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Update app.py
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app.py
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@@ -1,41 +1,16 @@
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import gradio as gr
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import cv2
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import tempfile
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import numpy as np
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import os
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import time
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import requests
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import base64
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import
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import
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# Backend server URL
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backend_server_url = "https://0416-2600-1017-a410-36b8-2357-52be-1318-959b.ngrok-free.app"
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send_thread = None # To keep track of ongoing threads
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# Audio playback
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def play_audio(audio_base64):
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"""
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Play audio file using pygame mixer.
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Args:
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audio_path: Path to audio file
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"""
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audio_bytes = base64.b64decode(audio_base64)
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try:
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with tempfile.NamedTemporaryFile(delete=False, suffix=".wav") as temp_audio:
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temp_audio.write(audio_bytes)
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temp_audio_path = temp_audio.name
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pygame.mixer.init()
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pygame.mixer.music.load(temp_audio_path)
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pygame.mixer.music.play()
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while pygame.mixer.music.get_busy():
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pygame.time.Clock().tick(10)
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except Exception as e:
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print(f"Audio error: {e}")
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# Backend interaction
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def send_to_backend(frame):
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try:
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except Exception as e:
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return {"error": f"Exception: {str(e)}"}
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def thread_sendToBackend(frame):
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""" Starts a thread to send the frame to the backend. """
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global send_thread
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if send_thread is None:
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send_thread = threading.Thread(target=send_to_backend, args=(frame,), daemon=True)
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send_thread.start()
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# # Gradio processing function
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def process_webcam(image):
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if image is None:
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return None,
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frame = cv2.cvtColor(np.array(image), cv2.COLOR_RGB2BGR)
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result = send_to_backend(frame)
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caption = result
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audio_base64 = result
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if audio_base64:
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return caption
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# Gradio interface
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@@ -95,6 +65,7 @@ demo = gr.Interface(
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inputs=gr.Image(sources=["upload", "webcam"]),
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outputs=[
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gr.Textbox(label="Caption"),
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],
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live=True,
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title="SpokenVision",
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allow_flagging="never"
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)
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demo.launch()
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import gradio as gr
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import cv2
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import numpy as np
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import os
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import requests
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import base64
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import base64
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import io
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import soundfile as sf
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# Backend server URL
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backend_server_url = "https://0416-2600-1017-a410-36b8-2357-52be-1318-959b.ngrok-free.app"
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# Backend interaction
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def send_to_backend(frame):
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try:
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except Exception as e:
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return {"error": f"Exception: {str(e)}"}
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# # Gradio processing function
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def process_webcam(image):
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if image is None:
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return None, None
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frame = cv2.cvtColor(np.array(image), cv2.COLOR_RGB2BGR)
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result = send_to_backend(frame)
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caption = result.get("caption", "No caption")
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audio_base64 = result.get("audio_base64", None)
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if audio_base64:
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audio_bytes = base64.b64decode(audio_base64)
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audio_buffer = io.BytesIO(audio_bytes)
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audio_array, sample_rate = sf.read(audio_buffer)
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return caption, (sample_rate, audio_array)
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return caption, None
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# Gradio interface
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inputs=gr.Image(sources=["upload", "webcam"]),
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outputs=[
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gr.Textbox(label="Caption"),
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gr.Audio(label="Audio Output")
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],
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live=True,
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title="SpokenVision",
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allow_flagging="never"
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)
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demo.launch()
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