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:
# !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://0xgr3y/Arch-Building-Image-Classification") - Notebooks
- Google Colab
- Kaggle
Download model_benchmark.json from 0xgr3y/Arch-Building-Image-Classification: direct link, hf CLI and curl.
- Browser
- Download file 823 Bytes
-
https://huggingface.co/0xgr3y/Arch-Building-Image-Classification/resolve/main/model_benchmark.json
- Command line
-
hf download hf://0xgr3y/Arch-Building-Image-Classification/model_benchmark.json
-
curl -L -o model_benchmark.json https://huggingface.co/0xgr3y/Arch-Building-Image-Classification/resolve/main/model_benchmark.json
823 Bytes
| { | |
| "model_file": "fine_tuning_swa.keras", | |
| "architecture": "EfficientNetV2-S+Conv2D(256)+BN+MaxPool2D+GeMPooling+Dense(256)+BN+Dropout(0.4)+Dense(8,softmax)", | |
| "total_params": 23350633, | |
| "trainable_params": 17810225, | |
| "non_trainable_params": 5540408, | |
| "input_shape": [ | |
| 320, | |
| 320, | |
| 3 | |
| ], | |
| "num_classes": 8, | |
| "model_size_mb": 226.75, | |
| "saved_model_size_mb": 183.29, | |
| "tflite_size_kb": 90483.55, | |
| "tfjs_size_mb": 89.54, | |
| "inference_ms_keras": 437.5, | |
| "inference_ms_tflite": 197.8, | |
| "metrics": { | |
| "train_accuracy": 0.9997, | |
| "val_accuracy": 0.9851, | |
| "test_accuracy": 0.9792, | |
| "test_loss": 0.3928, | |
| "tta_accuracy": 0.9814, | |
| "top1_accuracy": 0.9792, | |
| "top2_accuracy": 0.9918, | |
| "top3_accuracy": 0.9955, | |
| "macro_auc": 0.9975, | |
| "ece": 0.1813, | |
| "overfitting_gap": 0.0206 | |
| } | |
| } |