VideoDB Documentation

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AI Generated Ad Films for Product Videography: Wellsaid, Open AI & VideoDB

Automatically Creating a professional quality advertisement from product videography B-Roll

⁠

Overview

Crafting AI content and blending results from multiple tools can be incredibly powerful and time-efficient. Manual execution of these tasks is often cumbersome and time-consuming. However, with the right tools and techniques, you can automate various processes to achieve remarkable results effortlessly.

In this tutorial, we will explore how to leverage the seamless integration between

Wellsaid⁠

OpenAI⁠

and

VideoDB⁠

to create captivating voiceovers for product advertisements. By harnessing the advanced capabilities of these platforms, you can enhance the storytelling and engagement of your product videos with AI-generated voiceovers; all within a single environment.

For this tutorial, we’ll be using product footage from

a photoshoot⁠

from Youtube and converting it into a professionally made advertisement for a jewellery brand; all using prompts and programmatic scripting 😎.

⁠

Setup

📦 Installing packages

Ensure you have the necessary packages installed:

%pip install openai

%pip install videodb

🔑 API Keys

Ensure you have access to

OpenAI⁠

Wellsaid⁠

and

VideoDB⁠

API keys. If you haven't already, sign up for API access on the respective platforms.

Get your API key from

VideoDB Console⁠

. ( Free for first 50 uploads, No credit card required ) 🎉

import os

os.environ["OPENAI_API_KEY"] = ""

os.environ["WELLSAID_API_KEY"] = ""

os.environ["VIDEO_DB_API_KEY"] = ""

🎙️ Wellsaid's Voice Avatar

You will also need Wellsaid's Voice Avatar that you want to use to generate your voiceover.

For this demo, we’ll choose a slick, professional ads voiceover artist’s voice. Wellsaid has a wide range of options to choose from- you can check them out by signing up on their platform and accessing their

Voice Studio⁠

. Once finalized, copy the Speaker ID from Wellsaid and link it here.

voiceover_artist_id = "109"

⁠

Implementation

🌐 Step 1: Connect to VideoDB

Begin by establishing a connection to VideoDB using your API key.

from videodb import connect

# Connect to VideoDB using your API key

conn = connect()

coll = conn.get_collection()

🎥 Step 2: Upload Video

Upload your product video to VideoDB using its URL or file path.

# Upload a video by URL (replace the url with your video)

video = conn.upload('https://www.youtube.com/watch?v=2DcAMbmmYNM')

🔍 Step 3: Analyze Scenes and Generate Scene Descriptions

Analyze the scenes within your product video using VideoDB’s scene indexing capabilities. This will provide context for the script prompt.

video.index_scenes()

Let's view the description of first scene from the video

scenes = video.get_scenes()

print(f"{scenes[0]['start']} - {scenes[0]['end']}")

print(scenes[0]["response"])

Output:

[{'end': '0.5338666666666667', 'response': 'The jewellery is a beautiful and delicate piece that would be perfect for any occasion. The necklace is made of a thin gold chain with a small diamond pendant, and the earrings are made of the same gold with a small diamond stud. The bracelet is made of the same gold and has a small diamond charm. The ring is made of the same gold and has a small diamond solitaire.', 'start': '0'},

🎤 Step 4: Generate Voiceover Script with LLM

Combine scene descriptions with a script prompt, instructing LLM (OpenAI) to create a suitable voiceover for your product advertisement.

This script prompt can be refined and tweaked to generate the most suitable output. Check out

these examples⁠

to explore more use cases.

import openai

client = openai.OpenAI()

script_prompt = "Here's the data from a scene index for a video from a jewellery product photoshoot. Study this and then generate a synced script based on the description below. Make sure the script is in the language, voice and style of a professional voiceover artist skilled at weaving beautiful storytelling in advertisements.\n \n"

full_prompt = script_prompt

# run this prompt for each scene

for scene in scenes:

full_prompt += f"- {scene}\n"

openai_res = client.chat.completions.create(

model="gpt-3.5-turbo",

messages=[{"role": "system", "content": full_prompt}],

)

voiceover_script = openai_res.choices[0].message.content

# Truncate first 1000 characters of script

# If you have Wellsaid's paid plan remove this

voiceover_script = voiceover_script[:1000]

🎤 Step 5: Generate Voiceover Audio with Wellsaid

Utilize the generated script to synthesize a professional voiceover for your product advertisement using Wellsaid's API.

import requests

import time

# Call Wellsaid API to generate voiceover

url = "https://api.wellsaidlabs.com/v1/tts/stream"

headers = {

"accept": "application/json",

"content-type": "application/json",

"X-Api-Key": os.environ.get("WELLSAID_API_KEY")

}

# Initiate TTS Job for each Chunk

payload = {

"text": voiceover_script,

"speaker_id": speaker_id

}

wellsaid_res = requests.request("POST", url, json=payload, headers=headers)

# Save the audio file

audio_file = "audio.mp3"

CHUNK_SIZE = 1024

with open(audio_file, 'wb') as f:

for chunk in wellsaid_res.iter_content(chunk_size=CHUNK_SIZE):

if chunk:

f.write(chunk)

🎬 Step 6: Add Voiceover to Video with VideoDB

Upload the generated audio file (voiceover) to VideoDB and add it to the original product video using the

timeline feature⁠

audio = conn.upload(file_path=audio_file)

from videodb.timeline import Timeline

from videodb.asset import VideoAsset, AudioAsset

# Create a timeline object

timeline = Timeline(conn)

# Add the video asset to the timeline for playback

video_asset = VideoAsset(asset_id=video.id)

timeline.add_inline(asset=video_asset)

# Add the audio asset to the timeline for playback

audio_asset = AudioAsset(asset_id=audio.id)

timeline.add_overlay(start=0, asset=audio_asset)

🪄 Step 7: Review and Share

Preview the product video with the integrated voiceover to ensure it aligns with your vision. Once satisfied, share the video to showcase your product effectively.

from videodb import play_stream

stream_url = timeline.generate_stream()

play_stream(stream_url)

Output:

⁠

For more such explorations, refer to the

documentation of VideoDB⁠

and join the VideoDB community on

GitHub⁠

Discord⁠

for support and collaboration.

Feel free to share your creations via social media or other platforms to inspire others in the community. Join us on