Update app.py

app.py

@@ -1,74 +1,89 @@
 from fastai.vision.all import load_learner
 import gradio as gr
-
-#import pathlib
-#temp=pathlib.PosixPath
-#pathlib.PosixPath=pathlib.WindowsPath
-# Custom Seafoam theme
 from gradio.themes.base import Base
 from gradio.themes.utils import colors, fonts, sizes
 
+# Custom Seafoam theme
+class Seafoam(Base):
+    def __init__(
+        self,
+        *,
+        primary_hue: colors.Color | str = colors.emerald,
+        secondary_hue: colors.Color | str = colors.blue,
+        neutral_hue: colors.Color | str = colors.blue,
+        spacing_size: sizes.Size | str = sizes.spacing_md,
+        radius_size: sizes.Size | str = sizes.radius_md,
+        text_size: sizes.Size | str = sizes.text_lg,
+        font: fonts.Font | str | Iterable[fonts.Font | str] = (
+            fonts.GoogleFont("Quicksand"),
+            "ui-sans-serif",
+            "sans-serif",
+        ),
+        font_mono: fonts.Font | str | Iterable[fonts.Font | str] = (
+            fonts.GoogleFont("IBM Plex Mono"),
+            "ui-monospace",
+            "monospace",
+        ),
+    ):
+        super().__init__(
+            primary_hue=primary_hue,
+            secondary_hue=secondary_hue,
+            neutral_hue=neutral_hue,
+            spacing_size=spacing_size,
+            radius_size=radius_size,
+            text_size=text_size,
+            font=font,
+            font_mono=font_mono,
+        )
+        super().set(
+            body_background_fill="repeating-linear-gradient(45deg, *primary_200, *primary_200 10px, *primary_50 10px, *primary_50 20px)",
+            body_background_fill_dark="repeating-linear-gradient(45deg, *primary_800, *primary_800 10px, *primary_900 10px, *primary_900 20px)",
+            button_primary_background_fill="linear-gradient(90deg, *primary_300, *secondary_400)",
+            button_primary_background_fill_hover="linear-gradient(90deg, *primary_200, *secondary_300)",
+            button_primary_text_color="white",
+            button_primary_background_fill_dark="linear-gradient(90deg, *primary_600, *secondary_800)",
+            slider_color="*secondary_300",
+            slider_color_dark="*secondary_600",
+            block_title_text_weight="600",
+            block_border_width="3px",
+            block_shadow="*shadow_drop_lg",
+            button_shadow="*shadow_drop_lg",
+            button_large_padding="32px",
+        )
 
+seafoam = Seafoam()
 
-
+# Food labels
 food_labels = [
-    'Baked Potato',
-    'Crispy Chicken',
-    'Donut',
-    'Fries',
-    'Hot Dog',
-    'Sandwich',
-    'Taco',
-    'Taquito',
-    'Apple Pie',
-    'Burger',
-    'Butter Naan',
-    'Chai',
-    'Chapati',
-    'Cheesecake',
-    'Chicken Curry',
-    'Chole Bhature',
-    'Dal Makhani',
-    'Dhokla',
-    'Fried Rice',
-    'Ice Cream',
-    'Idli',
-    'Jalebi',
-    'Kaathi Rolls',
-    'Kadai Paneer',
-    'Kulfi',
-    'Masala Dosa',
-    'Momos',
-    'Omelette',
-    'Paani Puri',
-    'Pakode',
-    'Pancakes',
-    'Quesadilla',
-    'Ratatouille',
-    'Samosa',
-    'Spring Rolls',
-    'Stuffed Bell Peppers',
-    'Tandoori Chicken',
-    'Uttapam',
-    'Veggie Burger',
-    'Waffles',
-    'Zucchini Bread']
+    'Baked Potato', 'Crispy Chicken', 'Donut', 'Fries', 'Hot Dog', 'Sandwich', 'Taco', 'Taquito',
+    'Apple Pie', 'Burger', 'Butter Naan', 'Chai', 'Chapati', 'Cheesecake', 'Chicken Curry',
+    'Chole Bhature', 'Dal Makhani', 'Dhokla', 'Fried Rice', 'Ice Cream', 'Idli', 'Jalebi', 
+    'Kaathi Rolls', 'Kadai Paneer', 'Kulfi', 'Masala Dosa', 'Momos', 'Omelette', 'Paani Puri', 
+    'Pakode', 'Pancakes', 'Quesadilla', 'Ratatouille', 'Samosa', 'Spring Rolls', 'Stuffed Bell Peppers',
+    'Tandoori Chicken', 'Uttapam', 'Veggie Burger', 'Waffles', 'Zucchini Bread'
+]
 
-model=load_learner("food_model_v2.pkl")
+# Load model
+model = load_learner("food_model_v2.pkl")
 
+# Prediction function
 def recognize_image(image):
-  #import pdb;pdb.set_trace()
-  pred,idx,probs=model.predict(image)
-  print(pred)
-  return dict(zip(food_labels, map(float,probs)))
+    pred, idx, probs = model.predict(image)
+    return dict(zip(food_labels, map(float, probs)))
 
+# Gradio interface
 image = gr.Image()
 label = gr.Label()
-examples = [
-   "food1.jpg",
-   "food2.jpg",
-   "food3.jpg",
-   "food4.jpg"]
+examples = ["food1.jpg", "food2.jpg", "food3.jpg", "food4.jpg"]
+
+# Interface with Seafoam theme
+iface = gr.Interface(
+    fn=recognize_image,
+    inputs=image,
+    outputs=label,
+    examples=examples,
+    theme=seafoam  # Apply Seafoam theme here
+)
 
-iface = gr.Interface(fn=recognize_image, inputs=image, outputs=label,examples=examples)
-iface.launch(inline=False,share=True)
+# Launch the app
+iface.launch(inline=False, share=True)