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| import datasets | |
| import gradio as gr | |
| from transformers import AutoFeatureExtractor, AutoModelForImageClassification | |
| import torch | |
| dataset = datasets.load_dataset("beans") | |
| feature_extractor = AutoFeatureExtractor.from_pretrained("saved_model_files") | |
| model = AutoModelForImageClassification.from_pretrained("saved_model_files") | |
| labels = dataset['train'].features['labels'].names | |
| example_imgs = ["example_0.jpg", "example_1.jpg","example_2.jpg"] | |
| def classify(im): | |
| features = feature_extractor(im, return_tensors='pt') | |
| logits = model(features["pixel_values"])[-1] | |
| probability = torch.nn.functional.softmax(logits, dim=-1) | |
| probs = probability[0].detach().numpy() | |
| confidences = {label: float(probs[i]) for i, label in enumerate(labels)} | |
| return confidences | |
| interface = gr.Interface(fn = classify, | |
| inputs="image", | |
| outputs = "label", | |
| title = "Plant Leaf Disease Classifier", | |
| description = """Below is a simple app to detect Angular Leaf Spot and Bean Rust diseases on leaves. | |
| Data was annotated by experts from the National Crops Resources Research Institute (NaCRRI) | |
| in Uganda and collected by the Makerere AI research lab. | |
| The model being used is a fine-tuned Vision Transformer, specifically beginning with [google/vit-base-patch16-224] | |
| (https://huggingface.co/google/vit-base-patch16-224) and trained using the [beans](https://huggingface.co/datasets/beans) dataset. | |
| This app was created in Abubakar Abid's 'Building End-to-End Vision Applications' course through CoRise. | |
| """, | |
| examples = example_imgs) | |
| interface.launch(debug=True) | |