Upload app.py

backend/app.py

@@ -1,9 +1,38 @@
 from flask import Flask, request, jsonify, send_from_directory
 import io
 import os
+from PIL import Image
+import numpy as np
+import tensorflow as tf
 
 app = Flask(__name__, static_folder='../frontend', static_url_path='')
 
+model = tf.keras.models.load_model("./model.h5")
+
 @app.route("/")
 def index():
-    return send_from_directory(app.static_folder, "index.html")
+    return send_from_directory(app.static_folder, "index.html")
+
+@app.route("/predict", methods=["POST"])
+def predict():
+    file = request.files.get("file")
+    if file is None:
+        return jsonify({"error": "No file uploaded"}), 400
+
+    try:
+        img = Image.open(io.BytesIO(file.read())).convert("RGB").resize((32, 32))
+        arr = np.array(img).astype("float32") / 255.0
+        arr = np.expand_dims(arr, axis=0) 
+
+        preds = model.predict(arr)
+        top_idx = np.argmax(preds[0])
+        result = {
+            "class": top_idx,
+            "confidence": float(preds[0][top_idx]),
+            "raw": preds[0].tolist()
+        }
+
+        return jsonify(result)
+
+    except Exception as e:
+        return jsonify({"error": f"Gagal memproses gambar: {str(e)}"}), 500