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Create app.py
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app.py
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# تثبيت المكتبات المطلوبة
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!pip install transformers gradio torch gtts pydub SpeechRecognition
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import gradio as gr
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from transformers import BlipForImageTextRetrieval, AutoProcessor, WhisperForConditionalGeneration, AutoTokenizer
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from gtts import gTTS
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import speech_recognition as sr
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import torch
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from PIL import Image
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# تحميل النماذج والمعالجات
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image_model = BlipForImageTextRetrieval.from_pretrained("Salesforce/blip-itm-base-coco")
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image_processor = AutoProcessor.from_pretrained("Salesforce/blip-itm-base-coco")
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whisper_model = WhisperForConditionalGeneration.from_pretrained("openai/whisper-base")
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whisper_tokenizer = AutoTokenizer.from_pretrained("openai/whisper-base")
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# دالة مطابقة الصورة مع النص
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def image_text_matching(img, text):
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raw_image = img.convert('RGB')
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inputs = image_processor(images=raw_image, text=text, return_tensors="pt")
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outputs = image_model(**inputs)
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result = outputs[0][0]
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softmax_result = torch.softmax(result, dim=0)
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max_index = torch.argmax(softmax_result).item()
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return 'Match' if max_index == 1 else 'No Match'
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# دالة تحويل النص إلى صوت
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def text_to_audio(text):
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tts = gTTS(text=text, lang='en') # يمكنك تعديل اللغة إلى 'ar' للنصوص العربية
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audio_file = "output.mp3"
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tts.save(audio_file)
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return audio_file
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# دالة تحويل الصوت إلى نص
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def audio_to_text(audio):
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recognizer = sr.Recognizer()
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with sr.AudioFile(audio) as source:
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audio_data = recognizer.record(source)
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text = recognizer.recognize_google(audio_data, language='ar')
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return text
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# إعداد واجهة Gradio
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iface = gr.Interface(
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fn=lambda img, text, audio: (
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image_text_matching(img, text),
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text_to_audio(text),
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audio_to_text(audio) if audio else "No audio uploaded"
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),
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inputs=[
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gr.Image(type="pil", label="Upload Image"),
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gr.Textbox(label="Enter Text"),
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gr.Audio(label="Upload Audio", type="filepath") # تعديل هنا
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],
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outputs=["text", "audio", "text"],
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title="AI Project: Image-Text Matching and Audio Tasks",
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description="Upload an image and enter text to see if they match. Also, convert text to audio and audio to text."
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)
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# تشغيل الواجهة
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iface.launch()
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