Image Classification
Keras
English
agriscan
agriculture
plant-disease
crop-classification
efficientnet
efficientnetb0
tensorflow
plantvillage
Instructions to use Vernard/AgriScan_EfficientNetB0_Two_Classifier_Training with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use Vernard/AgriScan_EfficientNetB0_Two_Classifier_Training 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://Vernard/AgriScan_EfficientNetB0_Two_Classifier_Training") - Notebooks
- Google Colab
- Kaggle
File size: 983 Bytes
1a55b38 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 | {
"architecture": "EfficientNetB0",
"image_size": [
224,
224
],
"crop_classes": [
"Maize",
"Potato",
"Tomato"
],
"disease_classes": [
"Corn_(maize)___Cercospora_leaf_spot Gray_leaf_spot",
"Corn_(maize)___Common_rust_",
"Corn_(maize)___Northern_Leaf_Blight",
"Corn_(maize)___healthy",
"Potato___Early_blight",
"Potato___Late_blight",
"Potato___healthy",
"Tomato___Bacterial_spot",
"Tomato___Early_blight",
"Tomato___Late_blight",
"Tomato___Leaf_Mold",
"Tomato___Septoria_leaf_spot",
"Tomato___Spider_mites Two-spotted_spider_mite",
"Tomato___Target_Spot",
"Tomato___Tomato_Yellow_Leaf_Curl_Virus",
"Tomato___Tomato_mosaic_virus",
"Tomato___healthy"
],
"test_images": 4841,
"crop_accuracy": 0.9979343110927494,
"crop_macro_f1": 0.9954170890599903,
"disease_accuracy": 0.9750051642222681,
"disease_macro_f1": 0.9693152257967829,
"disease_weighted_f1": 0.9749148480133657
} |