Delete app.py

app.py

@@ -1,29 +0,0 @@
-import gradio as gr
-import tensorflow as tf
-import numpy as np
-
-# Load model
-model = tf.keras.models.load_model("waste_classification_finetuned.h5")
-IMG_SIZE = (224, 224)
-
-# Class labels
-index_to_label = {
-    0: "paper", 1: "e-waste", 2: "metal", 3: "light blubs",
-    4: "organic", 5: "plastic", 6: "clothes", 7: "glass", 8: "batteries"
-}
-
-def classify_image(img):
-    img = tf.image.resize(img, IMG_SIZE)
-    img = tf.expand_dims(img, axis=0)
-    img = tf.cast(img, tf.float32) / 255.0
-    pred = model.predict(img)[0]
-    return {index_to_label[i]: float(pred[i]) for i in range(len(pred))}
-
-demo = gr.Interface(
-    fn=classify_image,
-    inputs=gr.Image(type="numpy", label="Upload Waste Image"),
-    outputs=gr.Label(num_top_classes=3),
-    title="Smart Waste Classifier"
-)
-
-demo.launch()