Update app.py

app.py

@@ -1,35 +1,22 @@
 from flask import Flask, request, jsonify
 from transformers import pipeline
-from PIL import Image
-import io
+import os
+
+# Önemli: huggingface hub cache dizinini değiştir
+os.environ['HF_HOME'] = '/tmp/huggingface'
+os.environ['TRANSFORMERS_CACHE'] = '/tmp/transformers'
 
 app = Flask(__name__)
 
-# Hugging Face modelini yüklüyoruz (tek seferlik)
 classifier = pipeline("image-classification", model="ahmed792002/vit-plant-classification")
 
-@app.route("/", methods=["GET"])
-def home():
-    return "Lumi çalışıyor 🌿"
-
-@app.route("/predict", methods=["POST"])
+@app.route('/predict', methods=['POST'])
 def predict():
     if 'image' not in request.files:
-        return jsonify({"error": "Görsel dosyası 'image' olarak gönderilmeli."}), 400
+        return jsonify({'error': 'No image uploaded'}), 400
 
-    image_file = request.files['image']
-    try:
-        image = Image.open(image_file.stream)
-        results = classifier(image)
-        # En yüksek olasılıklı sonucu al
-        best = results[0]
-        label = best["label"]
-        score = round(best["score"] * 100, 2)
+    image = request.files['image']
+    predictions = classifier(image)
+    return jsonify(predictions)
 
-        return jsonify({
-            "bitkiAdi": label,
-            "tahminOrani": f"%{score}"
-        })
-    except Exception as e:
-        return jsonify({"error": str(e)}), 500