52 lines
1.9 KiB
Python
52 lines
1.9 KiB
Python
import torch
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from PIL import Image
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import gradio as gr
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from lavis.models import load_model_and_preprocess
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from lavis.processors import load_processor
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from gradio.themes.utils import sizes
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theme = gr.themes.Default(radius_size=sizes.radius_none).set(
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block_label_text_color = '#4D63FF',
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block_title_text_color = '#4D63FF',
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button_primary_text_color = '#4D63FF',
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button_primary_background_fill='#FFFFFF',
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button_primary_border_color='#4D63FF',
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button_primary_background_fill_hover='#EDEFFF',
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)
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raw_image = Image.open("./merlion.png").convert("RGB")
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device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
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model, vis_processors, text_processors = load_model_and_preprocess("blip_image_text_matching", "large", device=device, is_eval=True)
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def image_text_match_compute(image, text):
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raw_image = Image.open(image).convert("RGB")
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img = vis_processors["eval"](raw_image).unsqueeze(0).to(device)
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txt = text_processors["eval"](text)
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itm_output = model({"image": img, "text_input": txt}, match_head="itm")
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itm_scores = torch.nn.functional.softmax(itm_output, dim=1)
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return f'The image and text are matched with a probability of {itm_scores[:, 1].item():.3%}'
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with gr.Blocks(theme=theme, css="footer {visibility: hidden}") as demo:
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gr.Markdown("""
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<div align='center' ><font size='60'>图片文本相似度计算</font></div>
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""")
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with gr.Row():
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with gr.Column():
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image = gr.Image(label="图片", type="filepath")
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text = gr.Textbox(label="问题")
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with gr.Row():
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button = gr.Button("提交", variant="primary")
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box2 = gr.Textbox(label="文本")
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button.click(fn=image_text_match_compute, inputs=[image, text], outputs=box2)
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examples = gr.Examples(examples=[['merlion.png', 'merlion in Singapore']], inputs=[image, text], label="例子")
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if __name__ == "__main__":
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demo.queue().launch(server_name = "0.0.0.0")
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