Create app.py

app.py

@@ -0,0 +1,36 @@
+from flask import Flask, request, jsonify
+from transformers import AutoModelForImageClassification, AutoProcessor
+import torch
+from PIL import Image
+import io
+
+app = Flask(__name__)
+
+# ✅ Load the model with trust_remote_code=True
+model = AutoModelForImageClassification.from_pretrained(
+    "shahad-alh/arabichar-finetuned-v2",
+    trust_remote_code=True
+)
+processor = AutoProcessor.from_pretrained("shahad-alh/arabichar-finetuned-v2")
+
+@app.route('/classify', methods=['POST'])
+def classify():
+    if 'file' not in request.files:
+        return jsonify({"error": "No file uploaded"}), 400
+
+    file = request.files['file']
+    image = Image.open(io.BytesIO(file.read()))
+
+    # ✅ Process the image
+    inputs = processor(images=image, return_tensors="pt")
+
+    # ✅ Run inference
+    with torch.no_grad():
+        outputs = model(**inputs)
+
+    # ✅ Get predicted class
+    predicted_class = torch.argmax(outputs.logits, dim=-1).item()
+    return jsonify({"prediction": predicted_class})
+
+if __name__ == '__main__':
+    app.run(host="0.0.0.0", port=7860)