Add better model

app.py

@@ -2,13 +2,12 @@ import gradio as gr
 from transformers import pipeline
 from PIL import Image
 import torch
-from torchvision import transforms
+import re
 
-# MODELES
+# —————————————————————————————
+# 1. CLASSIFICATION D’INGReDIENTS
+# —————————————————————————————
 INGREDIENT_MODEL_ID = "stchakman/Fridge_Items_Model"
-RECIPE_MODEL_ID = "flax-community/t5-recipe-generation"
-
-# PIPELINES
 ingredient_classifier = pipeline(
     "image-classification",
     model=INGREDIENT_MODEL_ID,
@@ -16,47 +15,67 @@ ingredient_classifier = pipeline(
     top_k=4
 )
 
+# —————————————————————————————
+# 2. MODeLE DE GeNeRATION
+# —————————————————————————————
 recipe_generator = pipeline(
     "text2text-generation",
-    model=RECIPE_MODEL_ID,
+    model="flax-community/t5-recipe-generation",
     device=0 if torch.cuda.is_available() else -1
 )
 
-# AUGMENTATION
-augment = transforms.Compose([
-    transforms.RandomHorizontalFlip(p=0.5),
-    transforms.RandomRotation(10),
-    transforms.ColorJitter(brightness=0.2, contrast=0.2),
-])
-
-# FONCTION PRINCIPALE
+# —————————————————————————————
+# 3. FONCTION PRINCIPALE
+# —————————————————————————————
 def generate_recipe(image: Image.Image):
     try:
-        yield "🔄 Traitement de l'image..."
+        # Detection ingredients
+        results = ingredient_classifier(image)
+        ingredients = [res["label"].lower() for res in results]
+        if not ingredients:
+            return {
+                "error": "Aucun ingredient detecte.",
+                "ingredients_detected": []
+            }
+
+        prompt = ", ".join(ingredients)
+        generated = recipe_generator(prompt, max_length=200)[0]["generated_text"]
 
-        image_aug = image
+        # extraction par expressions regulieres
+        title_match = re.search(r"title\s*:\s*(.+?)(ingredients\s*:|$)", generated, re.IGNORECASE | re.DOTALL)
+        ingredients_match = re.search(r"ingredients\s*:\s*(.+?)(directions\s*:|$)", generated, re.IGNORECASE | re.DOTALL)
+        directions_match = re.search(r"directions\s*:\s*(.+)", generated, re.IGNORECASE | re.DOTALL)
 
-        yield "📸 Classification en cours..."
-        results = ingredient_classifier(image_aug)
-        ingredients = [res["label"] for res in results]
-        ingredient_str = ", ".join(ingredients)
+        title = title_match.group(1).strip() if title_match else None
+        ingredients_list = ingredients_match.group(1).strip().split('\n') if ingredients_match else []
+        directions_raw = directions_match.group(1).strip() if directions_match else None
+        directions_list = re.split(r"\.\s*", directions_raw) if directions_raw else []
 
-        yield f"🥕 Ingrédients détectés : {ingredient_str}\n\n🍳 Génération de la recette..."
-        prompt = f"Ingredients: {ingredient_str}. Recipe:"
-        recipe = recipe_generator(prompt, max_new_tokens=256, do_sample=True)[0]["generated_text"]
+        # nettoyage des listes
+        ingredients_list = [line.strip("- ").strip() for line in ingredients_list if line.strip()]
+        directions_list = [step.strip("- ").strip() for step in directions_list if step.strip()]
 
-        yield f"### 🥕 Ingrédients détectés :\n{ingredient_str}\n\n### 🍽️ Recette générée :\n{recipe}"
+        return {
+            "ingredients_detected": ingredients,
+            "generated": {
+                "title": title,
+                "ingredients": ingredients_list,
+                "instructions": directions_list
+            }
+        }
 
     except Exception as e:
-        yield f"❌ Une erreur est survenue : {str(e)}"
+        return {"error": str(e)}
 
-# INTERFACE
+# —————————————————————————————
+# 4. INTERFACE GRADIO
+# —————————————————————————————
 interface = gr.Interface(
     fn=generate_recipe,
-    inputs=gr.Image(type="pil", label="📷 Image de vos ingrédients"),
-    outputs=gr.Markdown(),
-    title="🥕 Générateur de Recettes 🧑‍🍳",
-    description="Dépose une image d'ingrédients pour obtenir une recette automatiquement générée à partir d'un modèle IA.",
+    inputs=gr.Image(type="pil", label="📷 Image de vos ingredients"),
+    outputs=gr.JSON(),
+    title="🥕 Generateur de Recettes",
+    description="Deposez une image d'ingredients pour generer une recette automatiquement (resultat JSON structure).",
     allow_flagging="never"
 )