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import streamlit as st
import os
from openai import OpenAI
import openai
import base64
import time
import errno
from elevenlabs import generate, play, voices
from elevenlabs import voices, set_api_key
set_api_key(os.environ['eleven'])
voice = voices()[-1]
client = OpenAI(api_key=os.environ['open'])
def encode_image(image_path):
while True:
try:
with open(image_path, "rb") as image_file:
return base64.b64encode(image_file.read()).decode("utf-8")
except IOError as e:
if e.errno != errno.EACCES:
# Not a "file in use" error, re-raise
raise
# File is being written to, wait a bit and retry
time.sleep(0.1)
def generate_new_line(base64_image):
return [
{
"role": "user",
"content": [
{"type": "text", "text": "Describe this image"},
{
"type": "image_url",
"image_url": f"data:image/jpeg;base64,{base64_image}",
},
],
},
]
def analyze_image(base64_image):
response = client.chat.completions.create(
model="gpt-4-vision-preview",
messages=[
{
"role": "system",
"content": """
You are Sir David Attenborough. Narrate the picture of the human as if it is a nature documentary.
Make it snarky and funny. Don't repeat yourself. Make it short. If I do anything remotely interesting, make a big deal about it!
""",
},
]
+ generate_new_line(base64_image),
max_tokens=100,
)
response_text = response.choices[0].message.content
return response_text
from io import BytesIO
import os
def save_uploaded_file(uploaded_file):
# Create a directory to save the file
save_path = 'uploaded_images'
if not os.path.exists(save_path):
os.makedirs(save_path)
# Save the file
with open(os.path.join(save_path, 'temp'), "wb") as f:
f.write(uploaded_file.getbuffer())
return os.path.join(save_path, 'temp')
def save_audio_file(audio):
# Create a directory to save the file
save_path = 'audio'
if not os.path.exists(save_path):
os.makedirs(save_path)
# Save the file
with open(os.path.join(save_path, 'temp.mp3'), "wb") as f:
f.write(audio)
return os.path.join(save_path, 'temp')
from moviepy.editor import ImageClip, AudioFileClip
def main():
st.title("Image to Audio Converter")
# Image upload
uploaded_file = st.file_uploader("Choose an image...", type=["jpg", "png", "jpeg"])
if uploaded_file:
path = save_uploaded_file(uploaded_file)
print(f'file saved to {path}')
encoded_image = encode_image(path)
print('image encoded')
analyzed_image = analyze_image(encoded_image)
print('image analyzed \n' + analyzed_image)
audio_file = generate(text=analyzed_image, voice=voice, model="eleven_turbo_v2")
if audio_file is not None:
st.audio(audio_file, format='audio/mp3')
st.download_button('Download Audio', audio_file, file_name='narrated.mp3')
audio_filename = 'narrated.mp3'
with open(audio_filename, 'wb') as f:
f.write(audio_file)
print('creating video')
# Create a video clip from the static image
video_clip = ImageClip(path).set_duration(AudioFileClip(audio_filename).duration)
# Set the audio of the video clip as the generated audio file
video_clip = video_clip.set_audio(AudioFileClip(audio_filename))
print('video created')
# Specify the filename for the video
video_filename = "narrated_video.mp4"
# Write the video file to disk
video_clip.write_videofile(video_filename, codec="libx264", audio_codec="aac", fps=24)
# Provide a download button for the video
with open(video_filename, "rb") as file:
st.video(video_filename)
st.download_button('Download Video', file, file_name=video_filename)
if __name__ == "__main__":
main() |