Update app.py

app.py

@@ -1,10 +1,6 @@
 import gradio as gr
 import torch
-import time
 import spaces
-from typing import Iterable
-from gradio.themes.base import Base
-from gradio.themes.utils import colors, fonts, sizes
 from transformers import AutoModel, AutoProcessor
 
 from gender_classification import gender_classification
@@ -21,46 +17,7 @@ from bird_species import bird_classification
 from alphabet_sign_language_detection import sign_language_classification
 from rice_leaf_disease import classify_leaf_disease
 from traffic_density import traffic_density_classification
-from clip_art import clipart_classification  # New import
-
-#Gradio-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.gray,
-        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,
-        )
-
-seafoam = Seafoam()
+from clip_art import clipart_classification
 
 # Main classification function for multi-model classification.
 def classify(image, model_name):