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app.py

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+import torch
+import pandas as pd
+import gradio as gr
+from PIL import Image
+from ultralytics import YOLO
+
+# Load YOLOv8 model
+model = YOLO("best (1).pt")  # Ensure "best.pt" is in the same directory
+
+# Load nutrition data CSV
+nutrition_df = pd.read_csv("cleaned_nutrition_values.csv")
+
+# Function to get nutrition info
+def get_nutrition_info(food):
+    food_lower = food.lower()
+    nutrition_info = nutrition_df[nutrition_df["Food Item"].str.lower() == food_lower]
+
+    if not nutrition_info.empty:
+        return nutrition_info.to_dict(orient="records")[0]
+    else:
+        return "No nutrition data available."
+
+# Function to process image and return food detection + nutrition
+def detect_food(image):
+    results = model(image)  # Run YOLO model on the image
+    detected_foods = [model.names[int(box.cls)] for r in results for box in r.boxes]
+
+    output = []
+    for food in detected_foods:
+        nutrition_info = get_nutrition_info(food)
+        output.append({"food": food, "nutrition": nutrition_info})
+    
+    return output
+
+# Gradio UI
+iface = gr.Interface(
+    fn=detect_food,
+    inputs=gr.Image(type="pil"),
+    outputs="json",
+    title="🍕 Food Detection & Nutrition Lookup",
+    description="Upload an image of food, and this app will detect the food item and provide its nutrition details.",
+)
+
+# Run Gradio App
+if __name__ == "__main__":
+    iface.launch()

best (1).pt

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+version https://git-lfs.github.com/spec/v1
+oid sha256:00b6cf93829db8099c7ddfc4e0edb7c0ef2ecf9f961b572acc257cbe73b6d8b8
+size 52167755

cleaned_nutrition_values.csv

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+Food Item,Calories (kcal),Protein (g),Carbohydrates (g),Fat (g),Sugar (g),Cholesterol (mg)
+Chicken,239,27.0,0.0,14.0,0.0,88
+Curd,98,11.0,4.0,5.0,4.0,17
+Gulab Jamun,432,5.0,60.0,20.0,35.0,10
+Kadai Paneer,270,14.0,10.0,20.0,4.0,40
+Kadhi Pakoda,130,5.0,15.0,6.0,3.0,15
+Kalakand,347,8.0,45.0,15.0,30.0,25
+Naan,275,9.0,50.0,5.0,3.0,2
+Palak Paneer,180,10.0,8.0,12.0,3.0,30
+Paneer Butter Masala,320,12.0,15.0,25.0,6.0,45
+Soan Papdi,540,5.0,60.0,30.0,40.0,0
+Banana,89,1.1,23.0,0.3,12.0,0
+Basundi,200,6.0,20.0,10.0,18.0,30
+Beans,35,2.0,7.0,0.2,1.0,0
+Bindi (Okra),33,2.0,7.0,0.1,1.0,0
+Biryani,290,12.0,40.0,10.0,2.0,40
+Black Beans,132,9.0,24.0,0.5,1.0,0
+Brinjal Gravy,150,3.0,10.0,12.0,2.0,10
+Buttermilk,40,3.0,5.0,1.0,4.0,5
+Cabbage,25,1.3,6.0,0.1,3.0,0
+Cauliflower,25,2.0,5.0,0.3,2.0,0
+Channa Masala,180,8.0,20.0,6.0,3.0,10
+Chapati,200,6.0,40.0,4.0,2.0,0
+Chicken Tikka Masala,150,12.0,5.0,10.0,3.0,50
+Curd Rice,120,5.0,20.0,4.0,3.0,15
+Dal Tadka,126,6.0,15.0,4.0,2.0,10
+Dosa,168,4.0,30.0,4.0,2.0,0
+Egg,155,13.0,1.0,11.0,1.0,373
+Egg Gravy,180,10.0,8.0,12.0,2.0,220
+Fish Curry,120,15.0,5.0,6.0,2.0,50
+Fish Fry,220,20.0,10.0,12.0,1.0,65
+Idli,140,3.0,28.0,1.0,1.0,0
+Jalebi,300,2.0,60.0,10.0,50.0,5
+Kachori,290,7.0,35.0,15.0,5.0,10
+Lemon Rice,210,4.0,35.0,8.0,2.0,5
+Momos,200,8.0,30.0,6.0,1.0,10
+Omelette,160,12.0,2.0,12.0,1.0,260
+Paneer,265,18.0,2.0,21.0,1.0,50
+Papad,371,22.0,55.0,2.0,1.0,0
+Parotta,270,6.0,45.0,10.0,3.0,5
+Pickle,60,2.0,10.0,2.0,4.0,0
+Pizza,280,12.0,35.0,10.0,3.0,25
+Poha,212,4.0,35.0,7.0,2.0,5
+Pongal,210,5.0,35.0,7.0,3.0,10
+Poori,260,6.0,40.0,12.0,3.0,5
+Prawn,99,20.0,1.0,1.0,0.0,195
+Pulav,250,5.0,40.0,8.0,2.0,15
+Rabri,250,6.0,30.0,10.0,25.0,30
+Raita,80,3.0,8.0,3.0,4.0,10
+Rasam,40,2.0,6.0,1.0,2.0,0
+Rasgulla,186,4.0,35.0,5.0,30.0,10
+Rice,130,2.7,28.0,0.3,0.1,0
+Roti,200,6.0,40.0,4.0,2.0,0
+Sambar,120,6.0,15.0,4.0,2.0,5
+Sheera,250,4.0,35.0,10.0,25.0,5
+Soft Drink,40,0.0,10.0,0.0,10.0,0
+Spaghetti,160,6.0,31.0,1.0,2.0,0
+Sweet,400,5.0,60.0,15.0,40.0,10
+Tandoori Chicken,220,25.0,5.0,10.0,2.0,65
+Vada,290,8.0,35.0,15.0,3.0,5
+Vegetables,50,2.0,10.0,0.5,3.0,0
+White Rice,130,2.7,28.0,0.3,0.1,0
+Apple,52,0.3,14.0,0.2,10.0,0
+Banana,89,1.1,23.0,0.3,12.0,0
+Carrot,41,0.9,10.0,0.2,4.7,0
+Tomato,18,0.9,3.9,0.2,2.6,0
+Potato,77,2.0,17.0,0.1,0.8,0
+Spinach,23,2.9,3.6,0.4,0.4,0
+Milk,42,3.4,5.0,1.0,5.0,5
+Egg,155,13.0,1.1,11.0,1.1,373
+Almonds,579,21.0,22.0,50.0,4.4,0
+Rice (Cooked),130,2.7,28.0,0.3,0.1,0
+Wheat Flour,340,13.2,72.0,2.5,0.4,0
+Orange,47,0.9,12.0,0.1,9.0,0
+Mango,60,0.8,15.0,0.4,14.0,0
+Pineapple,50,0.5,13.0,0.1,10.0,0
+Strawberry,32,0.7,7.7,0.3,4.9,0
+Cabbage,25,1.3,6.0,0.1,3.2,0
+Broccoli,34,2.8,7.0,0.4,1.7,0
+Peanuts,567,25.8,16.0,49.0,4.7,0
+Lentils,116,9.0,20.0,0.4,1.8,0
+Chickpeas,164,8.9,27.4,2.6,4.8,0
+Grapes,69,0.7,18.0,0.2,15.0,0
+Papaya,43,0.5,11.0,0.3,8.0,0
+Guava,68,2.6,14.0,0.9,9.0,0
+Pomegranate,83,1.7,19.0,1.2,14.0,0
+Watermelon,30,0.6,8.0,0.2,6.0,0
+Avocado,160,2.0,9.0,15.0,0.7,0
+Kiwi,61,1.1,15.0,0.5,9.0,0
+Chia Seeds,486,16.0,42.0,31.0,0.0,0
+Sunflower Seeds,584,21.0,20.0,51.0,2.6,0
+Sesame Seeds,573,18.0,23.0,50.0,0.3,0

requirements.txt

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+ultralytics
+torch
+torchvision
+gradio
+huggingface_hub