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from moviepy.editor import *
import json
def load_json_output(output_query_response):
# Convert JSON string to Python dictionary
return json.loads(output_query_response)
def extract_audio_from_video(video_path):
video = VideoFileClip(video_path)
audio_path = "audio/current_audio.mp3"
if video.audio is not None:
video.audio.write_audiofile(audio_path)
print("Audio file has been extracted from the video")
return audio_path
else:
print("No audio found in the video.")
return None
def get_explosion_segments(json_data):
# creating an empty array for the results
result = []
# iterate over every explosion occurrence and find start, end, best values using the ml algorithm
for i in json_data["value"]:
result.append([i["start"], i["end"], i["best"]])
# update start_explosion_time and end_explosion_time for each explosion occurrence
for explosion in result:
best_time = explosion[2]
best_time_seconds = sum(x * int(t) for x, t in zip([3600, 60, 1], best_time.split(":")))
start_explosion_time_seconds = best_time_seconds - 2
end_explosion_time_seconds = best_time_seconds + 1
explosion[0] = "{:02d}:{:02d}:{:02d}".format(start_explosion_time_seconds // 3600,
(start_explosion_time_seconds % 3600 // 60),
start_explosion_time_seconds % 60)
explosion[1] = "{:02d}:{:02d}:{:02d}".format(end_explosion_time_seconds // 3600,
(end_explosion_time_seconds % 3600 // 60),
end_explosion_time_seconds % 60)
return result
def create_final_audio(current_audio_path, haptic_audio_path, explosion_segments):
current_audio = AudioFileClip(current_audio_path) # location of the uploaded video
# define the segments for the audio clips
final_audio_segments = []
#haptic_audio_path = haptic_audio_url
haptic_audio = AudioFileClip(haptic_audio_path)
# Iterate through each explosion occurrence and create audio segments
for explosion in explosion_segments:
best_explosion_time = explosion[2]
best_explosion_time_seconds = sum(x * int(t) for x, t in zip([3600, 60, 1], best_explosion_time.split(":")))
# Adjust the duration of the haptic audio to match the duration of the explosion
haptic_audio_duration = haptic_audio.duration
haptic_audio_clip = haptic_audio.subclip(0, haptic_audio_duration)
# Create an audio clip starting from the best explosion time
explosion_audio_clip = current_audio.subclip(best_explosion_time_seconds - 1,
best_explosion_time_seconds + haptic_audio_duration)
# Concatenate the haptic audio clip with the explosion audio clip
final_audio = concatenate_audioclips([explosion_audio_clip, haptic_audio_clip])
final_audio_segments.append(final_audio)
# concatenate final audio segments
final_audio = concatenate_audioclips(final_audio_segments)
# Match the audio duration with the video duration
final_audio = final_audio.set_duration(current_audio.duration)
return final_audio
def master_audio(audio_clip):
# Apply audio mastering techniques here
# Example: loudness normalization, equalization, compression, etc.
# Replace the following line with your audio mastering process
mastered_audio = audio_clip.fx(afx.audio_normalize)
return mastered_audio
def save_audio(audio_clip, file_path):
audio_clip.write_audiofile(file_path)
print("Enhanced audio has been created")
def without_audio(video_clip):
return video_clip.without_audio()
def combine_video_audio(video_clip, audio_clip):
return video_clip.set_audio(audio_clip)
def save_video(video_clip, file_path):
video_clip.write_videofile(file_path, fps=60)
print("Final video has been created")
def process_video(current_video_path, output_query_response):
json_data = load_json_output(output_query_response)
audio_path = extract_audio_from_video(current_video_path)
if audio_path:
explosion_segments = get_explosion_segments(json_data)
final_audio = create_final_audio(audio_path, explosion_segments)
final_audio_mastered = master_audio(final_audio)
save_audio(final_audio_mastered, "output.mp3")
current_video = VideoFileClip(current_video_path)# Extracting audio from the video
extracted_video = without_audio(current_video)
final_video = combine_video_audio(extracted_video, final_audio_mastered)
save_video(final_video, "final_video.mp4")
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