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Update app.py
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app.py
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# ==========================================
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# 核心修復:偽裝螢幕環境,防止雲端伺服器崩潰
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# ==========================================
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import sys
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import types
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# 建立一個假的 screeninfo 模組
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fake_screeninfo = types.ModuleType("screeninfo")
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fake_screeninfo.ScreenInfoError = Exception
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# 偽裝 get_monitors 函數,讓它回傳一個假的螢幕物件(包含 width 和 height 屬性)
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class FakeMonitor:
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width = 1920
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height = 1080
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fake_screeninfo.get_monitors = lambda: [FakeMonitor()]
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# 強行注入到 Python 的全域模組緩存中
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sys.modules["screeninfo"] = fake_screeninfo
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# ==========================================
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import os
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import shutil
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import subprocess
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import gradio as gr
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OMR_DIR = "OMRChecker"
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#
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if image_file is None or not template_content:
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return None, None, "錯誤:請務必上傳答案卡圖片並填寫 Template JSON 配置。"
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# 定義 OMRChecker 的工作目錄結構
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job_dir = os.path.join(OMR_DIR, "inputs", "hf_space_job")
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outputs_dir = os.path.join(OMR_DIR, "outputs")
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# 清理舊的暫存輸入與輸出,避免前後兩次請求互相干擾
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if os.path.exists(job_dir):
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shutil.rmtree(job_dir)
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os.makedirs(job_dir, exist_ok=True)
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if os.path.exists(outputs_dir):
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shutil.rmtree(outputs_dir)
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# 將上傳的圖片複製到 OMR 要求的輸入目錄
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target_image_path = os.path.join(job_dir, "sheet.jpg")
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shutil.copy(image_file, target_image_path)
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# 將前端/API 傳入的 Template JSON 寫入對應位置
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with open(os.path.join(job_dir, "template.json"), "w", encoding="utf-8") as f:
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f.write(template_content)
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# 保險起見,也在 inputs 根目錄放一份
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with open(os.path.join(OMR_DIR, "inputs", "template.json"), "w", encoding="utf-8") as f:
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f.write(template_content)
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cwd=OMR_DIR,
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capture_output=True,
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text=True
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)
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# 3. 搜尋並收集 OMRChecker 產生的輸出結果 (CSV 與 標記圖片)
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csv_file = None
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output_image = None
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if os.path.exists(outputs_dir):
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for root, dirs, files in os.walk(outputs_dir):
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for file in files:
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if file.endswith(".csv"):
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csv_file = os.path.join(root, file)
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elif file.endswith((".jpg", ".jpeg", ".png")) and "results" in root.lower():
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output_image = os.path.join(root, file)
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# 彙整 CLI 的標準輸出日誌
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logs = f"--- STDOUT ---\n{result.stdout}\n\n--- STDERR ---\n{result.stderr}"
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return csv_file, output_image, logs
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# 4. 建立 Gradio 介面
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interface = gr.Interface(
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fn=process_omr,
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inputs=[
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gr.Image(type="filepath", label="1. 上傳 OMR 答案卡圖片 (JPG/PNG)"),
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gr.Textbox(lines=12, label="2. 填入 Template JSON 配置", placeholder='{"columns": [...]}')
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],
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outputs=[
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gr.File(label="下載辨識結果 (CSV)"),
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gr.Image(label="視覺化劃記檢視圖片"),
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gr.Textbox(label="系統執行日誌 (Logs)")
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],
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title="OMRChecker 雲端辨識系統 API",
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description="本系統基於 udayraj123/OMRChecker。除了網頁操作外,亦可透過頁尾的 'Use via API' 連結進行自動化調用。"
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)
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if __name__ == "__main__":
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interface.launch()
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import os
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import sys
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import shutil
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import subprocess
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import gradio as gr
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# 1. 啟動時檢查並自動克隆 OMRChecker 官方專案
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if not os.path.exists(OMR_DIR):
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@@ -147,12 +60,17 @@ def process_omr(image_file, template_content):
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with open(os.path.join(OMR_DIR, "inputs", "template.json"), "w", encoding="utf-8") as f:
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f.write(template_content)
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#
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result = subprocess.run(
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[sys.executable, "main.py"],
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cwd=OMR_DIR,
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capture_output=True,
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text=True
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)
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# 3. 搜尋並收集 OMRChecker 產生的輸出結果 (CSV 與 標記圖片)
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return csv_file, output_image, logs
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# 4. 建立 Gradio 介面
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interface = gr.Interface(
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fn=process_omr,
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inputs=[
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import os
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import sys
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import shutil
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import subprocess
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import gradio as gr
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OMR_DIR = "OMRChecker"
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MOCK_DIR = os.path.abspath("mock_libs")
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# =======================================================
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# 核心修復:在硬碟建立實體偽裝庫,並透過 PYTHONPATH 注入子程序
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# =======================================================
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os.makedirs(MOCK_DIR, exist_ok=True)
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with open(os.path.join(MOCK_DIR, "screeninfo.py"), "w", encoding="utf-8") as f:
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f.write('''\
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class ScreenInfoError(Exception):
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pass
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class FakeMonitor:
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width = 1920
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height = 1080
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def get_monitors():
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return [FakeMonitor()]
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''')
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# =======================================================
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# 1. 啟動時檢查並自動克隆 OMRChecker 官方專案
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if not os.path.exists(OMR_DIR):
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with open(os.path.join(OMR_DIR, "inputs", "template.json"), "w", encoding="utf-8") as f:
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f.write(template_content)
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# 配置環境變數,強迫子程序優先載��我們的 mock_libs
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current_env = os.environ.copy()
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current_env["PYTHONPATH"] = MOCK_DIR + os.pathsep + current_env.get("PYTHONPATH", "")
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# 2. 執行 OMRChecker CLI 核心 (帶入偽裝環境變數)
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result = subprocess.run(
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[sys.executable, "main.py"],
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cwd=OMR_DIR,
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capture_output=True,
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text=True,
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env=current_env
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)
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# 3. 搜尋並收集 OMRChecker 產生的輸出結果 (CSV 與 標記圖片)
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return csv_file, output_image, logs
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# 4. 建立 Gradio 介面
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interface = gr.Interface(
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fn=process_omr,
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inputs=[
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