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import gradio as gr | |
from huggingface_hub import from_pretrained_keras | |
from tensorflow.keras.preprocessing.image import array_to_img, img_to_array | |
from .labels import CLASS_LABELS | |
model = from_pretrained_keras("jsolow/grubguesser") | |
def _preprocess(imgage_input): | |
img = array_to_img(imgage_input, scale=False) | |
img = img.resize((224, 224)) | |
img = img_to_array(img) | |
return img / 255.0 | |
def predict(image): | |
image_array = _preprocess(image) | |
predictions = model.predict(image_array) | |
return {k:v for k, v in zip(CLASS_LABELS, predictions)} | |
gr.Interface( | |
predict, | |
inputs=gr.inputs.Image(label="Upload food image", type="filepath"), | |
outputs=gr.outputs.Label(num_top_classes=10), | |
title="Grubguesser - What is this food?", | |
).launch() | |