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| import gradio as gr | |
| from fastai.vision.all import * | |
| # def greet(name): | |
| # return "Hello " + name + "!!" | |
| # demo = gr.Interface(fn=greet, inputs="text", outputs="text") | |
| # demo.launch() | |
| im = PILImage.create('victory.jpg') | |
| im | |
| learn = load_learner('clean_model.pkl') | |
| learn.predict(im) | |
| categories = ('victory hand sign photo','thumbs up human hand', 'thumbs down human hand') | |
| def classify_image(img): | |
| pred,idx,probs = learn.predict(img) | |
| return(dict(zip(categories,map(float,probs)))) | |
| print(classify_image(im)) | |
| ## | |
| image = gr.Image(width=500, height = 256) | |
| label = gr.Label() | |
| examples = ['victory.jpg'] | |
| intf = gr.Interface(fn = classify_image, inputs = image, outputs = label, examples = examples) | |
| intf.launch(inline = False) | |