videogen_api / main.py
Lakpriya Seneviratna
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import requests
import praw
import json
import cv2
import numpy as np
import textwrap
from gtts import gTTS
from pydub import AudioSegment
import subprocess
import re
import os
import random
import time
import sys
import uuid
from googleapiclient.discovery import build
from googleapiclient.errors import HttpError
from googleapiclient.http import MediaFileUpload
from oauth2client.client import flow_from_clientsecrets
from oauth2client.file import Storage
from oauth2client.tools import run_flow
from google.auth.transport.requests import Request
# Define the output folder path
output_folder = 'output'
# Constants
SCOPES = ["https://www.googleapis.com/auth/youtube.upload"]
CLIENT_SECRETS_FILE = "client_secrets.json" # Update with your client_secrets.json file path
YOUTUBE_UPLOAD_SCOPE = "https://www.googleapis.com/auth/youtube.upload"
DRIVE_SCOPE = "https://www.googleapis.com/auth/drive"
YOUTUBE_API_SERVICE_NAME = "youtube"
YOUTUBE_API_VERSION = "v3"
MAX_RETRIES = 10
RETRIABLE_STATUS_CODES = [500, 502, 503, 504]
ELEVENLABS_KEY = "55bfc10fb7eecae379f73e6740807101"
# Check if the folder exists, if not, create it
if not os.path.exists(output_folder):
os.makedirs(output_folder)
banned_words = ["fuck", "pussy", "ass", "porn", "gay", "dick", "cock", "kill", "fucking", "shit", "bitch", "bullshit", "asshole","douchebag", "bitch", "motherfucker", "nigga","cunt", "whore", "piss", "shoot", "bomb", "palestine", "israel" ]
def contains_banned_word(text, banned_words):
for word in banned_words:
if word in text.lower():
return True
return False
def fetch_reddit_data(subreddit_name):
# Reddit API Credentials
client_id = 'TIacEazZS9FHWzDZ3T-3cA'
client_secret = '6Urwdiqo_cC8Gt040K_rBhnR3r8CLg'
user_agent = 'script by u/lakpriya1'
# Initialize PRAW with your credentials
reddit = praw.Reddit(client_id=client_id, client_secret=client_secret, user_agent=user_agent)
subreddit = reddit.subreddit(subreddit_name)
for _ in range(10): # Limit the number of attempts to 10
post = subreddit.random()
# Check if the title contains a pattern resembling a URL
if post and not re.search(r'\w+\.\w+', post.title) and not contains_banned_word(post.title, banned_words) and not len(post.title) < 50:
post_data = {'title': post.title}
with open('top_post.json', 'w') as outfile:
json.dump(post_data, outfile, indent=4)
print("Top post data saved to top_post.json")
return # Exit after finding a suitable post
print("No suitable post found without a URL-like string in the title.")
def read_json(filename):
print("Reading data from", filename)
with open(filename, 'r') as file:
data = json.load(file)
return data
def wrap_text(text, wrap_width):
return textwrap.wrap(text, width=wrap_width)
def resize_background_image(image_path, frame_width, frame_height):
print("Resizing background image")
image = cv2.imread(image_path)
h, w = image.shape[:2]
scale = max(frame_width / w, frame_height / h)
new_w, new_h = int(w * scale), int(h * scale)
resized_image = cv2.resize(image, (new_w, new_h))
# Cropping the resized image to fill the frame
startx = new_w // 2 - (frame_width // 2)
starty = new_h // 2 - (frame_height // 2)
cropped_image = resized_image[starty:starty+frame_height, startx:startx+frame_width]
return cropped_image
def put_text_with_stroke(frame, text, position, font_scale, line_height, wrap_width, font_color=(255, 255, 255), stroke_color=(0, 0, 0)):
font = cv2.FONT_HERSHEY_COMPLEX
lines = wrap_text(text, wrap_width)
# Calculate the total height of the text block
total_text_height = line_height * len(lines)
# Starting Y position to center text vertically
start_y = (frame.shape[0] - total_text_height) // 2
for line in lines:
text_size = cv2.getTextSize(line, font, font_scale, 1)[0]
# Calculate x coordinate for center alignment
text_x = (frame.shape[1] - text_size[0]) // 2
text_y = start_y + line_height
# Draw text stroke (increase thickness for a bolder stroke)
cv2.putText(frame, line, (text_x, text_y), font, font_scale, stroke_color, 8, cv2.LINE_AA)
# Draw original text on top
cv2.putText(frame, line, (text_x, text_y), font, font_scale, font_color, 2, cv2.LINE_AA)
start_y += line_height
def create_video_from_title(title, background_image, output_filename, audio_duration):
print("Creating video from title")
# Video properties
fps = 24
frame_width, frame_height = 720, 1280 # 9:16 aspect ratio
frame_count = audio_duration * fps
# Logo images
top_logo = load_logo('logo.png', frame_width, frame_height, 'top')
bottom_logo = load_logo('sub.png', frame_width, frame_height, 'bottom')
# OpenCV VideoWriter
fourcc = cv2.VideoWriter_fourcc(*'mp4v')
out = cv2.VideoWriter(output_filename, fourcc, fps, (frame_width, frame_height))
# Resize the background image
background = resize_background_image(background_image, frame_width, frame_height)
for i in range(int(np.floor(frame_count))):
frame = background.copy() # Use the resized background image
# Overlay logos
frame = overlay_logo(frame, top_logo)
frame = overlay_logo(frame, bottom_logo)
# Add title to frame with text wrapping and highlight
put_text_with_stroke(frame, title, (50, 500), 1, 50, 25, font_color=(255, 255, 255), stroke_color=(0, 0, 0)) # Adjust wrap_width and line_height as needed
out.write(frame) # Write the frame to the video
out.release()
def fetch_random_nature_image(api_key):
print("Fetching random nature image from Unsplash")
url = f"https://api.unsplash.com/photos/random?query=nature&client_id={api_key}"
response = requests.get(url)
if response.status_code == 200:
img_url = response.json()['urls']['regular']
img_data = requests.get(img_url).content
with open('nature_background.jpg', 'wb') as handler:
handler.write(img_data)
return 'nature_background.jpg'
else:
print("Failed to fetch image from Unsplash")
return None
def text_to_speech(text, output_file):
print("Converting text to speech")
tts = gTTS(text=text, lang='en')
tts.save(output_file)
return output_file
def get_audio_duration(audio_file):
print("Getting audio duration")
audio = AudioSegment.from_mp3(audio_file)
return len(audio) / 1000.0 # Convert to seconds
def combine_audio_video(video_file, audio_file, output_file, audio_delay_seconds=0.3):
# Construct the full path for the output file
output_file = os.path.join(output_folder, output_file)
# Add a delay to the audio start
cmd = f'ffmpeg -i "{video_file}" -itsoffset {audio_delay_seconds} -i "{audio_file}" -c:v copy -c:a aac -strict experimental -map 0:v:0 -map 1:a:0 "{output_file}"'
subprocess.call(cmd, shell=True)
print("Successfully made the video:", output_file)
def load_logo(logo_path, frame_width, frame_height, position='top'):
logo = cv2.imread(logo_path, cv2.IMREAD_UNCHANGED) # Load with alpha channel
logo_height, logo_width = logo.shape[:2]
# Scaling down the logo if it's too big
scale_factor = min(1, frame_width / 3 / logo_width, frame_height / 10 / logo_height)
new_size = (int(logo_width * scale_factor*1.3), int(logo_height * scale_factor*1.3))
logo = cv2.resize(logo, new_size, interpolation=cv2.INTER_AREA)
# Positioning
x_center = frame_width // 2 - logo.shape[1] // 2
if position == 'top':
y_pos = 100 # 10 pixels from the top
else: # 'bottom'
y_pos = frame_height - logo.shape[0] - 100 # 10 pixels from the bottom
return logo, (x_center, y_pos)
def overlay_logo(frame, logo_info):
logo, (x, y) = logo_info
y1, y2 = y, y + logo.shape[0]
x1, x2 = x, x + logo.shape[1]
if logo.shape[2] == 4: # If the logo has an alpha channel
alpha_logo = logo[:, :, 3] / 255.0
alpha_frame = 1.0 - alpha_logo
for c in range(0, 3):
frame[y1:y2, x1:x2, c] = (alpha_logo * logo[:, :, c] +
alpha_frame * frame[y1:y2, x1:x2, c])
else: # If the logo does not have an alpha channel
frame[y1:y2, x1:x2] = logo
return frame
def get_authenticated_service():
flow = flow_from_clientsecrets(CLIENT_SECRETS_FILE, scope=YOUTUBE_UPLOAD_SCOPE)
storage = Storage(f"{sys.argv[0]}-oauth2.json")
credentials = storage.get()
if credentials is None or credentials.invalid:
credentials = run_flow(flow, storage)
return build(YOUTUBE_API_SERVICE_NAME, YOUTUBE_API_VERSION, credentials=credentials)
def upload_video_to_drive(video_file, folder_id=None):
"""Uploads a video to Google Drive."""
# Check if the credentials are stored
storage = Storage(f"{sys.argv[0]}-oauth2.json")
credentials = storage.get()
# If credentials are not available or are invalid, run the flow
if not credentials or credentials.invalid:
flow = flow_from_clientsecrets(CLIENT_SECRETS_FILE, scope=[DRIVE_SCOPE])
credentials = run_flow(flow, storage)
service = build('drive', 'v3', credentials=credentials)
file_metadata = {
'name': os.path.basename(video_file),
'mimeType': 'video/mp4'
}
if folder_id:
file_metadata['parents'] = [folder_id]
media = MediaFileUpload(video_file, mimetype='video/mp4', resumable=True)
file = service.files().create(body=file_metadata, media_body=media, fields='id').execute()
print('File ID: %s' % file.get('id'))
def initialize_upload(youtube, options):
tags = None
if 'keywords' in options and options['keywords']:
tags = options['keywords'].split(",")
body = dict(
snippet=dict(
title=options['title'],
description=options['description'],
tags=tags,
categoryId=options['category']
),
status=dict(
privacyStatus=options['privacyStatus']
)
)
# Call the API's videos.insert method to create and upload the video.
insert_request = youtube.videos().insert(
part=",".join(body.keys()),
body=body,
# The chunksize parameter specifies the size of each chunk of data, in
# bytes, that will be uploaded at a time. Set a higher value for
# reliable connections as fewer chunks lead to faster uploads. Set a lower
# value for better recovery on less reliable connections.
#
# Setting "chunksize" equal to -1 in the code below means that the entire
# file will be uploaded in a single HTTP request. (If the upload fails,
# it will still be retried where it left off.) This is usually a best
# practice, but if you're using Python older than 2.6 or if you're
# running on App Engine, you should set the chunksize to something like
# 1024 * 1024 (1 megabyte).
media_body=MediaFileUpload(options["file"], chunksize=-1, resumable=True)
)
resumable_upload(insert_request)
# This method implements an exponential backoff strategy to resume a
# failed upload.
def resumable_upload(insert_request):
response = None
error = None
retry = 0
while response is None:
try:
print("Uploading file...")
status, response = insert_request.next_chunk()
if response is not None:
if 'id' in response:
print("Video id '%s' was successfully uploaded." % response['id'])
else:
exit("The upload failed with an unexpected response: %s" % response)
except HttpError as e:
if e.resp.status in RETRIABLE_STATUS_CODES:
error = "A retriable HTTP error %d occurred:\n%s" % (e.resp.status,
e.content)
else:
raise
# except RETRIABLE_EXCEPTIONS as e:
# error = "A retriable error occurred: %s" % e
if error is not None:
print(error)
retry += 1
if retry > MAX_RETRIES:
exit("No longer attempting to retry.")
max_sleep = 2 ** retry
sleep_seconds = random.random() * max_sleep
print("Sleeping %f seconds and then retrying..." % sleep_seconds)
time.sleep(sleep_seconds)
def eleven_labs_text_to_speech(text, output_file):
voice_ids = {
"ndntWUKwYjgJGYkvF6at",
"SVLJSgUbrKWfY8HvF2Xd",
"sjdiTCylizqR74A3ssv4",
}
# randomly pick one of the voices
voice_id = random.choice(list(voice_ids))
url = f"https://api.elevenlabs.io/v1/text-to-speech/{voice_id}"
headers = {
"Accept": "audio/mpeg",
"Content-Type": "application/json",
"xi-api-key": ELEVENLABS_KEY
}
data = {
"text": text,
"model_id": "eleven_monolingual_v1",
"voice_settings": {
"stability": 0.5,
"similarity_boost": 0.5,
"speed": 0.3,
}
}
response = requests.post(url, json=data, headers=headers)
if response.status_code == 200:
with open(output_file, 'wb') as f:
for chunk in response.iter_content(chunk_size=1024):
f.write(chunk)
print(f"Audio content written to {output_file}")
else:
print(f"Failed to synthesize speech: {response.content}")
api_key = 'VhLwkCKi3iu5Pf37LXfz-Lp7hTW69EV8uw_hkLAPkiA' # Replace with your Unsplash API key
background_image = fetch_random_nature_image(api_key)
if background_image:
# Example usage
fetch_reddit_data('Glitch_in_the_Matrix')
# Read data from JSON
reddit_data = read_json('top_post.json') # Change filename if needed
title = reddit_data.get('title')
filename = "video_" + str(uuid.uuid4())
# Convert text to speech
# voiceover_file = text_to_speech(title, 'voiceover.mp3')
voiceover_file = eleven_labs_text_to_speech(title, 'voiceover.mp3')
# Get audio duration
audio_duration = get_audio_duration('voiceover.mp3')
# Create and save the video
create_video_from_title(title, background_image, "reddit_post_video_cv2.mp4", audio_duration)
# Combine audio and video
combine_audio_video('reddit_post_video_cv2.mp4', 'voiceover.mp3', filename + '.mp4')
options = {
'file': 'output/'+ filename + '.mp4',
'title': "Amazing Facts Revealed: Unveiling the World's Hidden Wonders #shorts",
'description': "Welcome to our latest YouTube video, 'Amazing Facts Revealed: Unveiling the World's Hidden Wonders'! In this enthralling episode, we dive deep into the most astonishing and lesser-known facts about our world. From the mysteries of the deep sea to the enigmas of outer space, we cover it all. Get ready to be amazed by incredible scientific discoveries, historical secrets, and mind-blowing natural phenomena. Each fact is meticulously researched and presented with stunning visuals and engaging narration. Don't forget to like, share, and subscribe for more fascinating content. Stay curious and let's explore the wonders of our world together #shorts",
'category': "22",
'keywords': "facts, shorts, funny",
'privacyStatus': "private"
}
# try:
# youtube = get_authenticated_service()
# initialize_upload(youtube, options)
# upload_video_to_drive('output/'+ filename + '.mp4','1t2lcYNLgz6FTeabzccY_06rvcnTGdQiR')
# except HttpError as e:
# print("An HTTP error %d occurred:\n%s" % (e.resp.status, e.content))