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Update app.py
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app.py
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import gradio as gr
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import numpy as np
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import wave
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import matplotlib.pyplot as plt
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def
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return "Ошибка: WAV файл должен быть монофоническим."
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# Читаем данные WAV файла
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wav_data = np.frombuffer(wav_file.readframes(n_frames), dtype=np.int16)
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fig, ax = plt.subplots()
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ax.imshow(image)
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ax.axis('off')
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buf = BytesIO()
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plt.savefig(buf, format="png")
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buf.seek(0)
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return buf
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except Exception as e:
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return f"Ошибка: {e}"
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#
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iface = gr.Interface(
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fn=
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inputs=gr.
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outputs=
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title="SSTV
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description="
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#
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iface.launch()
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import numpy as np
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import scipy.signal
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import matplotlib.pyplot as plt
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import gradio as gr
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def dummy_sstv_decode(audio_data, sample_rate):
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"""
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A placeholder function for decoding SSTV signals.
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For a real decoder, you would process the audio_data to extract image information.
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"""
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# In a real implementation, you'd process the audio to extract an image.
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# Here, we just return a blank image for demonstration purposes.
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image = np.zeros((256, 320, 3), dtype=np.uint8)
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return image
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def sstv_decoder(audio_file):
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# Load the audio file
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sample_rate, audio_data = scipy.io.wavfile.read(audio_file.name)
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# Decode the SSTV signal (Dummy Function)
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image = dummy_sstv_decode(audio_data, sample_rate)
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# Display the image
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plt.imshow(image)
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plt.axis('off')
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plt.show()
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return image
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# Set up Gradio interface
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iface = gr.Interface(
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fn=sstv_decoder,
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inputs=gr.Audio(source="upload", type="filepath"),
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outputs="image",
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title="SSTV Decoder",
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description="Upload an audio file with an SSTV signal to decode it into an image.",
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)
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# Launch the interface
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iface.launch()
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