Upload app.py

app.py

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+import os
+
+import cv2
+import gradio as gr
+import numpy as np
+import tensorflow as tf
+from huggingface_hub import from_pretrained_keras
+
+MODEL_NAME = os.getenv("MODEL_NAME")
+HF_TOKEN = os.getenv("HF_TOKEN")
+
+model = from_pretrained_keras(MODEL_NAME, token=HF_TOKEN)
+
+
+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)