Spaces:
Running
on
Zero
Running
on
Zero
Update app.py
Browse files
app.py
CHANGED
@@ -27,16 +27,16 @@ from painting_126 import painting_classification
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from sketch_126 import sketch_classification # New import
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#Gradio-Theme
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-
class
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def __init__(
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self,
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*,
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primary_hue: colors.Color | str = colors.sky,
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secondary_hue: colors.Color | str = colors.
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neutral_hue: colors.Color | str = colors.indigo,
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spacing_size: sizes.Size | str = sizes.
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radius_size: sizes.Size | str = sizes.
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text_size: sizes.Size | str = sizes.
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font: fonts.Font | str | Iterable[fonts.Font | str] = (
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fonts.GoogleFont("Inter"),
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"ui-sans-serif",
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@@ -59,13 +59,12 @@ class MinimalModern(Base):
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font_mono=font_mono,
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)
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super().set(
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button_primary_background_fill_hover="*secondary_100",
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button_primary_text_color="white",
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button_primary_background_fill_dark="*secondary_500",
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slider_color="*secondary_200",
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slider_color_dark="*secondary_500",
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block_title_text_weight="400",
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@@ -75,7 +74,8 @@ class MinimalModern(Base):
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button_large_padding="24px",
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)
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-
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# Main classification function for multi-model classification.
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def classify(image, model_name):
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@@ -167,7 +167,7 @@ def infer(image, candidate_labels):
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return postprocess_siglip(sg1_probs, sg2_probs, labels=candidate_labels)
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# Build the Gradio Interface with two tabs.
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with gr.Blocks(theme=
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gr.Markdown("# Multi-Domain & Zero-Shot Image Classification")
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with gr.Tabs():
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from sketch_126 import sketch_classification # New import
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#Gradio-Theme
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class MinimalMinimal(Base):
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def __init__(
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self,
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*,
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primary_hue: colors.Color | str = colors.sky,
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secondary_hue: colors.Color | str = colors.lavender,
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neutral_hue: colors.Color | str = colors.indigo,
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spacing_size: sizes.Size | str = sizes.spacing_sm,
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radius_size: sizes.Size | str = sizes.radius_sm,
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text_size: sizes.Size | str = sizes.text_md,
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font: fonts.Font | str | Iterable[fonts.Font | str] = (
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fonts.GoogleFont("Inter"),
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"ui-sans-serif",
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font_mono=font_mono,
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)
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super().set(
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body_background_fill="linear-gradient(135deg, *primary_100, *secondary_100)",
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body_background_fill_dark="linear-gradient(135deg, *primary_700, *secondary_700)",
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button_primary_background_fill="linear-gradient(90deg, *primary_200, *secondary_200)",
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button_primary_background_fill_hover="linear-gradient(90deg, *primary_100, *secondary_100)",
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button_primary_text_color="white",
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button_primary_background_fill_dark="linear-gradient(90deg, *primary_500, *secondary_500)",
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slider_color="*secondary_200",
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slider_color_dark="*secondary_500",
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block_title_text_weight="400",
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button_large_padding="24px",
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)
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minimal_minimal = MinimalMinimal()
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# Main classification function for multi-model classification.
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def classify(image, model_name):
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return postprocess_siglip(sg1_probs, sg2_probs, labels=candidate_labels)
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# Build the Gradio Interface with two tabs.
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with gr.Blocks(theme=minimal_minimal) as demo:
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gr.Markdown("# Multi-Domain & Zero-Shot Image Classification")
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with gr.Tabs():
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