Create app.py

app.py

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+import gradio as gr
+import requests
+import base64
+import os
+
+# argparse 的简单替代，如有需要可替换为 argparse
+from argparse import Namespace
+
+# 假设 libra_eval 在你的 python 包 libra.eval 中
+from libra.eval import libra_eval
+
+# 预定义图像及其链接（或者本地路径）
+DEFAULT_IMAGES = {
+    "Image 1": "https://drive.google.com/uc?export=view&id=10bvR7a4WSyDAtWsNQUjPSs1GlcSxtP81",
+    "Image 2": "https://drive.google.com/uc?export=view&id=1yzKM1eo8yBAGRcm7ayqUhxASXQHNANUa"
+}
+
+###############################################################################
+# 如果需要直接使用本地文件，可将以上链接替换为本地路径，比如：
+# DEFAULT_IMAGES = {
+#     "Image 1": "/path/to/local/file1.jpg",
+#     "Image 2": "/path/to/local/file2.jpg"
+# }
+###############################################################################
+
+def image_url_to_base64(image_url: str) -> str:
+    """
+    将远程图片 URL 转换为 Base64 数据 URI。
+    如果请求失败，则返回提示文本。
+    """
+    try:
+        response = requests.get(image_url)
+        response.raise_for_status()
+        base64_image = base64.b64encode(response.content).decode("utf-8")
+        return f"data:image/jpeg;base64,{base64_image}"
+    except Exception as e:
+        return f"<p style='color: red;'>Failed to load image: {e}</p>"
+
+def generate_image_html(image_url: str) -> str:
+    """
+    生成一个 <img> 标签的 HTML，用于在 Gradio 中以预览形式显示图片。
+    如果是 http(s) 链接，则尝试转换为 Base64；如果是本地路径，直接使用 file://。
+    """
+    # 判断是否以 http(s) 开头
+    if image_url.startswith("http"):
+        base64_image = image_url_to_base64(image_url)
+        return f'<img src="{base64_image}" style="width: 200px; height: auto; display: inline-block; margin: 10px; border-radius: 10px;" />'
+    else:
+        # 直接使用本地路径
+        return f'<img src="file://{image_url}" style="width: 200px; height: auto; display: inline-block; margin: 10px; border-radius: 10px;" />'
+
+def generate_radiology_description(
+    prompt: str,
+    selected_current: str,
+    uploaded_current: str,
+    selected_prior: str,
+    uploaded_prior: str,
+    temperature: float,
+    top_p: float,
+    num_beams: int,
+    max_new_tokens: int
+) -> str:
+    """
+    核心推理函数：
+    1. 获取用户输入或默认图片
+    2. 调用 libra_eval 来生成报告描述
+    3. 返回生成的结果或错误消息
+    """
+    # 如果用户上传了图片，则优先使用上传的图片；否则使用默认图片
+    current_image = uploaded_current if uploaded_current else DEFAULT_IMAGES.get(selected_current)
+    prior_image = uploaded_prior if uploaded_prior else DEFAULT_IMAGES.get(selected_prior)
+
+    # 确保用户选择或上传了两张图片
+    if not current_image or not prior_image:
+        return "Please select or upload both current and prior images."
+
+    # 模型路径（示例）
+    model_path = "/nfs/LLaVA-ai4bio/gla-biomed-playground/final_model/finetuned_model/llava-libra-test"
+    conv_mode = "libra_v1"
+
+    try:
+        # 调用 libra_eval 进行推理
+        output = libra_eval(
+            model_path=model_path,
+            model_base=None,
+            image_file=[current_image, prior_image],
+            query=prompt,
+            temperature=temperature,
+            top_p=top_p,
+            num_beams=num_beams,
+            length_penalty=1.0,
+            num_return_sequences=1,
+            conv_mode=conv_mode,
+            max_new_tokens=max_new_tokens
+        )
+        return output
+    except Exception as e:
+        return f"An error occurred: {str(e)}"
+
+# 在 Gradio 中构建 UI
+# Blocks 为最新的容器API，可以更好地对布局进行控制
+with gr.Blocks() as demo:
+    # 标题和简单说明
+    gr.Markdown("# Libra Radiology Report Generator")
+    gr.Markdown("Use **Libra** to generate radiology image descriptions. Provide a **Current** and a **Prior** image below.")
+
+    # 用户输入的文本
+    with gr.Row():
+        prompt_input = gr.Textbox(
+            label="Prompt", 
+            value="Provide a detailed description of the findings in the radiology image."
+        )
+
+    # 当前图像（Current Image）和历史对比图像（Prior Image）
+    with gr.Row():
+        with gr.Column():
+            gr.Markdown("### Current Image")
+            # 预览默认图像
+            for img in DEFAULT_IMAGES.values():
+                gr.HTML(generate_image_html(img))
+            # 在Radio中选择
+            selected_current = gr.Radio(
+                label="Select Current Image", 
+                choices=list(DEFAULT_IMAGES.keys()), 
+                value="Image 1"
+            )
+            # 或者上传一张新的
+            uploaded_current = gr.Image(
+                label="Or Upload Current Image", 
+                type="filepath", 
+                tool="editor"
+            )
+
+        with gr.Column():
+            gr.Markdown("### Prior Image")
+            # 同样显示默认图像
+            for img in DEFAULT_IMAGES.values():
+                gr.HTML(generate_image_html(img))
+            selected_prior = gr.Radio(
+                label="Select Prior Image", 
+                choices=list(DEFAULT_IMAGES.keys()), 
+                value="Image 2"
+            )
+            uploaded_prior = gr.Image(
+                label="Or Upload Prior Image", 
+                type="filepath", 
+                tool="editor"
+            )
+
+    # 一些可调参数
+    with gr.Row():
+        temperature_slider = gr.Slider(
+            label="Temperature", 
+            minimum=0.1, 
+            maximum=1.0, 
+            step=0.1, 
+            value=0.7
+        )
+        top_p_slider = gr.Slider(
+            label="Top P", 
+            minimum=0.1, 
+            maximum=1.0, 
+            step=0.1, 
+            value=0.8
+        )
+        num_beams_slider = gr.Slider(
+            label="Number of Beams", 
+            minimum=1, 
+            maximum=20, 
+            step=1, 
+            value=2
+        )
+        max_tokens_slider = gr.Slider(
+            label="Max New Tokens", 
+            minimum=10, 
+            maximum=4096, 
+            step=10, 
+            value=128
+        )
+
+    # 用于显示模型生成的结果
+    output_text = gr.Textbox(
+        label="Generated Description",
+        lines=10
+    )
+
+    # 点击按钮时触发的推理逻辑
+    generate_button = gr.Button("Generate Description")
+    generate_button.click(
+        fn=generate_radiology_description,
+        inputs=[
+            prompt_input, 
+            selected_current, 
+            uploaded_current,
+            selected_prior, 
+            uploaded_prior,
+            temperature_slider, 
+            top_p_slider, 
+            num_beams_slider, 
+            max_tokens_slider
+        ],
+        outputs=output_text
+    )
+
+# 启动 Gradio 应用（将 share 设置为 True 以便在 Hugging Face Spaces 中分享）
+if __name__ == "__main__":
+    demo.launch(share=True)