js
Eval Results (legacy)
Instructions to use 0xgr3y/Arch-Building-Image-Classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use 0xgr3y/Arch-Building-Image-Classification with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://0xgr3y/Arch-Building-Image-Classification") - Notebooks
- Google Colab
- Kaggle
| { | |
| "ece": 0.1813, | |
| "n_bins": 15, | |
| "bin_boundaries": [ | |
| 0.0, | |
| 0.0667, | |
| 0.1333, | |
| 0.2, | |
| 0.2667, | |
| 0.3333, | |
| 0.4, | |
| 0.4667, | |
| 0.5333, | |
| 0.6, | |
| 0.6667, | |
| 0.7333, | |
| 0.8, | |
| 0.8667, | |
| 0.9333, | |
| 1.0 | |
| ], | |
| "bin_accuracies": [ | |
| 0.0, | |
| 0.0, | |
| 0.0, | |
| 0.0, | |
| 0.0, | |
| 0.0, | |
| 0.2857, | |
| 0.4, | |
| 0.75, | |
| 0.8824, | |
| 1.0, | |
| 0.9865, | |
| 0.9977, | |
| 0.9375, | |
| 1.0 | |
| ], | |
| "bin_confidences": [ | |
| 0.0333, | |
| 0.1, | |
| 0.1667, | |
| 0.2306, | |
| 0.3179, | |
| 0.3818, | |
| 0.4339, | |
| 0.502, | |
| 0.5496, | |
| 0.6375, | |
| 0.7084, | |
| 0.7819, | |
| 0.8255, | |
| 0.8889, | |
| 0.9381 | |
| ], | |
| "bin_counts": [ | |
| 0, | |
| 0, | |
| 0, | |
| 1, | |
| 2, | |
| 1, | |
| 7, | |
| 10, | |
| 8, | |
| 17, | |
| 26, | |
| 371, | |
| 868, | |
| 32, | |
| 1 | |
| ], | |
| "per_class_auc": { | |
| "barn": 0.9955, | |
| "bridge": 0.9977, | |
| "castle": 0.9998, | |
| "mosque": 0.999, | |
| "skyscraper": 0.9999, | |
| "stadium": 0.9954, | |
| "temple": 0.9944, | |
| "windmill": 0.9979 | |
| }, | |
| "temperature": 0.46449432701083704, | |
| "ece_before_t_scaling": 0.18125913327648527, | |
| "ece_after_t_scaling": 0.009534640510460726 | |
| } |