Delete urdu_tts_video.py

urdu_tts_video.py

@@ -1,135 +0,0 @@
-import gradio as gr
-import os
-import cv2
-import ffmpeg
-import numpy as np
-from gtts import gTTS
-from diffusers import StableDiffusionPipeline
-import torch
-
-# Ensure required folders exist
-os.makedirs("generated_images", exist_ok=True)
-os.makedirs("output", exist_ok=True)
-
-# Load Stable Diffusion for image generation
-model_id = "runwayml/stable-diffusion-v1-5"
-pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float32)
-pipe.safety_checker = None  # Disable safety checker
-
-# Global variable to store generated TTS audio path
-global_audio_path = None
-
-
-### 🗣️ TEXT-TO-SPEECH FUNCTION ###
-def text_to_speech(script_file):
-    if script_file is None:
-        return None, "⚠️ Please upload an Urdu script file!"
-    
-    with open(script_file.name, "r", encoding="utf-8") as f:
-        urdu_text = f.read().strip()
-
-    audio_path = "output/urdu_audio.mp3"
-    tts = gTTS(text=urdu_text, lang="ur")
-    tts.save(audio_path)
-
-    global global_audio_path
-    global_audio_path = audio_path
-
-    return audio_path, "✅ Audio generated successfully!"
-
-
-### 🏞️ IMAGE GENERATION FUNCTION ###
-def generate_images(script_file, num_images):
-    if script_file is None:
-        return None, "⚠️ Please upload a script file!"
-    
-    num_images = int(num_images)
-
-    with open(script_file.name, "r", encoding="utf-8") as f:
-        text_lines = f.read().split("\n\n")  # Splitting scenes by double newlines
-    
-    image_paths = []
-    for i, scene in enumerate(text_lines[:num_images]):
-        prompt = f"Scene {i+1}: {scene.strip()}"
-        image = pipe(prompt).images[0]
-        image_path = f"generated_images/image_{i+1}.png"
-        image.save(image_path)
-        image_paths.append(image_path)
-    
-    return image_paths, "✅ Images generated successfully!"
-
-
-### 🎥 VIDEO CREATION FUNCTION ###
-def images_to_video(image_paths, fps=1):
-    if not image_paths:
-        return None
-    
-    frame = cv2.imread(image_paths[0])
-    height, width, layers = frame.shape
-
-    video_path = "output/generated_video.mp4"
-    fourcc = cv2.VideoWriter_fourcc(*"mp4v")
-    video = cv2.VideoWriter(video_path, fourcc, fps, (width, height))
-
-    for image in image_paths:
-        frame = cv2.imread(image)
-        video.write(frame)
-    
-    video.release()
-    return video_path
-
-
-### 🔊 AUDIO-VIDEO MERGE FUNCTION ###
-def merge_audio_video(video_path):
-    if global_audio_path is None:
-        return None, "⚠️ No audio found! Please generate Urdu TTS first."
-    
-    final_video_path = "output/final_video.mp4"
-    
-    video = ffmpeg.input(video_path)
-    audio = ffmpeg.input(global_audio_path)
-    
-    ffmpeg.output(video, audio, final_video_path, vcodec="libx264", acodec="aac").run(overwrite_output=True)
-    
-    return final_video_path, "✅ Video with Urdu voice-over generated successfully!"
-
-
-### 🎬 FINAL VIDEO GENERATION PIPELINE ###
-def generate_final_video(script_file, num_images):
-    if script_file is None:
-        return None, "⚠️ Please upload a script file for image generation!"
-    
-    image_paths, img_msg = generate_images(script_file, num_images)
-    if not image_paths:
-        return None, img_msg
-
-    video_path = images_to_video(image_paths, fps=1)
-    final_video_path, vid_msg = merge_audio_video(video_path)
-    
-    return final_video_path, vid_msg
-
-
-### 🚀 GRADIO UI ###
-with gr.Blocks() as demo:
-    gr.Markdown("## 🎤 Urdu Text-to-Speech & AI Video Generator")
-    
-    # TTS Section
-    with gr.Tab("🗣️ Urdu Text-to-Speech"):
-        script_file_tts = gr.File(label="📂 Upload Urdu Script for Audio", type="filepath")
-        generate_audio_btn = gr.Button("🎙️ Generate Audio", variant="primary")
-        audio_output = gr.Audio(label="🔊 Urdu Speech Output", interactive=False)
-        audio_status = gr.Textbox(label="ℹ️ Status", interactive=False)
-    
-    generate_audio_btn.click(text_to_speech, inputs=[script_file_tts], outputs=[audio_output, audio_status])
-    
-    # Video Generation Section
-    with gr.Tab("🎥 AI Video Generator"):
-        script_file_video = gr.File(label="📂 Upload Urdu Script for Images", type="filepath")
-        num_images = gr.Number(label="📸 Number of Scenes", value=3, minimum=1, maximum=10, step=1)
-        generate_video_btn = gr.Button("🎬 Generate Video", variant="primary")
-        video_output = gr.Video(label="🎞️ Generated Video")
-        video_status = gr.Textbox(label="ℹ️ Status", interactive=False)
-    
-    generate_video_btn.click(generate_final_video, inputs=[script_file_video, num_images], outputs=[video_output, video_status])
-
-demo.launch()