Upload app.py

app.py

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+import streamlit as st
+
+import tensorflow as tf
+from PIL import Image
+import img_classification
+import numpy as np
+st.set_page_config(page_title="Food Vision",
+                   page_icon="🍔")
+
+st.title("Food Vision 🍔📷")
+st.header("Identify what's in your food photos!")
+
+st.sidebar.title("What actually is this?")
+st.sidebar.write("""
+FoodVision is an end-to-end **CNN Image Classification Model** which identifies the food in your image. 
+It can identify over 100 different food classes
+
+And also this model is trained using Transfer Learning (Efficientnet-B0)
+""")
+st.sidebar.markdown("Created by **Sravanth**")
+uploaded_file = st.file_uploader("Upload a food image", type=["jpeg","jpg","png"])
+if uploaded_file is not None:
+    img = uploaded_file.read()
+    st.image(img, caption='Uploaded Image.', use_column_width=True)
+    st.write("")
+    #img = tf.io.read_file(uploaded_file)
+    img = tf.io.decode_image(img, channels=3)
+    img = tf.image.resize(img, [224, 224])
+    st.write("Classifying...")
+    label = img_classification.classify(img)
+    label = label.capitalize()
+    st.success(f'Prediction : {label}\n')
+
+