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  1. README.md +14 -14
  2. app.py +20 -60
  3. requirements.txt +5 -3
README.md CHANGED
@@ -1,14 +1,14 @@
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- ---
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- title: Basata
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- emoji: 💬
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- colorFrom: yellow
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- colorTo: purple
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- sdk: gradio
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- sdk_version: 5.0.1
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- app_file: app.py
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- pinned: false
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- license: mit
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- short_description: المساعد الذكي لتطبيق بساطة الطبي
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- ---
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-
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- An example chatbot using [Gradio](https://gradio.app), [`huggingface_hub`](https://huggingface.co/docs/huggingface_hub/v0.22.2/en/index), and the [Hugging Face Inference API](https://huggingface.co/docs/api-inference/index).
 
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+
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+ # مشروع استخراج النصوص من الصور
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+
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+ ### الوصف
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+ تطبيق يعتمد على EasyOCR لتحليل النصوص من الصور باستخدام Gradio.
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+
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+ ### المتطلبات
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+ - Python 3.7+
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+ - مكتبة EasyOCR و Gradio مثبتة.
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+
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+ ### كيفية الاستخدام
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+ 1. قم بتشغيل المشروع.
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+ 2. ارفع صورة تحتوي على نصوص.
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+ 3. احصل على النصوص المستخرجة مباشرةً.
app.py CHANGED
@@ -1,64 +1,24 @@
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- import gradio as gr
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- from huggingface_hub import InferenceClient
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-
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- """
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- For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
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- """
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- client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
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-
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-
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- def respond(
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- message,
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- history: list[tuple[str, str]],
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- system_message,
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- max_tokens,
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- temperature,
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- top_p,
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- ):
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- messages = [{"role": "system", "content": system_message}]
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-
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- for val in history:
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- if val[0]:
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- messages.append({"role": "user", "content": val[0]})
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- if val[1]:
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- messages.append({"role": "assistant", "content": val[1]})
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-
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- messages.append({"role": "user", "content": message})
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- response = ""
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-
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- for message in client.chat_completion(
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- messages,
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- max_tokens=max_tokens,
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- stream=True,
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- temperature=temperature,
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- top_p=top_p,
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- ):
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- token = message.choices[0].delta.content
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-
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- response += token
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- yield response
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-
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-
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- """
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- For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
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- """
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- demo = gr.ChatInterface(
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- respond,
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- additional_inputs=[
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- gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
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- gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
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- gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
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- gr.Slider(
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- minimum=0.1,
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- maximum=1.0,
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- value=0.95,
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- step=0.05,
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- label="Top-p (nucleus sampling)",
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- ),
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- ],
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  )
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-
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  if __name__ == "__main__":
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- demo.launch()
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ import gradio as gr
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+ import easyocr
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+
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+ # تعريف وظيفة لتحليل النصوص من الصور
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+ def extract_text_from_image(image_path):
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+ reader = easyocr.Reader(['ar', 'en']) # يدعم العربية والإنجليزية
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+ result = reader.readtext(image_path, detail=0)
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+ return " ".join(result)
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+
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+ # إنشاء واجهة باستخدام Gradio
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+ def process_image(image):
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+ text = extract_text_from_image(image)
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+ return text
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+
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+ interface = gr.Interface(
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+ fn=process_image,
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+ inputs=gr.Image(type="filepath"),
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+ outputs="text",
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+ title="استخراج النصوص من الصور"
 
 
 
 
 
 
 
 
 
 
 
 
 
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  )
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  if __name__ == "__main__":
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+ interface.launch()
requirements.txt CHANGED
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- huggingface_hub==0.25.2
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- gradio==3.34.0
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- torch
 
 
 
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+
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+ easyocr
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+ torch
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+ torchvision
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+ gradio