Instructions to use kolkela/simple-cnn-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use kolkela/simple-cnn-classifier with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://kolkela/simple-cnn-classifier") - Notebooks
- Google Colab
- Kaggle
File size: 454 Bytes
48b3e2b 27ac963 48b3e2b 27ac963 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 | ---
language: en
tags:
- keras
- computer-vision
- image-classification
- cnn
license: mit
---
# Simple CNN Classifier
## Model Architecture
- **Data Augmentation:** Random Flip, Rotation, Zoom, Contrast
- **Conv Blocks:** 32 -> 64 -> 128 filters + MaxPool
- **Regularization:** Dropout
- **Head:** GlobalAveragePooling2D -> Dense Layer
## How to Load & Use
```python
import keras
model = keras.saving.load_model("hf://kolkela/simple-cnn-classifier") |