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Update app.py
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app.py
CHANGED
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@@ -7,13 +7,11 @@ from moviepy import VideoFileClip, TextClip, CompositeVideoClip
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from arabic_reshaper import reshape
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# --- الإعدادات ---
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FONT_PATH = "arialbd.ttf"
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model = WhisperModel("large-v3", device="cpu", compute_type="int8")
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def process_arabic_text(text):
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return reshape(text) + "\n "
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# إضافة gr.Progress لتتبع التقدم في الواجهة
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def step_1_extract_words(video_path, progress=gr.Progress()):
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if not video_path:
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return None, "الرجاء رفع فيديو أولاً."
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@@ -22,7 +20,7 @@ def step_1_extract_words(video_path, progress=gr.Progress()):
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segments, _ = model.transcribe(video_path, word_timestamps=True, language="ar")
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words_data = []
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progress(0.5, desc="جاري تحليل الصوت
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for segment in segments:
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for word in segment.words:
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@@ -31,18 +29,19 @@ def step_1_extract_words(video_path, progress=gr.Progress()):
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df = pd.DataFrame(words_data, columns=["الكلمة", "البداية", "النهاية"])
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return df, "تم الاستخراج بنجاح!"
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-
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if video_path is None or df_edited is None or df_edited.empty:
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return None, "بيانات ناقصة."
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output_path = "
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video = VideoFileClip(video_path)
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w, h = int(video.w), int(video.h)
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clips = [video]
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words_list = df_edited.values.tolist()
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chunk_size = 3
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progress(0.1, desc="جاري ت
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for i in range(0, len(words_list), chunk_size):
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current_chunk = words_list[i : i + chunk_size]
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@@ -55,12 +54,12 @@ def step_2_render_video(video_path, df_edited, progress=gr.Progress()):
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txt_clip = TextClip(
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text=clean_sentence,
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font_size=
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color=
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stroke_color='black',
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stroke_width=2,
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method='caption',
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font=
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size=(int(w * 0.9), None),
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text_align='center'
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).with_start(c_start).with_duration(duration).with_position(('center', int(h * 0.65)))
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@@ -69,35 +68,48 @@ def step_2_render_video(video_path, df_edited, progress=gr.Progress()):
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final_video = CompositeVideoClip(clips, size=(w, h))
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print("بدء عملية دمج الفيديو والترميز...")
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final_video.write_videofile(
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output_path,
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codec="libx264",
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audio_codec="aac",
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fps=video.fps,
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logger='bar'
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)
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return output_path, "تم إنتاج الفيديو بنجاح!"
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# --- بناء الواجهة ---
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with gr.Blocks(title="Caption Pro
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gr.Markdown("# 🎬
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with gr.Row():
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video_in = gr.Video(label="فيديو المدخلات")
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video_out = gr.Video(label="الفيديو الناتج")
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status = gr.Textbox(label="الحالة", interactive=False)
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table = gr.Dataframe(headers=["الكلمة", "البداية", "النهاية"], datatype=["str", "number", "number"], interactive=True)
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btn_ex = gr.Button("1. استخراج الكلمات", variant="primary")
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btn_re = gr.Button("2. إنتاج الفيديو", variant="secondary")
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#
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btn_ex.click(step_1_extract_words, inputs=[video_in], outputs=[table, status])
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btn_re.click(
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if __name__ == "__main__":
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app.launch()
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from arabic_reshaper import reshape
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# --- الإعدادات ---
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model = WhisperModel("large-v3", device="cpu", compute_type="int8")
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def process_arabic_text(text):
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return reshape(text) + "\n "
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def step_1_extract_words(video_path, progress=gr.Progress()):
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if not video_path:
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return None, "الرجاء رفع فيديو أولاً."
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segments, _ = model.transcribe(video_path, word_timestamps=True, language="ar")
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words_data = []
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progress(0.5, desc="جاري تحليل الصوت...")
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for segment in segments:
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for word in segment.words:
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df = pd.DataFrame(words_data, columns=["الكلمة", "البداية", "النهاية"])
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return df, "تم الاستخراج بنجاح!"
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# إضافة خيارات اللون والخط كمدخلات للدالة
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def step_2_render_video(video_path, df_edited, font_selection, text_color, font_size, progress=gr.Progress()):
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if video_path is None or df_edited is None or df_edited.empty:
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return None, "بيانات ناقصة."
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output_path = "final_captioned_video.mp4"
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video = VideoFileClip(video_path)
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w, h = int(video.w), int(video.h)
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clips = [video]
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words_list = df_edited.values.tolist()
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chunk_size = 3
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progress(0.1, desc="جاري إنتاج الفيديو بالخيارات المختارة...")
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for i in range(0, len(words_list), chunk_size):
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current_chunk = words_list[i : i + chunk_size]
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txt_clip = TextClip(
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text=clean_sentence,
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font_size=font_size,
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color=text_color, # اللون المختار من الواجهة
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stroke_color='black',
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stroke_width=2,
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method='caption',
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font=font_selection, # الخط المختار من الواجهة
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size=(int(w * 0.9), None),
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text_align='center'
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).with_start(c_start).with_duration(duration).with_position(('center', int(h * 0.65)))
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final_video = CompositeVideoClip(clips, size=(w, h))
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print(f"بدء الدمج بلون {text_color} وخط {font_selection}...")
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final_video.write_videofile(
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output_path,
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codec="libx264",
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audio_codec="aac",
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fps=video.fps,
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logger='bar'
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)
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return output_path, "تم إنتاج الفيديو بنجاح!"
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# --- بناء الواجهة ---
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with gr.Blocks(title="Caption Pro Custom") as app:
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gr.Markdown("# 🎬 محرر الكابشن: تخصيص الألوان والخطوط")
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with gr.Row():
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video_in = gr.Video(label="فيديو المدخلات")
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video_out = gr.Video(label="الفيديو الناتج")
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with gr.Row():
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# خيارات التخصيص
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font_dropdown = gr.Dropdown(
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choices=["arialbd.ttf", "Cairo-Bold.ttf", "Almarai-Bold.ttf", "Tajawal-Bold.ttf"],
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value="arialbd.ttf",
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label="اختر الخط (تأكد من رفع الملف)"
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)
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color_picker = gr.ColorPicker(value="#FFFF00", label="اختر لون النص") # القيمة الافتراضية أصفر
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size_slider = gr.Slider(minimum=30, maximum=120, value=70, step=5, label="حجم الخط")
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status = gr.Textbox(label="الحالة", interactive=False)
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table = gr.Dataframe(headers=["الكلمة", "البداية", "النهاية"], datatype=["str", "number", "number"], interactive=True)
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btn_ex = gr.Button("1. استخراج الكلمات", variant="primary")
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btn_re = gr.Button("2. إنتاج الفيديو", variant="secondary")
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# ربط المدخلات الجديدة بالدالة
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btn_ex.click(step_1_extract_words, inputs=[video_in], outputs=[table, status])
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btn_re.click(
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step_2_render_video,
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inputs=[video_in, table, font_dropdown, color_picker, size_slider],
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outputs=[video_out, status]
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)
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if __name__ == "__main__":
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app.launch()
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