Upload 5 files

.gitattributes

@@ -33,3 +33,6 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+anna-pelzer-IGfIGP5ONV0-unsplash.jpg filter=lfs diff=lfs merge=lfs -text
+nikolay-smeh-gPpbFaEkl00-unsplash.jpg filter=lfs diff=lfs merge=lfs -text
+pexels-marvin-ozz-2474658.jpg filter=lfs diff=lfs merge=lfs -text

app.py

@@ -0,0 +1,82 @@
+import streamlit as st
+import os
+from langchain_google_genai import GoogleGenerativeAIEmbeddings
+import google.generativeai as genai
+from langchain_google_genai import ChatGoogleGenerativeAI
+from dotenv import load_dotenv
+from PIL import Image
+import google.generativeai as genai
+
+load_dotenv()
+genai.configure(api_key=os.getenv("GOOGLE_API_KEY"))
+
+
+# Load Gemini pro vision
+
+model = genai.GenerativeModel("gemini-pro-vision")
+
+def get_final_response(system_prompt,input_image,user_prompt):
+    response = model.generate_content([system_prompt,input_image[0],user_prompt])
+    for candidate in response.candidates:
+        return [part.text for part in candidate.content.parts][0]
+    #return response.text
+
+def image_processing(upload_file):
+    """
+    This function converts the image in bytes
+    """
+
+    if upload_file is not None:
+        data_bytes = upload_file.getvalue()
+        image_parts = [
+            {
+                "mime_type" : upload_file.type,
+                "data" : data_bytes
+            }
+        ]
+        return image_parts
+    else:
+        raise FileNotFoundError("No file is uploaded.")
+    
+system_prompt  = """
+You're developing an advanced nutritional analysis tool that uses image recognition technology to estimate calorie intake from food images. 
+The system should be capable of accurately identifying different types of food items in an image and calculating the total calorie intake as well as providing a breakdown
+ of calorie counts for each food item detected. At the same time keep a count of quantity of each item and calculate calorie accordingly.
+
+The system will accept food images as input and return the following output (in bullet points):
+
+
+        Total calories : Sum of calories of all food item
+        1. Food item 1 (Quantity): Calorie count of food item 1 
+        2. Food item 2 (Quantity): Calorie count of food item 2 
+        3. Food item 3 (Quantity): Calorie count of food item 3 
+        .
+        .
+        . and so on..
+
+"""
+
+## Stremlit code:
+    
+st.set_page_config(page_title="Nutritional Model 🍿🍜")
+
+st.header("Calorie Analysis 🍔🍕")
+input = st.text_input("Input Prompt: ", key= "user_prompt")
+upload_file = st.file_uploader("Upload your Food Image", type = ["jpg", "jpeg", "png"])
+submit = st.button("Generate Calorie Analysis")
+
+image = ""
+
+if submit:
+    image_data = image_processing(upload_file)
+    response =  get_final_response(system_prompt,image_data,input)
+    st.subheader("See Calorie Analysis below : ")
+    st.success(response)
+
+if upload_file is not None:
+     image = Image.open(upload_file)
+     st.image(image, caption = "Uploaded image",width=500)
+
+
+
+

requirements.txt

@@ -0,0 +1,7 @@
+streamlit
+google-generativeai
+python-dotenv
+langchain
+PyPDF2
+chromadb
+langchain_google_genai