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import os
import cv2
import gradio as gr
import numpy as np
import tensorflow as tf
from huggingface_hub import login, from_pretrained_keras
MODEL_NAME = os.getenv("MODEL_NAME")
HF_TOKEN = os.getenv("HF_TOKEN")
login(token=HF_TOKEN)
model = from_pretrained_keras(MODEL_NAME)
def classify_image(inp):
inp = cv2.resize(inp, (299, 299))
inp = np.expand_dims(inp, axis=0)
prediction = model.predict(inp)
pred = tf.nn.sigmoid(prediction).numpy().squeeze()
confidences = {"Application": 1 - pred, "Product": pred.item()}
return confidences
gr.Interface(
fn=classify_image,
inputs=gr.Image(),
outputs=gr.Label(num_top_classes=2),
allow_flagging="never",
).launch(debug=True, enable_queue=True)
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