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Update app.py
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app.py
CHANGED
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@@ -2,14 +2,53 @@ import os
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import json
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import gradio as gr
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from pathlib import Path
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# =============== 配置:HF dataset 仓库 ID =================
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HF_DATASET_ID = "maplebb/UniREditBench-Results"
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HF_BASE_URL = f"https://huggingface.co/datasets/{HF_DATASET_ID}/resolve/main"
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ROOT_DIR = Path(__file__).resolve().parent
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# =============== data.json 还是放在 Space 本地 =================
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JSON_PATH = ROOT_DIR / "data.json"
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# =============== 读 json & 建索引 =================
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@@ -21,7 +60,8 @@ ALL_NAMES = sorted({item["name"] for item in data})
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# (name, idx_str) -> item
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INDEX_MAP = {(item["name"], str(item["idx"])): item for item in data}
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# =============== baseline
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ALL_MODELS = [
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"Bagel-Think",
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"DreamOmni2",
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@@ -58,20 +98,27 @@ def get_indices_for_name(name: str):
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def render_img_html(rel_path: str, max_h=512):
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"""
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像第二段代码那样,直接返回远程 URL,不在后端拉图 / 编码。
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rel_path 例如: 'original_image/jewel2/0001.png'
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"""
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if not rel_path:
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return "<p>No original image.</p>"
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-
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-
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-
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def get_baseline_gallery(name: str, idx: str, models):
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"""生成 baseline 图像的 HTML
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if not name or not idx:
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return "<p>Please select name and idx.</p>"
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@@ -90,7 +137,9 @@ def get_baseline_gallery(name: str, idx: str, models):
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# 第一行:模型名
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html += "<tr>"
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for m in sub_models:
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html +=
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for _ in range(N_COL - len(sub_models)):
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html += f'<td width="{WIDTH}%"></td>'
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html += "</tr>"
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@@ -98,10 +147,8 @@ def get_baseline_gallery(name: str, idx: str, models):
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# 第二行:对应图片
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html += "<tr>"
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for m in sub_models:
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# 对应 dataset 目录:Unireditbench_baseline_images/{model}/{name}/{idx}.png
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rel_path = f"Unireditbench_baseline_images/{m}/{name}/{idx}.png"
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cell = f'<img src="{src}" style="max-width:100%; max-height:256px;">'
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html += f'<td width="{WIDTH}%" style="text-align:center;">{cell}</td>'
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for _ in range(N_COL - len(sub_models)):
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html += f'<td width="{WIDTH}%"></td>'
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@@ -133,7 +180,7 @@ def load_sample(name, idx, selected_models):
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instruction = item.get("instruction", "")
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rules = item.get("rules", "")
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# data.json
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# "original_image_path": "original_image/jewel2/0001.png"
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orig_rel = item.get("original_image_path", "")
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orig_html = render_img_html(orig_rel, max_h=512)
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@@ -142,7 +189,6 @@ def load_sample(name, idx, selected_models):
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return info_md, instruction, rules, orig_html, gallery_html
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-
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def _step_idx(name: str, idx: str, direction: int):
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"""direction=-1 上一个, direction=+1 下一个;到边界就停住。"""
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idxs = get_indices_for_name(name)
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@@ -206,11 +252,12 @@ with gr.Blocks() as demo:
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prev_button = gr.Button("Prev")
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next_button = gr.Button("Next")
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load_button = gr.Button("Load sample")
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model_checkboxes = gr.CheckboxGroup(
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label="Baselines to show",
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choices=BASELINE_MODELS,
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value=
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)
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with gr.Column(scale=2):
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@@ -226,6 +273,7 @@ with gr.Blocks() as demo:
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gr.Markdown("### Original Image")
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orig_image_html = gr.HTML()
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gallery_html = gr.HTML()
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name_dropdown.change(
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@@ -239,7 +287,7 @@ with gr.Blocks() as demo:
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inputs=[name_dropdown, idx_dropdown, model_checkboxes],
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outputs=[info_markdown, instruction_box, rules_box, orig_image_html, gallery_html]
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)
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# Prev / Next:会同时更新 idx_dropdown + 刷新所有内容
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prev_button.click(
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fn=prev_sample,
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@@ -255,4 +303,5 @@ with gr.Blocks() as demo:
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if __name__ == "__main__":
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demo.launch(server_name="0.0.0.0", server_port=7860)
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import json
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import gradio as gr
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from pathlib import Path
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from io import BytesIO
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import base64
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import requests
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from PIL import Image
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# =============== 配置:HF dataset 仓库 ID =================
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HF_DATASET_ID = "maplebb/UniREditBench-Results"
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HF_BASE_URL = f"https://huggingface.co/datasets/{HF_DATASET_ID}/resolve/main"
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BASE_HF_URL = f"https://huggingface.co/datasets/{HF_DATASET_ID}/resolve/main"
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_image_cache = {}
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_html_cache = {}
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def get_url_response(url):
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try:
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resp = requests.get(url, timeout=10)
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resp.raise_for_status()
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return resp
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except Exception as e:
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print(f"Error fetching {url}: {e}")
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return None
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def load_image_uniredit(rel_path: str):
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"""从 UniREditBench 数据集拉图(后端 requests)"""
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rel_path = rel_path.lstrip("/")
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if rel_path in _image_cache:
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return _image_cache[rel_path]
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url = f"{BASE_HF_URL}/{rel_path}"
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resp = get_url_response(url)
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if not resp:
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return None
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img = Image.open(BytesIO(resp.content)).convert("RGB")
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_image_cache[rel_path] = img
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return img
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def pil_to_base64(img):
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if img is None:
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return ""
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buf = BytesIO()
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img.save(buf, format="PNG")
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s = base64.b64encode(buf.getvalue()).decode("utf-8")
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return f"data:image/png;base64,{s}"
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ROOT_DIR = Path(__file__).resolve().parent
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# =============== data.json 还是放在 Space 本地 =================
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# 如果想把 data.json 也放到 dataset 里,可以改成用 hf_hub_download(后面我再写)
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JSON_PATH = ROOT_DIR / "data.json"
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# =============== 读 json & 建索引 =================
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# (name, idx_str) -> item
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INDEX_MAP = {(item["name"], str(item["idx"])): item for item in data}
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# =============== baseline 模型列表(现在不能再 os.listdir,本地没图了) =================
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# 建议直接手动写齐你有的模型
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ALL_MODELS = [
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"Bagel-Think",
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"DreamOmni2",
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def render_img_html(rel_path: str, max_h=512):
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if not rel_path:
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return "<p>No original image.</p>"
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key = (rel_path, None) # 不区分高度
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if key in _html_cache:
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data_url = _html_cache[key]
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return f'<img src="{data_url}" style="max-width:100%; max-height:{max_h}px;">'
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img = load_image_uniredit(rel_path)
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if img is None:
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return "<p>Failed to load image.</p>"
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# 不再 resize,直接按原分辨率编码
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data_url = pil_to_base64(img)
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_html_cache[key] = data_url
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return f'<img src="{data_url}" style="max-width:100%; max-height:{max_h}px;">'
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def get_baseline_gallery(name: str, idx: str, models):
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"""生成 baseline 图像的 HTML 表格(使用远程 URL)."""
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if not name or not idx:
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return "<p>Please select name and idx.</p>"
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# 第一行:模型名
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html += "<tr>"
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for m in sub_models:
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html += (
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f'<td width="{WIDTH}%" style="text-align:center;"><h4>{m}</h4></td>'
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)
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for _ in range(N_COL - len(sub_models)):
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html += f'<td width="{WIDTH}%"></td>'
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html += "</tr>"
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# 第二行:对应图片
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html += "<tr>"
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for m in sub_models:
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rel_path = f"Unireditbench_baseline_images/{m}/{name}/{idx}.png"
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cell = render_img_html(rel_path, max_h=256)
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html += f'<td width="{WIDTH}%" style="text-align:center;">{cell}</td>'
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for _ in range(N_COL - len(sub_models)):
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html += f'<td width="{WIDTH}%"></td>'
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instruction = item.get("instruction", "")
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rules = item.get("rules", "")
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# data.json 里原本的 original_image_path 建议直接保持为相对路径:
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# "original_image_path": "original_image/jewel2/0001.png"
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orig_rel = item.get("original_image_path", "")
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orig_html = render_img_html(orig_rel, max_h=512)
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return info_md, instruction, rules, orig_html, gallery_html
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def _step_idx(name: str, idx: str, direction: int):
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"""direction=-1 上一个, direction=+1 下一个;到边界就停住。"""
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idxs = get_indices_for_name(name)
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prev_button = gr.Button("Prev")
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next_button = gr.Button("Next")
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load_button = gr.Button("Load sample")
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model_checkboxes = gr.CheckboxGroup(
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label="Baselines to show",
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choices=BASELINE_MODELS, # 还是所有模型都可以选
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value=PRIORITY_MODELS, # ✅ 默认只勾选优先那几个
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)
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with gr.Column(scale=2):
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gr.Markdown("### Original Image")
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orig_image_html = gr.HTML()
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gallery_html = gr.HTML()
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name_dropdown.change(
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inputs=[name_dropdown, idx_dropdown, model_checkboxes],
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outputs=[info_markdown, instruction_box, rules_box, orig_image_html, gallery_html]
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)
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# Prev / Next:会同时更新 idx_dropdown + 刷新所有内容
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prev_button.click(
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fn=prev_sample,
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if __name__ == "__main__":
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# 不再需要 allowed_paths / set_static_paths
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demo.launch(server_name="0.0.0.0", server_port=7860)
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