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Created Recipe Generator

app.py

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+import streamlit as st
+import torch
+import cv2
+import numpy as np
+from ultralytics import YOLO
+from PIL import Image
+import easyocr
+import requests
+
+def load_model():
+    # Load the pre-trained YOLOv8 model for object detection
+    model = YOLO("yolov8n.pt")  # You can use a custom-trained model for food detection
+    return model
+
+def detect_ingredients(image, model):
+    results = model(image)
+    detected_items = set()
+    for result in results:
+        for box in result.boxes:
+            cls = result.names[int(box.cls[0])]
+            detected_items.add(cls)
+    return list(detected_items)
+
+def extract_text(image):
+    # Use EasyOCR to extract text from the image
+    reader = easyocr.Reader(['en'])  # Specify language
+    results = reader.readtext(np.array(image))  # Convert PIL image to NumPy
+    extracted_text = [text[1] for text in results]  # Extract detected text
+    return extracted_text
+
+MEALDB_API_URL = "https://www.themealdb.com/api/json/v1/1"
+
+def fetch_ingredients():
+    """Fetches a list of available ingredients from TheMealDB API."""
+    url = f"{MEALDB_API_URL}/list.php?i=list"
+    response = requests.get(url)
+    if response.status_code == 200:
+        data = response.json()
+        return [item["strIngredient"].lower() for item in data["meals"]]
+    return []
+
+def filter_valid_ingredients(detected_ingredients):
+    """Filters detected ingredients against TheMealDB ingredient list."""
+    valid_ingredients = fetch_ingredients()
+    return [ing for ing in detected_ingredients if ing.lower() in valid_ingredients]
+
+def get_recipes(ingredients):
+    """Fetch recipes from TheMealDB based on detected ingredients."""
+    recipe_list = set()
+    
+    for ingredient in ingredients:
+        url = f"{MEALDB_API_URL}/filter.php?i={ingredient}"
+        response = requests.get(url)
+        
+        if response.status_code == 200:
+            data = response.json()
+            if data["meals"]:
+                for meal in data["meals"]:
+                    recipe_list.add(meal["strMeal"])
+    
+    return list(recipe_list) if recipe_list else ["No matching recipes found."]
+
+def main():
+    st.title("VQA Recipe Generator")
+    st.write("Upload an image of ingredients, and we'll suggest recipes you can make!")
+
+    with st.expander("How It Works"):
+        st.write("""
+        1. **Upload an Image**: Upload a photo of ingredients you have.
+        2. **Ingredient Detection**: The app uses a YOLOv8 model to detect visible ingredients.
+        3. **Text Extraction**: Any text in the image (e.g., labels) is extracted using EasyOCR.
+        4. **Ingredient Validation**: The detected ingredients are cross-checked with TheMealDB database.
+        5. **Recipe Suggestions**: The app fetches recipes that match the available ingredients.
+        P.S This is a work in progress so it can't cater all ingredients and can't really detect if ingredients don't have labels.
+        """)
+    
+    model = load_model()
+    
+    uploaded_file = st.file_uploader("Upload an image", type=["jpg", "png", "jpeg"])
+    if uploaded_file:
+        image = Image.open(uploaded_file)
+        st.image(image, caption="Uploaded Image", use_column_width=True)
+        
+        # Convert image for processing
+        img_array = np.array(image)
+        img_array = cv2.cvtColor(img_array, cv2.COLOR_RGB2BGR)
+        
+        with st.spinner("Detecting ingredients..."):
+            detected_ingredients = detect_ingredients(img_array, model)
+            extracted_text = extract_text(image)
+            
+            # Merge OCR text with detected objects
+            detected_ingredients.extend(extracted_text)
+            
+            # Filter only valid ingredients from TheMealDB
+            valid_ingredients = filter_valid_ingredients(detected_ingredients)
+            
+        st.subheader("Detected Ingredients:")
+        st.write(", ".join(valid_ingredients))
+        
+        recipes = get_recipes(valid_ingredients)
+        
+        st.subheader("Suggested Recipes:")
+        for recipe in recipes:
+            st.write(f"- {recipe}")
+
+if __name__ == "__main__":
+    main()

yolov8n.pt

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+version https://git-lfs.github.com/spec/v1
+oid sha256:f59b3d833e2ff32e194b5bb8e08d211dc7c5bdf144b90d2c8412c47ccfc83b36
+size 6549796