work of nayon

.gitattributes

@@ -33,3 +33,4 @@ 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
+image_to_food_model.keras filter=lfs diff=lfs merge=lfs -text

image_to_food_model.h5

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+version https://git-lfs.github.com/spec/v1
+oid sha256:b1c2179ca3751be5bce47fcd79940ac3697099530871a09fa5015711a80c532d
+size 45028192

image_to_food_model.keras

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:5fc9bbb79489b2b12e8207fd1c64ced29302b9125b58e1c3259ece747d1f47b9
+size 45027596

image_to_food_model1.h5

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:40c57ca9506bb3762fb6f3ad0bf7b4983c235866c4b34d5f31fc78d0128d0b15
+size 45028192

labels.txt

@@ -0,0 +1,80 @@
+adhirasam
+aloo_gobi
+aloo_matar
+aloo_methi
+aloo_shimla_mirch
+aloo_tikki
+anarsa
+ariselu
+bandar_laddu
+basundi
+bhatura
+bhindi_masala
+biryani
+boondi
+butter_chicken
+chak_hao_kheer
+cham_cham
+chana_masala
+chapati
+chhena_kheeri
+chicken_razala
+chicken_tikka
+chicken_tikka_masala
+chikki
+daal_baati_churma
+daal_puri
+dal_makhani
+dal_tadka
+dharwad_pedha
+doodhpak
+double_ka_meetha
+dum_aloo
+gajar_ka_halwa
+gavvalu
+ghevar
+gulab_jamun
+imarti
+jalebi
+kachori
+kadai_paneer
+kadhi_pakoda
+kajjikaya
+kakinada_khaja
+kalakand
+karela_bharta
+kofta
+kuzhi_paniyaram
+lassi
+ledikeni
+litti_chokha
+lyangcha
+maach_jhol
+makki_di_roti_sarson_da_saag
+malapua
+misi_roti
+misti_doi
+modak
+mysore_pak
+naan
+navrattan_korma
+palak_paneer
+paneer_butter_masala
+phirni
+pithe
+poha
+poornalu
+pootharekulu
+qubani_ka_meetha
+rabri
+ras_malai
+rasgulla
+sandesh
+shankarpali
+sheer_korma
+sheera
+shrikhand
+sohan_halwa
+sohan_papdi
+sutar_feni
+unni_appam

main.py

@@ -0,0 +1,110 @@
+# import streamlit as st
+# import tensorflow as tf
+# import numpy as np
+# from flask import Flask, jsonify, request
+# import requests
+
+# # Create a Flask app
+# app = Flask(__name__)
+
+# # Tensorflow Model Prediction
+# def model_prediction(test_image):
+#     model = tf.keras.models.load_model("image_to_food_model1.h5")
+#     image = tf.keras.preprocessing.image.load_img(test_image, target_size=(256, 256))
+#     input_arr = tf.keras.preprocessing.image.img_to_array(image)
+#     input_arr = np.array([input_arr])  # convert single image to batch
+#     predictions = model.predict(input_arr)
+#     return np.argmax(predictions)  # return index of max element
+
+
+# # Define an endpoint to handle predictions
+# @app.route('/', methods=['POST'])
+# def predict():
+#     test_image = request.files['file']
+#     result_index = model_prediction(test_image)
+#     # Reading Labels
+#     with open("labels.txt") as f:
+#         content = f.readlines()
+#     label = [i.strip() for i in content]
+#     prediction = label[result_index]
+#     return jsonify({"prediction": prediction})
+
+
+# # Sidebar
+# st.sidebar.title("Dashboard")
+# app_mode = st.sidebar.selectbox("Select Page", ["Prediction"])
+
+# # Main Page
+# # if app_mode == "Home":
+# #     st.header("Food Recipe")
+# #     image_path = "home_page.jpg"
+# #     st.image(image_path)
+
+# # Prediction Page
+# if app_mode == "Prediction":
+#     st.header("Model Prediction")
+#     test_image = st.file_uploader("Choose an Image:")
+#     if st.button("Show Image"):
+#         st.image(test_image, width=4, use_column_width=True)
+
+#     # Predict button
+#     if st.button("Predict"):
+#         st.write("Our Prediction")
+#         # Send image to backend for prediction
+#         files = {'file': test_image.getvalue()}
+#         response = requests.post('http://localhost:8501', files=files)
+#         prediction = response.json()["prediction"]
+#         st.success("Model is Predicting it's a {}".format(prediction))
+
+
+
+
+import streamlit as st
+import tensorflow as tf
+import numpy as np
+
+
+
+#Tensorflow Model Prediction
+def model_prediction(test_image):
+    model = tf.keras.models.load_model("image_to_food_model1.h5")
+    image = tf.keras.preprocessing.image.load_img(test_image,target_size=(256,256))
+    input_arr = tf.keras.preprocessing.image.img_to_array(image)
+    input_arr = np.array([input_arr]) #convert single image to batch
+    predictions = model.predict(input_arr)
+    return np.argmax(predictions) #return index of max element
+
+
+#Sidebar
+st.sidebar.title("Dashboard")
+app_mode = st.sidebar.selectbox("Select Page",["Prediction"])
+
+# #Main Page
+# if(app_mode=="Home"):
+#     st.header("Food Recipe")
+#     image_path = "home_page.jpg"
+#     st.image(image_path)
+
+
+#Prediction Page
+if(app_mode=="Prediction"):
+    st.header("Model Prediction")
+    test_image = st.file_uploader("Choose an Image:")
+    if(st.button("Show Image")):
+        st.image(test_image,width=4,use_column_width=True)
+    
+    #Predict button
+    if(st.button("Predict")):
+        st.snow()
+        st.write("Our Prediction")
+        result_index = model_prediction(test_image)
+        #Reading Labels
+        with open("labels.txt") as f:
+            content = f.readlines()
+        label = []
+        
+        for i in content:
+            label.append(i[:-1])
+        st.success("Model is Predicting it's a {}".format(label[result_index]))
+  
+

requirements.txt

@@ -0,0 +1,65 @@
+absl-py==2.1.0
+altair==5.3.0
+astunparse==1.6.3
+attrs==23.2.0
+blinker==1.8.2
+cachetools==5.3.3
+certifi==2024.2.2
+charset-normalizer==3.3.2
+click==8.1.7
+colorama==0.4.6
+flatbuffers==24.3.25
+gast==0.5.4
+gitdb==4.0.11
+GitPython==3.1.43
+google-pasta==0.2.0
+grpcio==1.63.0
+h5py==3.11.0
+idna==3.7
+Jinja2==3.1.4
+jsonschema==4.22.0
+jsonschema-specifications==2023.12.1
+keras==3.3.3
+libclang==18.1.1
+Markdown==3.6
+markdown-it-py==3.0.0
+MarkupSafe==2.1.5
+mdurl==0.1.2
+ml-dtypes==0.3.2
+namex==0.0.8
+numpy==1.26.4
+opt-einsum==3.3.0
+optree==0.11.0
+packaging==24.0
+pandas==2.2.2
+pillow==10.3.0
+protobuf==4.25.3
+pyarrow==16.0.0
+pydeck==0.9.1
+Pygments==2.18.0
+python-dateutil==2.9.0.post0
+pytz==2024.1
+referencing==0.35.1
+requests==2.31.0
+rich==13.7.1
+rpds-py==0.18.1
+setuptools==69.5.1
+six==1.16.0
+smmap==5.0.1
+streamlit==1.34.0
+tenacity==8.3.0
+tensorboard==2.16.2
+tensorboard-data-server==0.7.2
+tensorflow==2.16.1
+tensorflow-intel==2.16.1
+termcolor==2.4.0
+toml==0.10.2
+toolz==0.12.1
+tornado==6.4
+typing_extensions==4.11.0
+tzdata==2024.1
+urllib3==2.2.1
+watchdog==4.0.0
+Werkzeug==3.0.3
+wheel==0.43.0
+wrapt==1.16.0