Update app.py

app.py

@@ -3,7 +3,6 @@ from transformers import pipeline
 from rembg import remove
 from PIL import Image
 from io import BytesIO
-import base64
 from transformers import GPT2LMHeadModel, GPT2Tokenizer
 import random
 
@@ -26,21 +25,33 @@ def convert_image(img):
 
 def fix_image(upload):
     image = Image.open(upload)
-    col1.write("Original Image :camera:")
-    col1.image(image)
+    st.image(image, caption="Original Image", use_column_width=True)
 
     fixed = remove(image)
-    col2.write("Fixed Image :wrench:")
-    col2.image(fixed)
+    st.image(fixed, caption="Fixed Image", use_column_width=True)
     st.sidebar.markdown("\n")
     st.sidebar.download_button("Download fixed image", convert_image(fixed), "fixed.png", "image/png")
 
 def generate_recipe(title, max_length=200):
-    matching_entries = [entry for entry in dataset if entry["title"] == title]
+    # Replace this with your actual dataset
+    dataset = {
+        "Gulab Jamun": {
+            "ingredients": ["milk powder", "ghee", "rose water", "saffron", "cardamom", "sugar syrup"],
+            "recipe": "Instructions for making Gulab Jamun...",
+        },
+        "Jalebi": {
+            "ingredients": ["all-purpose flour", "yogurt", "sugar", "water", "saffron strands", "cardamom powder", "ghee or oil for frying"],
+            "recipe": "Instructions for making Jalebi...",
+        },
+        "Rasgulla": {
+            "ingredients": ["milk", "sugar", "lemon juice", "rose water"],
+            "recipe": "Instructions for making Rasgulla...",
+        }
+    }
 
-    if matching_entries:
-        selected_entry = random.choice(matching_entries)
-        title = selected_entry["title"]
+    if title in dataset:
+        selected_entry = dataset[title]
+        title = title
         ingredients = selected_entry["ingredients"]
     else:
         title = "Default Recipe Title"
@@ -54,36 +65,10 @@ def generate_recipe(title, max_length=200):
     generated_recipe = recipe_tokenizer.decode(output[0], skip_special_tokens=True)
     return generated_recipe
 
-# Your dataset of titles, ingredients, and recipes
-dataset = [
-    {
-        "title": "Gulab Jamun",
-        "ingredients": ["milk powder", "ghee", "rose water", "saffron", "cardamom", "sugar syrup"],
-        "recipe": "Instructions for making Gulab Jamun..."
-    },
-    {
-        "title": "Jalebi",
-        "ingredients": ["all-purpose flour", "yogurt", "sugar", "water", "saffron strands", "cardamom powder", "ghee or oil for frying"],
-        "recipe": "Instructions for making Jalebi..."
-    },
-    {
-        "title": "Rasgulla",
-        "ingredients": ["milk", "sugar", "lemon juice", "rose water"],
-        "recipe": "Instructions for making Rasgulla..."
-    }
-]
-
 col1, col2 = st.columns(2)
 my_upload = st.sidebar.file_uploader("Upload an image", type=["png", "jpg", "jpeg"])
 
-st.write()
-st.markdown("""---""")
-st.write()
-
-# global label
-# label = ""
-
-if my_upload is not None:
+if my_upload:
     st.image(my_upload, caption="Uploaded Image", use_column_width=True)
 
     if st.sidebar.button("Classify"):
@@ -104,16 +89,12 @@ if my_upload is not None:
     if my_upload.size > MAX_FILE_SIZE:
         st.error("The uploaded file is too large. Please upload an image smaller than 5MB.")
     else:
-        fix_image(upload=my_upload)
-else:
-    fix_image("jalebi.jpg")
-
-
+        fix_image(my_upload)
 
 # Recipe generation based on selected item
 st.write("## Recipe Generation")
 
-selected_item = st.selectbox("Select a food item", [entry["title"] for entry in dataset])
+selected_item = st.selectbox("Select a food item", ["Gulab Jamun", "Jalebi", "Rasgulla"])
 if st.button("Generate Recipe"):
      generated_recipe = generate_recipe(selected_item, max_length=200)
      st.write(f"Recipe for {selected_item}:\n{generated_recipe}")
@@ -126,4 +107,5 @@ st.sidebar.markdown("3. Select a food item to generate a recipe.")
 st.sidebar.markdown("4. Click the 'Generate Recipe' button to get the recipe.")
 
 # Display a placeholder for the main content
-st.write("Please upload an image and use the sidebar to classify it and generate a recipe.")
+st.write("Please upload an image and use the sidebar to classify it and generate a recipe.")
+