Update app.py

app.py

@@ -1,11 +1,9 @@
-
-
 import os, io, sys, base64, traceback
 from pathlib import Path
 from flask import Flask, request, render_template, jsonify
 from PIL import Image
 
-# Répertoire absolu contenant app.py
+
 BASE_DIR = Path(__file__).resolve().parent
 if str(BASE_DIR) not in sys.path:
     sys.path.insert(0, str(BASE_DIR))
@@ -42,9 +40,9 @@ def predict():
     file         = request.files.get("image")
 
     if not file or file.filename == "":
-        return render_template("index.html", error="Veuillez uploader une image."), 400
+        return render_template("index.html", error="Upload an image."), 400
     if not allowed_file(file.filename):
-        return render_template("index.html", error="Format non supporté. Utilisez JPG, PNG, WEBP ou BMP."), 400
+        return render_template("index.html", error="You have to use JPG, PNG, WEBP ou BMP."), 400
 
     img_bytes = file.read()
     pil_img   = Image.open(io.BytesIO(img_bytes)).convert("RGB")
@@ -54,20 +52,20 @@ def predict():
     try:
         if model_choice == "pytorch":
             if not Path(PYTORCH_MODEL_PATH).exists():
-                raise FileNotFoundError(f"Modèle PyTorch introuvable : {PYTORCH_MODEL_PATH}")
+                raise FileNotFoundError(f"Model PyTorch not found : {PYTORCH_MODEL_PATH}")
             result = predict_pytorch(str(tmp_path), model_path=PYTORCH_MODEL_PATH)
         else:
             if not Path(TF_MODEL_PATH).exists():
-                raise FileNotFoundError(f"Modèle TensorFlow introuvable : {TF_MODEL_PATH}")
+                raise FileNotFoundError(f"Model TensorFlow not found : {TF_MODEL_PATH}")
             result = predict_tensorflow(str(tmp_path), model_path=TF_MODEL_PATH)
 
     except FileNotFoundError as e:
         tmp_path.unlink(missing_ok=True)
-        return render_template("index.html", error=f"Modèle introuvable : {e}"), 500
+        return render_template("index.html", error=f"Model not found : {e}"), 500
     except Exception as e:
         tmp_path.unlink(missing_ok=True)
         print("ERREUR INFERENCE :", traceback.format_exc())
-        return render_template("index.html", error=f"Erreur : {str(e)}"), 500
+        return render_template("index.html", error=f"Error : {str(e)}"), 500
     finally:
         tmp_path.unlink(missing_ok=True)