2023-03-29 08:59:06 +00:00
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import gradio as gr
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from transformers import AutoProcessor, AutoModelForCausalLM, AutoConfig
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def inference(img):
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pretrained_model_path = "git-large-coco"
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processor = AutoProcessor.from_pretrained(pretrained_model_path)
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model = AutoModelForCausalLM.from_pretrained(pretrained_model_path)
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pixel_values = processor(images=img, return_tensors="pt").pixel_values
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generated_ids = model.generate(pixel_values=pixel_values, max_length=50)
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generated_caption = processor.batch_decode(generated_ids, skip_special_tokens=True)[0]
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return generated_caption
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2023-03-30 03:33:11 +00:00
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title = "Image to text:git-large-coco"
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2023-03-29 08:59:06 +00:00
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article = "<p style='text-align: center'><a href='https://github.com/bryandlee/animegan2-pytorch' target='_blank'>Github Repo Pytorch</a></p> <center><img src='https://visitor-badge.glitch.me/badge?page_id=akhaliq_animegan' alt='visitor badge'></center></p>"
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examples=[['example_cat.jpg'],['Masahiro.png']]
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2023-04-06 05:10:02 +00:00
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with gr.Blocks() as demo:
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gr.Markdown(
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"""
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# Image to text:git-large-coco
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这是一个git-large-coco的Gradio Demo。 上传你想要的图像或者点击下面的示例来加载它。
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""")
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with gr.Row():
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text_input = gr.Image()
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text_output = gr.Textbox()
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image_button = gr.Button("上传")
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image_button.click(inference, inputs=text_input, outputs=text_output)
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gr.Examples(examples, inputs=text_input)
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2023-04-17 08:30:43 +00:00
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demo.launch(server_name="0.0.0.0")
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