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.gitattributes

@@ -32,3 +32,5 @@ 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
+examples/example_1.jpg filter=lfs diff=lfs merge=lfs -text
+examples/example_6.jpg filter=lfs diff=lfs merge=lfs -text

README.md

@@ -1,13 +1,13 @@
 ---
-title: Food-Category-Classification V2 App
-emoji: 💩
-colorFrom: green
-colorTo: indigo
-sdk: streamlit
-sdk_version: 1.17.0
+title: Food Category Classification V2 App
+emoji: 🍳
+colorFrom: blue
+colorTo: green
+sdk: gradio
+sdk_version: 3.0.24
 app_file: app.py
 pinned: false
-license: openrail
+license: apache-2.0
 ---
 
 Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

@@ -0,0 +1,112 @@
+import streamlit as st
+from PIL import Image
+
+from transformers import pipeline
+import numpy as np
+from transformers import AutoFeatureExtractor
+from transformers import AutoModelForImageClassification
+
+st.set_page_config(layout='wide',
+                   page_title='Food Category Classification & Recipes'
+                   )
+
+# Setting up Sidebar
+social_acc = ['App Description', 'About Project']
+social_acc_nav = st.sidebar.radio('**INFORMATION SECTION**', social_acc)
+
+if social_acc_nav == 'App Description':
+    st.sidebar.markdown("<h2 style='text-align: center;'> Food Category Classification Description </h2> ", unsafe_allow_html=True)
+    st.sidebar.markdown("This is an updated Food Category Image Classifier model of the [old](https://huggingface.co/Kaludi/food-category-classification) model that has been trained by [Kaludi](https://huggingface.co/Kaludi) to recognize 12 different categories of foods, which includes **Bread**, **Dairy**, **Dessert**, **Egg**, **Fried Food**, **Fruit**, **Meat**, **Noodles**, **Rice**, **Seafood**, **Soup**, and **Vegetable**. It can accurately classify an image of food into one of these categories by analyzing its visual features. This model can be used by food bloggers, restaurants, and recipe websites to quickly categorize and sort their food images, making it easier to manage their content and provide a better user experience.")
+
+elif social_acc_nav == 'About Project':
+    st.sidebar.markdown("<h2 style='text-align: center;'> About Project </h2>", unsafe_allow_html=True)
+    st.sidebar.markdown("<hr style='text-align: center;'>", unsafe_allow_html=True)
+    st.sidebar.markdown("<h3 style='text-align: center;'>Project Location:</h3>", unsafe_allow_html=True)
+    st.sidebar.markdown("<p style='text-align: center;'><strong><a href='https://github.com/Kaludii'>Model</a></strong>  |  <strong><a href='https://github.com/Kaludii'>Dataset</a></strong></p>", unsafe_allow_html=True)
+    st.sidebar.markdown("<hr style='text-align: center;'>", unsafe_allow_html=True)
+    st.sidebar.markdown("<h3 style='text-align: center;'>Project Creators:</h3>", unsafe_allow_html=True)
+    st.sidebar.markdown("<p style='text-align: center;'><a href='https://github.com/Kaludii'><strong>AA</strong></a></p>", unsafe_allow_html=True)
+    st.sidebar.markdown("<p style='text-align: center;'><a href='https://github.com/Kaludii'><strong>AM</strong></a></p>", unsafe_allow_html=True)
+    st.sidebar.markdown("<p style='text-align: center;'><a href='https://github.com/Kaludii'><strong>BK</strong></a></p>", unsafe_allow_html=True)
+    st.sidebar.markdown("<p style='text-align: center;'><a href='https://github.com/Kaludii'><strong>DK</strong></a></p>", unsafe_allow_html=True)
+    
+
+def main():
+    st.title("Food Category Classification & Recipes")
+     
+    st.markdown("### Backgroud")  
+    st.markdown("This is an updated Food Category Image Classifier model of the [old](https://huggingface.co/Kaludi/food-category-classification) model that has been trained by [Kaludi](https://huggingface.co/Kaludi) to recognize 12 different categories of foods, which includes **Bread**, **Dairy**, **Dessert**, **Egg**, **Fried Food**, **Fruit**, **Meat**, **Noodles**, **Rice**, **Seafood**, **Soup**, and **Vegetable**. It can accurately classify an image of food into one of these categories by analyzing its visual features. This model can be used by food bloggers, restaurants, and recipe websites to quickly categorize and sort their food images, making it easier to manage their content and provide a better user experience.")  
+    st.header("Try it out!")
+
+    images = ["examples/example_0.jpg",
+                    "examples/example_1.jpg",
+                    "examples/example_2.jpg",
+                    "examples/example_3.jpg",
+                    "examples/example_4.jpg",
+                    "examples/example_5.jpg",
+                    "examples/example_6.jpg",
+                    "examples/example_7.jpg"]
+    show_images = False
+    if st.button("Show/Hide Examples"):
+        show_images = not show_images
+        if show_images:
+            st.header("Example Images")
+            for image in images:
+                st.image(image, width=250)
+
+    uploaded_file = st.file_uploader("Upload Files",type=['png','jpeg','jpg'])
+
+    if uploaded_file!=None:
+        img=Image.open(uploaded_file)
+
+        extractor = AutoFeatureExtractor.from_pretrained("Kaludi/food-category-classification-v2.0")
+        model = AutoModelForImageClassification.from_pretrained("Kaludi/food-category-classification-v2.0")
+
+        inputs = extractor(img,return_tensors="pt")
+        outputs = model(**inputs)
+        label_num=outputs.logits.softmax(1).argmax(1)
+        label_num=label_num.item()
+
+        probs = outputs.logits.softmax(dim=1)
+        percentage = round(probs[0, label_num].item() * 100, 2)
+
+        st.write("The prediction class is:")
+
+        if label_num==0:
+            st.write("Bread (" + f"{percentage}%)")
+        elif label_num==1:
+            st.write("Dairy (" + f"{percentage}%)")
+        elif label_num==2:
+            st.write("Dessert (" + f"{percentage}%)")
+        elif label_num==3:
+            st.write("Egg (" + f"{percentage}%)")
+        elif label_num==4:
+            st.write("Fried Food (" + f"{percentage}%)")
+        elif label_num==5:
+            st.write("Fruit (" + f"{percentage}%)")
+        elif label_num==6:
+            st.write("Meat (" + f"{percentage}%)")
+        elif label_num==7:
+            st.write("Noodles (" + f"{percentage}%)")
+        elif label_num==8:
+            st.write("Rice (" + f"{percentage}%)")
+        elif label_num==9:
+            st.write("Seafood (" + f"{percentage}%)")
+        elif label_num==10:
+            st.write("Soup (" + f"{percentage}%)")
+        else:
+            st.write("Vegetable (" + f"{percentage}%)")
+
+    
+        select_health = st.selectbox("Select one:", ["Choose healthy or non-healthy", "Healthy", "Non-healthy"])
+        if select_health == "Healthy":
+            st.write("You selected healthy for", "Bread" if label_num==0 else "Dairy" if label_num==1 else "Dessert" if label_num==2 else "Egg" if label_num==3 else "Fried Food" if label_num==4 else "Fruit" if label_num==5 else "Meat" if label_num==6 else "Noodles" if label_num==7 else "Rice" if label_num==8 else "Seafood" if label_num==9 else "Soup" if label_num==10 else "Vegetable")
+            # Add code to fetch healthy recipe here
+        elif select_health == "Non-healthy":
+            st.write("You selected non-healthy for", "Bread" if label_num==0 else "Dairy" if label_num==1 else "Dessert" if label_num==2 else "Egg" if label_num==3 else "Fried Food" if label_num==4 else "Fruit" if label_num==5 else "Meat" if label_num==6 else "Noodles" if label_num==7 else "Rice" if label_num==8 else "Seafood" if label_num==9 else "Soup" if label_num==10 else "Vegetable")
+            # Add code to fetch unhealthy recipe here
+
+        st.image(img)
+
+if __name__ == '__main__':
+    main()

requirements.txt

@@ -0,0 +1,4 @@
+fastai==2.7.4
+huggingface_hub[fastai]
+fastcore>=1.3.27
+transformers