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
Download crop_classification_report.csv from Vernard/AgriScan_EfficientNetB0_Two_Classifier_Training: direct link, hf CLI and curl.
- Browser
- Download file 423 Bytes
-
https://huggingface.co/Vernard/AgriScan_EfficientNetB0_Two_Classifier_Training/resolve/main/crop_classification_report.csv
- Command line
-
hf download hf://Vernard/AgriScan_EfficientNetB0_Two_Classifier_Training/crop_classification_report.csv
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curl -L -o crop_classification_report.csv https://huggingface.co/Vernard/AgriScan_EfficientNetB0_Two_Classifier_Training/resolve/main/crop_classification_report.csv
423 Bytes
| ,precision,recall,f1-score,support | |
| Maize,1.0,1.0,1.0,794.0 | |
| Potato,0.9975,0.9779411764705882,0.9876237623762376,408.0 | |
| Tomato,0.9975322182615849,0.9997251992305578,0.9986275048037332,3639.0 | |
| accuracy,0.9979343110927494,0.9979343110927494,0.9979343110927494,0.9979343110927494 | |
| macro avg,0.9983440727538616,0.9925554585670486,0.9954170890599903,4841.0 | |
| weighted avg,0.997934257850425,0.9979343110927494,0.9979252189692812,4841.0 | |