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| import gradio as gr | |
| from fastai.vision.all import * | |
| import skimage | |
| learn = load_learner('modefinalnew.pkl') | |
| labels = learn.dls.vocab | |
| def predict(img): | |
| img = PILImage.create(img) | |
| pred,pred_idx,probs = learn.predict(img) | |
| return {labels[i]: float(probs[i]) for i in range(len(labels))} | |
| title = "PDF Classifier" | |
| description = "A model to classify documents, documents should be first converted to images" | |
| examples = ['aLRzygLYOk.pdf_1.png','auXcrtOmbP.pdf_1.png','basrgvSqEN.pdf_1.png', 'bpsiLLgpoa.pdf_1.png'] | |
| interpretation='default' | |
| enable_queue=True | |
| gr.Interface(fn=predict, inputs=gr.inputs.Image(shape=(512, 512)),title=title,description=description,examples=examples,interpretation=interpretation,enable_queue=enable_queue, outputs=gr.outputs.Label(num_top_classes=3)).launch(share=True) | |