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import torch
from transformers import AutoModel, AutoProcessor
import gradio as gr
from PIL import Image
import requests
from typing import Iterable
from gradio.themes import Soft
from gradio.themes.utils import colors, fonts, sizes
colors.orange_red = colors.Color(
name="orange_red",
c50="#FFF0E5",
c100="#FFE0CC",
c200="#FFC299",
c300="#FFA366",
c400="#FF8533",
c500="#FF4500",
c600="#E63E00",
c700="#CC3700",
c800="#B33000",
c900="#992900",
c950="#802200",
)
class OrangeRedTheme(Soft):
def __init__(
self,
*,
primary_hue: colors.Color | str = colors.gray,
secondary_hue: colors.Color | str = colors.orange_red, # Use the new color
neutral_hue: colors.Color | str = colors.slate,
text_size: sizes.Size | str = sizes.text_lg,
font: fonts.Font | str | Iterable[fonts.Font | str] = (
fonts.GoogleFont("Outfit"), "Arial", "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,
text_size=text_size,
font=font,
font_mono=font_mono,
)
super().set(
background_fill_primary="*primary_50",
background_fill_primary_dark="*primary_900",
body_background_fill="linear-gradient(135deg, *primary_200, *primary_100)",
body_background_fill_dark="linear-gradient(135deg, *primary_900, *primary_800)",
button_primary_text_color="white",
button_primary_text_color_hover="white",
button_primary_background_fill="linear-gradient(90deg, *secondary_500, *secondary_600)",
button_primary_background_fill_hover="linear-gradient(90deg, *secondary_600, *secondary_700)",
button_primary_background_fill_dark="linear-gradient(90deg, *secondary_600, *secondary_700)",
button_primary_background_fill_hover_dark="linear-gradient(90deg, *secondary_500, *secondary_600)",
button_secondary_text_color="black",
button_secondary_text_color_hover="white",
button_secondary_background_fill="linear-gradient(90deg, *primary_300, *primary_300)",
button_secondary_background_fill_hover="linear-gradient(90deg, *primary_400, *primary_400)",
button_secondary_background_fill_dark="linear-gradient(90deg, *primary_500, *primary_600)",
button_secondary_background_fill_hover_dark="linear-gradient(90deg, *primary_500, *primary_500)",
slider_color="*secondary_500",
slider_color_dark="*secondary_600",
block_title_text_weight="600",
block_border_width="3px",
block_shadow="*shadow_drop_lg",
button_primary_shadow="*shadow_drop_lg",
button_large_padding="11px",
color_accent_soft="*primary_100",
block_label_background_fill="*primary_200",
)
orange_red_theme = OrangeRedTheme()
model = AutoModel.from_pretrained("facebook/metaclip-2-mt5-worldwide-s16", torch_dtype=torch.bfloat16, attn_implementation="sdpa")
processor = AutoProcessor.from_pretrained("facebook/metaclip-2-mt5-worldwide-s16")
def postprocess_metaclip(probs, labels):
output = {labels[i]: probs[0][i].item() for i in range(len(labels))}
return output
def metaclip_detector(image, texts):
inputs = processor(text=texts, images=image, return_tensors="pt", padding=True)
with torch.no_grad():
outputs = model(**inputs)
logits_per_image = outputs.logits_per_image
probs = logits_per_image.softmax(dim=1)
return probs
def infer(image, candidate_labels):
candidate_labels = [label.lstrip(" ") for label in candidate_labels.split(",")]
probs = metaclip_detector(image, candidate_labels)
return postprocess_metaclip(probs, labels=candidate_labels)
with gr.Blocks(theme=orange_red_theme) as demo:
gr.Markdown("# **MetaCLIP 2 Zero-Shot Classification**")
gr.Markdown(
"Test the performance of MetaCLIP 2 on zero-shot classification in this Space"
)
with gr.Row():
with gr.Column():
image_input = gr.Image(type="pil")
text_input = gr.Textbox(label="Input a list of labels (comma seperated)")
run_button = gr.Button("Run", visible=True)
with gr.Column():
metaclip_output = gr.Label(label="MetaCLIP 2 Output", num_top_classes=3)
examples = [
["./baklava.jpg", "dessert on a plate, a serving of baklava, a plate and spoon"],
["./cat.jpg", "a cat, two cats, three cats"],
["./cat.jpg", "two sleeping cats, two cats playing, three cats laying down"],
]
gr.Examples(
examples=examples,
inputs=[image_input, text_input],
outputs=[metaclip_output],
fn=infer,
)
run_button.click(fn=infer, inputs=[image_input, text_input], outputs=[metaclip_output])
demo.launch() |