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import io |
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import base64 |
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import requests |
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import numpy as np |
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import gradio as gr |
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from PIL import Image |
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from io import BytesIO |
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def image_classifier(image, api_key): |
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buffered = io.BytesIO() |
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image = Image.fromarray(np.uint8(image)) |
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image = image.convert("RGB") |
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image.save(buffered, quality=90, format="JPEG") |
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img_str = base64.b64encode(buffered.getvalue()) |
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img_str = img_str.decode("ascii") |
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headers = {'Content-Type': 'application/json', 'accept': 'application/json'} |
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r = requests.post(f'https://classify.roboflow.com/clasificacion-sin-regularizacion/1?api_key={api_key}', |
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data=img_str, |
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headers=headers) |
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preds = r.json() |
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output = {x:round(float(y['confidence']), 3) for x,y in preds['predictions'].items()} |
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return output |
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demo = gr.Interface(fn=image_classifier, inputs=["image", "text"], outputs="label") |
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demo.launch(debug=True) |
