Update app.py

app.py

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+import base64
+import io
+import json
+import os
+from typing import Dict, List, Tuple, Any, Optional
+import time
+import requests
+from PIL import Image
+import gradio as gr
+import re
+import tempfile
+from urllib.parse import urlparse
+
+# =========================
+# Config
+# =========================
+DEFAULT_API_URL = os.environ.get("API_URL")
+TOKEN = os.environ.get("TOKEN")
+LOGO_IMAGE_PATH = "./assets/logo.jpg"
+GOOGLE_FONTS_URL = "<link href='https://fonts.googleapis.com/css2?family=Noto+Sans+SC:wght@400;700&display=swap' rel='stylesheet'>"
+LATEX_DELIMS = [
+    {"left": "$$", "right": "$$", "display": True},
+    {"left": "$",  "right": "$",  "display": False},
+    {"left": "\\(", "right": "\\)", "display": False},
+    {"left": "\\[", "right": "\\]", "display": True},
+]
+AUTH_HEADER = {"Authorization": f"bearer {TOKEN}"} if TOKEN else {}
+JSON_HEADERS = {**AUTH_HEADER, "Content-Type": "application/json"} if AUTH_HEADER else {"Content-Type": "application/json"}
+JSON_HEADERS["Client-Platform"] = "huggingface-demo"
+
+# =========================
+# Base64 & Examples (URL直链渲染)
+# =========================
+def image_to_base64_data_url(filepath: str) -> str:
+    """仅用于本地上传预览的兼容方案；URL 预览不会用到它。"""
+    try:
+        ext = os.path.splitext(filepath)[1].lower()
+        mime_types = {".jpg": "image/jpeg", ".jpeg": "image/jpeg", ".png": "image/png", ".gif": "image/gif", ".webp": "image/webp", ".bmp": "image/bmp"}
+        mime_type = mime_types.get(ext, "image/jpeg")
+        with open(filepath, "rb") as image_file:
+            encoded_string = base64.b64encode(image_file.read()).decode("utf-8")
+        return f"data:{mime_type};base64,{encoded_string}"
+    except Exception as e:
+        print(f"Error encoding image to Base64: {e}")
+        return ""
+
+def _escape_inequalities_in_math(md: str) -> str:
+    """把数学块中的 < > 替换为 \\lt \\gt，避免被 Markdown 误解析。"""
+    _MATH_PATTERNS = [
+        re.compile(r"\$\$([\s\S]+?)\$\$"),
+        re.compile(r"\$([^\$]+?)\$"),
+        re.compile(r"\\\[([\s\S]+?)\\\]"),
+        re.compile(r"\\\(([\s\S]+?)\\\)"),
+    ]
+
+    def fix(s: str) -> str:
+        s = s.replace("<=", r" \le ").replace(">=", r" \ge ")
+        s = s.replace("≤", r" \le ").replace("≥", r" \ge ")
+        s = s.replace("<", r" \lt ").replace(">", r" \gt ")
+        return s
+
+    for pat in _MATH_PATTERNS:
+        md = pat.sub(lambda m: m.group(0).replace(m.group(1), fix(m.group(1))), md)
+    return md
+
+def _get_examples_from_dir(dir_path: str) -> List[List[str]]:
+    """
+    从本地目录读取文件名，拼出远程直链 URL（不下载、不转码），用于 <img src="URL"> 直接渲染。
+    你原来使用的 BOS 基础路径保留。
+    """
+    BASE_URL = "https://paddle-model-ecology.bj.bcebos.com/PPOCRVL/dataset/examples"
+    supported_exts = {".png", ".jpg", ".jpeg", ".bmp", ".webp"}
+    examples = []
+    if not os.path.exists(dir_path):
+        print(f"Warning: example dir {dir_path} not found.")
+        return []
+    for filename in sorted(os.listdir(dir_path)):
+        ext = os.path.splitext(filename)[1].lower()
+        if ext in supported_exts:
+            subdir = os.path.basename(dir_path.rstrip("/"))
+            img_url = f"{BASE_URL}/{subdir}/{filename}"
+            examples.append([img_url])
+    return examples
+
+def _on_gallery_select(example_paths: List[str], evt: gr.SelectData):
+    """
+    与原版不同：直接返回 URL，不再下载到本地临时文件。
+    """
+    idx = evt.index
+    selected = example_paths[idx]
+    if isinstance(selected, list):
+        selected = selected[0]
+    return selected  # 直接是 https://... URL
+
+TARGETED_EXAMPLES_DIR = "examples/targeted"
+COMPLEX_EXAMPLES_DIR = "examples/complex"
+targeted_recognition_examples = _get_examples_from_dir(TARGETED_EXAMPLES_DIR)
+complex_document_examples = _get_examples_from_dir(COMPLEX_EXAMPLES_DIR)
+
+# =========================
+# UI Helpers（URL直链渲染）
+# =========================
+def render_uploaded_image_div(path_or_url: str) -> str:
+    """
+    支持两种输入：
+    - 远程 URL：直接用 <img src="URL"> 渲染
+    - 本地文件：为兼容旧逻辑，依然转 data: URL 预览（也可以改为 File 组件，这里先保持一致）
+    """
+    if not path_or_url:
+        return ""
+    is_url = isinstance(path_or_url, str) and path_or_url.startswith(("http://", "https://"))
+    if is_url:
+        src = path_or_url  # 直接远程URL
+    else:
+        src = image_to_base64_data_url(path_or_url)  # 本地上传时的兼容
+    return f"""
+    <div class="uploaded-image">
+        <img src="{src}" alt="Preview image" style="width:100%;height:100%;object-fit:contain;" loading="lazy"/>
+    </div>
+    """
+
+def update_preview_visibility(path_or_url: Optional[str]) -> Dict:
+    if path_or_url:
+        html_content = render_uploaded_image_div(path_or_url)
+        return gr.update(value=html_content, visible=True)
+    else:
+        return gr.update(value="", visible=False)
+
+# =========================
+# API 调用逻辑（支持URL或本地文件）
+# =========================
+def _file_to_b64_image_only(path_or_url: str) -> Tuple[str, int]:
+    """
+    输入可以是本地文件路径或远程URL。
+    - URL：仅在发请求给后端时下载字节转Base64（不影响前端渲染）。
+    - 本地：读取文件字节。
+    """
+    if not path_or_url:
+        raise ValueError("Please upload an image first.")
+
+    is_url = isinstance(path_or_url, str) and path_or_url.startswith(("http://", "https://"))
+    content: bytes
+    if is_url:
+        r = requests.get(path_or_url, timeout=600)
+        r.raise_for_status()
+        content = r.content
+        ext = os.path.splitext(urlparse(path_or_url).path)[1].lower()
+    else:
+        ext = os.path.splitext(path_or_url)[1].lower()
+        with open(path_or_url, "rb") as f:
+            content = f.read()
+
+    # 放宽后缀限制：有些URL可能没有后缀，这里仅在极端情况下提示
+    supported = {".png", ".jpg", ".jpeg", ".bmp", ".webp"}
+    if ext and (ext not in supported):
+        print(f"Warning: file extension {ext} not in supported set {supported}, continue anyway.")
+
+    return base64.b64encode(content).decode("utf-8"), 1  # 1 = image 类型
+
+def _call_api(api_url: str, path_or_url: str, use_layout_detection: bool,
+              prompt_label: Optional[str], use_chart_recognition: bool = False,
+              use_doc_unwarping: bool = True, use_doc_orientation_classify: bool = True) -> Dict[str, Any]:
+    b64, file_type = _file_to_b64_image_only(path_or_url)
+    payload = {
+        "file": b64,
+        "useLayoutDetection": bool(use_layout_detection),
+        "fileType": file_type,
+        "useDocUnwarping": use_doc_unwarping,
+        "useDocOrientationClassify": use_doc_orientation_classify
+    }
+    if not use_layout_detection:
+        if not prompt_label:
+            raise ValueError("Please select a recognition type.")
+        payload["promptLabel"] = prompt_label.strip().lower()
+    if use_layout_detection and use_chart_recognition:
+        payload["useChartRecognition"] = True
+
+    try:
+        print(f"Sending API request to {api_url}...")
+        start_time = time.time()
+        resp = requests.post(api_url, json=payload, headers=JSON_HEADERS, timeout=600)
+        end_time = time.time()
+        print(f"Received API response in {end_time - start_time:.2f} seconds.")
+        resp.raise_for_status()
+        data = resp.json()
+    except requests.exceptions.RequestException as e:
+        raise gr.Error(f"API request failed: {e}")
+    except json.JSONDecodeError:
+        raise gr.Error(f"Invalid JSON response from server:\n{getattr(resp, 'text', '')}")
+
+    if data.get("errorCode", -1) != 0:
+        raise gr.Error("API returned an error:")
+    return data
+
+def _process_api_response_page(result: Dict[str, Any]) -> Tuple[str, str, str]:
+    """
+    处理后端返回结果：
+    1) 把 markdown 里的占位图路径替换为真实URL
+    2) 构造一个可视化<img>（如果有）
+    """
+    layout_results = (result or {}).get("layoutParsingResults", [])
+    if not layout_results:
+        return "No content was recognized.", "<p>No visualization available.</p>", ""
+
+    page0 = layout_results[0] or {}
+    md_data = page0.get("markdown") or {}
+    md_text = md_data.get("text", "") or ""
+    md_images_map = md_data.get("images", {})
+
+    if md_images_map:
+        for placeholder_path, image_url in md_images_map.items():
+            md_text = md_text.replace(f'src="{placeholder_path}"', f'src="{image_url}"') \
+                             .replace(f']({placeholder_path})', f']({image_url})')
+
+    output_html = "<p style='text-align:center; color:#888;'>No visualization image available.</p>"
+    out_imgs = page0.get("outputImages") or {}
+    sorted_urls = [img_url for _, img_url in sorted(out_imgs.items()) if img_url]
+
+    output_image_url: Optional[str] = None
+    if len(sorted_urls) >= 2:
+        output_image_url = sorted_urls[1]
+    elif sorted_urls:
+        output_image_url = sorted_urls[0]
+
+    if output_image_url:
+        print(f"Found visualization image URL: {output_image_url}")
+        output_html = f'<img src="{output_image_url}" alt="Detection Visualization" loading="lazy">'
+
+    md_text = _escape_inequalities_in_math(md_text)
+    return md_text or "(Empty result)", output_html, md_text
+
+def handle_complex_doc(path_or_url: str, use_chart_recognition: bool, use_doc_unwarping: bool, use_doc_orientation_classify: bool) -> Tuple[str, str, str]:
+    if not path_or_url:
+        raise gr.Error("Please upload an image first.")
+    data = _call_api(DEFAULT_API_URL, path_or_url, use_layout_detection=True,
+                     prompt_label=None, use_chart_recognition=use_chart_recognition,
+                     use_doc_unwarping=use_doc_unwarping, use_doc_orientation_classify=use_doc_orientation_classify)
+    result = data.get("result", {})
+    return _process_api_response_page(result)
+
+def handle_targeted_recognition(path_or_url: str, prompt_choice: str) -> Tuple[str, str]:
+    if not path_or_url:
+        raise gr.Error("Please upload an image first.")
+    mapping = {
+        "Text Recognition": "ocr",
+        "Formula Recognition": "formula",
+        "Table Recognition": "table",
+        "Chart Recognition": "chart",
+    }
+    label = mapping.get(prompt_choice, "ocr")
+    data = _call_api(DEFAULT_API_URL, path_or_url, use_layout_detection=False, prompt_label=label, use_doc_unwarping=False, use_doc_orientation_classify=False)
+    result = data.get("result", {})
+    md_preview, _, md_raw = _process_api_response_page(result)
+    return md_preview, md_raw
+
+# =========================
+# CSS & UI
+# =========================
+custom_css = """
+body, .gradio-container { font-family: "Noto Sans SC", "Microsoft YaHei", "PingFang SC", sans-serif; }
+.app-header { text-align: center; max-width: 900px; margin: 0 auto 8px !important; }
+.gradio-container { padding: 4px 0 !important; }
+.gradio-container [data-testid="tabs"], .gradio-container .tabs { margin-top: 0 !important; }
+.gradio-container [data-testid="tabitem"], .gradio-container .tabitem { padding-top: 4px !important; }
+.quick-links { text-align: center; padding: 8px 0; border: 1px solid #e5e7eb; border-radius: 8px; margin: 8px auto; max-width: 900px; }
+.quick-links a { margin: 0 12px; font-size: 14px; font-weight: 600; color: #3b82f6; text-decoration: none; }
+.quick-links a:hover { text-decoration: underline; }
+.prompt-grid { display: flex; flex-wrap: wrap; gap: 8px; margin-top: 6px; }
+.prompt-grid button { height: 40px !important; padding: 0 12px !important; border-radius: 8px !important; font-weight: 600 !important; font-size: 13px !important; letter-spacing: 0.2px; }
+#image_preview_vl, #image_preview_doc { height: 400px !important; overflow: auto; }
+#image_preview_vl img, #image_preview_doc img, #vis_image_doc img { width: 100% !important; height: auto !important; object-fit: contain !important; display: block; }
+#md_preview_vl, #md_preview_doc { max-height: 540px; min-height: 180px; overflow: auto; scrollbar-gutter: stable both-edges; }
+#md_preview_vl .prose, #md_preview_doc .prose { line-height: 1.7 !important; }
+#md_preview_vl .prose img, #md_preview_doc .prose img { display: block; margin: 0 auto; max-width: 100%; height: auto; }
+.notice { margin: 8px auto 0; max-width: 900px; padding: 10px 12px; border: 1px solid #e5e7eb; border-radius: 8px; background: #f8fafc; font-size: 14px; line-height: 1.6; }
+.notice strong { font-weight: 700; }
+.notice a { color: #3b82f6; text-decoration: none; }
+.notice a:hover { text-decoration: underline; }
+.checkbox-row .gradio-checkbox { flex-grow: 1; text-align: center; }
+"""
+
+with gr.Blocks(head=GOOGLE_FONTS_URL, css=custom_css, theme=gr.themes.Soft()) as demo:
+    logo_data_url = image_to_base64_data_url(LOGO_IMAGE_PATH) if os.path.exists(LOGO_IMAGE_PATH) else ""
+    gr.HTML(f"""<div class="app-header"><img src="{logo_data_url}" alt="App Logo" style="max-height:10%; width: auto; margin: 10px auto; display: block;"></div>""")
+    gr.HTML("""<div class="notice"><strong>Heads up:</strong> The Hugging Face demo can be slow at times. For a faster experience, please try <a href="https://aistudio.baidu.com/application/detail/98365" target="_blank" rel="noopener noreferrer">Baidu AI Studio</a> or <a href="https://modelscope.cn/studios/PaddlePaddle/PaddleOCR-VL_Online_Demo/summary" target="_blank" rel="noopener noreferrer">ModelScope</a>.</div>""")
+
+    gr.HTML("""<div class="quick-links"><a href="https://github.com/PaddlePaddle/PaddleOCR" target="_blank">GitHub</a> | <a href="https://ernie.baidu.com/blog/publication/PaddleOCR-VL_Technical_Report.pdf" target="_blank">Technical Report</a> | <a href="https://huggingface.co/PaddlePaddle/PaddleOCR-VL" target="_blank">Model</a> | <a href="https://aistudio.baidu.com/paddleocr" target="_blank">Official Website</a></div>""")
+
+    with gr.Tabs():
+        # ===================== Document Parsing =====================
+        with gr.Tab("Document Parsing"):
+            with gr.Row():
+                with gr.Column(scale=5):
+                    file_doc = gr.File(label="Upload Image", file_count="single", type="filepath", file_types=["image"])
+                    preview_doc_html = gr.HTML(value="", elem_id="image_preview_doc", visible=False)
+                    gr.Markdown("_(Use this mode for recognizing full-page documents such as reports, papers, or magazines. **Note: Headers, footers, and page numbers are ignored by default. For full results including these elements, you can obtain the raw JSON via locally deployed PaddleOCR inference.**)_")
+                    gr.Markdown("💡 *To recognize a single, pre-cropped element (e.g., a table or formula), switch to the 'Element-level Recognition' tab for better results.*")
+
+                    example_url_doc = gr.State(value=None)
+
+                    with gr.Row(variant="panel"):
+                        with gr.Column(scale=2):
+                            btn_parse = gr.Button("Parse Document", variant="primary")
+                        with gr.Column(scale=3):
+                            with gr.Row(elem_classes=["checkbox-row"]):
+                                chart_parsing_switch = gr.Checkbox(label="Enable chart parsing", value=False, min_width=10)
+                                # ###############  修改点在这里 ###############
+                                doc_unwarping_switch = gr.Checkbox(label="Enable document unwarping", value=False, min_width=10)
+                                doc_orientation_switch = gr.Checkbox(label="Enable orientation classification", value=False, min_width=10)
+
+                    if complex_document_examples:
+                        complex_paths = [e[0] for e in complex_document_examples]
+                        complex_state = gr.State(complex_paths)
+
+                        gallery_complex = gr.Gallery(
+                            value=complex_paths, columns=4, height=400,
+                            preview=False, label=None, allow_preview=False
+                        )
+
+                        def on_gallery_select_for_doc(paths, evt: gr.SelectData):
+                            idx = evt.index
+                            if isinstance(idx, (list, tuple)):
+                                idx = idx[0]
+                            try:
+                                url = paths[int(idx)]
+                            except Exception:
+                                raise gr.Error(f"Invalid index from gallery: {evt.index}")
+
+                            return url, update_preview_visibility(url)
+
+                        gallery_complex.select(
+                            fn=on_gallery_select_for_doc,
+                            inputs=[complex_state],
+                            outputs=[example_url_doc, preview_doc_html],
+                        )
+
+                    # ===================== 更新日志模块 =====================
+                    gr.Markdown("""
+                    <div class="notice">
+                        <h3>History Updates</h3>
+                        <ul>
+                            <li>
+                                <strong>Oct 30, 2025:</strong>
+                                Added two advanced control options under the "Document Parsing" tab. These features were previously enabled by default (set to true) but are now user-configurable and default to false.
+                                <ul>
+                                    <li><strong>Enable document unwarping:</strong> Corrects distortions in bent or poorly photographed documents.</li>
+                                    <li><strong>Enable orientation classification:</strong> Automatically corrects the orientation of rotated or upside-down images.</li>
+                                </ul>
+                            </li>
+                            <li>
+                                <strong>Oct 16, 2025:</strong> Initial release of the demo.
+                            </li>
+                        </ul>
+                    </div>
+                    """)
+
+                with gr.Column(scale=7):
+                    with gr.Tabs():
+                        with gr.Tab("Markdown Preview"):
+                            md_preview_doc = gr.Markdown("Please upload an image and click 'Parse Document'.", latex_delimiters=LATEX_DELIMS, elem_id="md_preview_doc")
+                        with gr.Tab("Visualization"):
+                            vis_image_doc = gr.HTML(label="Detection Visualization", elem_id="vis_image_doc")
+                        with gr.Tab("Markdown Source"):
+                            md_raw_doc = gr.Code(label="Markdown Source Code", language="markdown")
+
+            def on_file_doc_change(fp):
+                return None, update_preview_visibility(fp)
+
+            file_doc.change(fn=on_file_doc_change, inputs=[file_doc], outputs=[example_url_doc, preview_doc_html])
+
+            def parse_doc_router(fp, example_url, use_chart, use_unwarping, use_orientation):
+                src = fp if fp else example_url
+                if not src:
+                    raise gr.Error("Please upload an image or pick an example first.")
+                return handle_complex_doc(src, use_chart, use_unwarping, use_orientation)
+
+            btn_parse.click(fn=parse_doc_router, inputs=[file_doc, example_url_doc, chart_parsing_switch, doc_unwarping_switch, doc_orientation_switch],
+                            outputs=[md_preview_doc, vis_image_doc, md_raw_doc])
+
+        # ===================== Element-level Recognition =====================
+        with gr.Tab("Element-level Recognition"):
+            with gr.Row():
+                with gr.Column(scale=5):
+                    file_vl = gr.File(label="Upload Image", file_count="single", type="filepath", file_types=["image"])
+                    preview_vl_html = gr.HTML(value="", elem_id="image_preview_vl", visible=False)
+                    gr.Markdown("_(Best for images with a **simple, single-column layout** (e.g., pure text), or for a **pre-cropped single element** like a table, formula, or chart.)_")
+                    gr.Markdown("Choose a recognition type:")
+
+                    with gr.Row(elem_classes=["prompt-grid"]):
+                        btn_ocr = gr.Button("Text Recognition", variant="secondary")
+                        btn_formula = gr.Button("Formula Recognition", variant="secondary")
+                    with gr.Row(elem_classes=["prompt-grid"]):
+                        btn_table = gr.Button("Table Recognition", variant="secondary")
+                        btn_chart = gr.Button("Chart Recognition", variant="secondary")
+
+                    example_url_vl = gr.State(value=None)
+
+                    if targeted_recognition_examples:
+                        targeted_paths = [e[0] for e in targeted_recognition_examples]
+                        targeted_state = gr.State(targeted_paths)
+
+                        gallery_targeted = gr.Gallery(
+                            value=targeted_paths, columns=4, height=400,
+                            preview=False, label=None, allow_preview=False
+                        )
+
+                        def on_gallery_select_for_vl(paths, evt: gr.SelectData):
+                            idx = evt.index
+                            if isinstance(idx, (list, tuple)):
+                                idx = idx[0]
+                            try:
+                                url = paths[int(idx)]
+                            except Exception:
+                                raise gr.Error(f"Invalid index from gallery: {evt.index}")
+                            return url, update_preview_visibility(url)
+
+                        gallery_targeted.select(
+                            fn=on_gallery_select_for_vl,
+                            inputs=[targeted_state],
+                            outputs=[example_url_vl, preview_vl_html],
+                        )
+
+                with gr.Column(scale=7):
+                    with gr.Tabs():
+                        with gr.Tab("Recognition Result"):
+                            md_preview_vl = gr.Markdown("Please upload an image and click a recognition type.", latex_delimiters=LATEX_DELIMS, elem_id="md_preview_vl")
+                        with gr.Tab("Raw Output"):
+                            md_raw_vl = gr.Code(label="Raw Output", language="markdown")
+
+            def on_file_vl_change(fp):
+                return None, update_preview_visibility(fp)
+
+            file_vl.change(fn=on_file_vl_change, inputs=[file_vl], outputs=[example_url_vl, preview_vl_html])
+
+            def parse_vl_router(fp, example_url, prompt_choice):
+                src = fp if fp else example_url
+                if not src:
+                    raise gr.Error("Please upload an image or pick an example first.")
+                return handle_targeted_recognition(src, prompt_choice)
+
+            btn_ocr.click(fn=parse_vl_router, inputs=[file_vl, example_url_vl, gr.State("Text Recognition")], outputs=[md_preview_vl, md_raw_vl])
+            btn_formula.click(fn=parse_vl_router, inputs=[file_vl, example_url_vl, gr.State("Formula Recognition")], outputs=[md_preview_vl, md_raw_vl])
+            btn_table.click(fn=parse_vl_router, inputs=[file_vl, example_url_vl, gr.State("Table Recognition")], outputs=[md_preview_vl, md_raw_vl])
+            btn_chart.click(fn=parse_vl_router, inputs=[file_vl, example_url_vl, gr.State("Chart Recognition")], outputs=[md_preview_vl, md_raw_vl])
+
+if __name__ == "__main__":
+    demo.queue(max_size=64).launch()