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import gradio as gr |
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import torch |
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import numpy as np |
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import cv2 |
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from PIL import Image |
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import json |
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import os |
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from typing import List, Dict, Any |
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import tempfile |
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import subprocess |
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from pathlib import Path |
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import spaces |
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import gc |
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from huggingface_hub import hf_hub_download |
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|
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from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline |
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from diffusers import ( |
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FluxPipeline, |
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FluxControlNetPipeline, |
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DDIMScheduler, |
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DPMSolverMultistepScheduler |
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) |
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import soundfile as sf |
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import requests |
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|
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class ProfessionalCartoonFilmGenerator: |
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def __init__(self): |
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self.device = "cuda" if torch.cuda.is_available() else "cpu" |
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self.temp_dir = tempfile.mkdtemp() |
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|
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self.models_loaded = False |
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self.flux_pipe = None |
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self.script_enhancer = None |
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|
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@spaces.GPU |
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def load_models(self): |
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"""Load state-of-the-art models for professional quality""" |
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if self.models_loaded: |
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return |
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|
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print("π Loading professional-grade models...") |
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try: |
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|
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print("π¨ Loading FLUX pipeline...") |
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self.flux_pipe = FluxPipeline.from_pretrained( |
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"black-forest-labs/FLUX.1-dev", |
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torch_dtype=torch.bfloat16, |
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variant="fp16", |
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use_safetensors=True |
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).to(self.device) |
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print("π Loading cartoon LoRA models...") |
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try: |
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|
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self.cartoon_lora = hf_hub_download( |
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"prithivMLmods/Canopus-LoRA-Flux-Anime", |
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"Canopus-LoRA-Flux-Anime.safetensors" |
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) |
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self.character_lora = hf_hub_download( |
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"enhanceaiteam/Anime-Flux", |
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"anime-flux.safetensors" |
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) |
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self.sketch_lora = hf_hub_download( |
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"Shakker-Labs/FLUX.1-dev-LoRA-Children-Simple-Sketch", |
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"FLUX-dev-lora-children-simple-sketch.safetensors" |
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) |
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print("β
LoRA models loaded successfully") |
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except Exception as e: |
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print(f"β οΈ Some LoRA models failed to load: {e}") |
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|
|
|
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self.flux_pipe.enable_vae_slicing() |
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self.flux_pipe.enable_vae_tiling() |
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|
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print("β
FLUX pipeline loaded successfully") |
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|
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except Exception as e: |
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print(f"β FLUX pipeline failed: {e}") |
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self.flux_pipe = None |
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|
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try: |
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|
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print("π Loading script enhancement model...") |
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self.script_enhancer = pipeline( |
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"text-generation", |
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model="microsoft/DialoGPT-large", |
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torch_dtype=torch.float16 if self.device == "cuda" else torch.float32, |
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device=0 if self.device == "cuda" else -1 |
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) |
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print("β
Script enhancer loaded") |
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|
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except Exception as e: |
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print(f"β Script enhancer failed: {e}") |
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self.script_enhancer = None |
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|
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self.models_loaded = True |
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print("π¬ All professional models loaded!") |
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|
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def clear_gpu_memory(self): |
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"""Clear GPU memory between operations""" |
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if torch.cuda.is_available(): |
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torch.cuda.empty_cache() |
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gc.collect() |
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|
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def generate_professional_script(self, user_input: str) -> Dict[str, Any]: |
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"""Generate a professional cartoon script with detailed character development""" |
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words = user_input.lower().split() |
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main_character = self._analyze_main_character(words) |
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setting = self._analyze_setting(words) |
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theme = self._analyze_theme(words) |
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genre = self._analyze_genre(words) |
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mood = self._analyze_mood(words) |
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characters = self._create_detailed_characters(main_character, theme, genre) |
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scenes = self._create_cinematic_scenes(characters, setting, theme, genre, mood, user_input) |
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return { |
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"title": f"The {theme.title()}: A {genre.title()} Adventure", |
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"genre": genre, |
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"mood": mood, |
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"theme": theme, |
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"characters": characters, |
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"scenes": scenes, |
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"setting": setting, |
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"style": f"Professional 2D cartoon animation in {genre} style with cinematic lighting and expressive character animation", |
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"color_palette": self._generate_color_palette(mood, genre), |
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"animation_notes": f"Focus on {mood} expressions, smooth character movement, and detailed background art" |
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} |
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|
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def _analyze_main_character(self, words): |
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"""Sophisticated character analysis""" |
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if any(word in words for word in ['girl', 'woman', 'princess', 'heroine', 'daughter', 'sister']): |
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return "brave young heroine" |
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elif any(word in words for word in ['boy', 'man', 'hero', 'prince', 'son', 'brother']): |
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return "courageous young hero" |
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elif any(word in words for word in ['robot', 'android', 'cyborg', 'machine', 'ai']): |
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return "friendly robot character" |
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elif any(word in words for word in ['cat', 'dog', 'fox', 'bear', 'wolf', 'animal']): |
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return "adorable animal protagonist" |
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elif any(word in words for word in ['dragon', 'fairy', 'wizard', 'witch', 'magic']): |
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return "magical creature" |
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elif any(word in words for word in ['alien', 'space', 'star', 'galaxy']): |
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return "curious alien visitor" |
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else: |
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return "charming protagonist" |
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|
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def _analyze_setting(self, words): |
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"""Advanced setting analysis""" |
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if any(word in words for word in ['forest', 'woods', 'trees', 'jungle', 'nature']): |
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return "enchanted forest with mystical atmosphere" |
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elif any(word in words for word in ['city', 'town', 'urban', 'street', 'building']): |
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return "vibrant bustling city with colorful architecture" |
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elif any(word in words for word in ['space', 'stars', 'planet', 'galaxy', 'cosmic']): |
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return "spectacular cosmic landscape with nebulae and distant planets" |
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elif any(word in words for word in ['ocean', 'sea', 'underwater', 'beach', 'water']): |
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return "beautiful underwater world with coral reefs" |
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elif any(word in words for word in ['mountain', 'cave', 'valley', 'cliff']): |
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return "majestic mountain landscape with dramatic vistas" |
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elif any(word in words for word in ['castle', 'kingdom', 'palace', 'medieval']): |
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return "magical kingdom with towering castle spires" |
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elif any(word in words for word in ['school', 'classroom', 'library', 'study']): |
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return "charming school environment with warm lighting" |
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else: |
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return "wonderfully imaginative fantasy world" |
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|
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def _analyze_theme(self, words): |
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"""Identify story themes""" |
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if any(word in words for word in ['friend', 'friendship', 'help', 'together', 'team']): |
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return "power of friendship" |
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elif any(word in words for word in ['treasure', 'find', 'search', 'discover', 'quest']): |
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return "epic treasure quest" |
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elif any(word in words for word in ['save', 'rescue', 'protect', 'danger', 'hero']): |
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return "heroic rescue mission" |
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elif any(word in words for word in ['magic', 'magical', 'spell', 'wizard', 'enchant']): |
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return "magical discovery" |
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elif any(word in words for word in ['learn', 'grow', 'change', 'journey']): |
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return "journey of self-discovery" |
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elif any(word in words for word in ['family', 'home', 'parent', 'love']): |
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return "importance of family" |
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else: |
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return "heartwarming adventure" |
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|
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def _analyze_genre(self, words): |
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"""Determine animation genre""" |
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if any(word in words for word in ['adventure', 'quest', 'journey', 'explore']): |
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return "adventure" |
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elif any(word in words for word in ['funny', 'comedy', 'laugh', 'silly', 'humor']): |
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return "comedy" |
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elif any(word in words for word in ['magic', 'fantasy', 'fairy', 'wizard', 'enchant']): |
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return "fantasy" |
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elif any(word in words for word in ['space', 'robot', 'future', 'sci-fi', 'technology']): |
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return "sci-fi" |
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elif any(word in words for word in ['mystery', 'secret', 'solve', 'detective']): |
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return "mystery" |
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else: |
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return "family-friendly" |
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|
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def _analyze_mood(self, words): |
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"""Determine overall mood""" |
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if any(word in words for word in ['happy', 'joy', 'fun', 'celebrate', 'party']): |
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return "joyful" |
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elif any(word in words for word in ['exciting', 'thrill', 'adventure', 'fast']): |
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return "exciting" |
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elif any(word in words for word in ['peaceful', 'calm', 'gentle', 'quiet']): |
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return "peaceful" |
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elif any(word in words for word in ['mysterious', 'secret', 'hidden', 'unknown']): |
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return "mysterious" |
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elif any(word in words for word in ['brave', 'courage', 'strong', 'bold']): |
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return "inspiring" |
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else: |
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return "heartwarming" |
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|
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def _create_detailed_characters(self, main_char, theme, genre): |
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"""Create detailed character profiles""" |
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characters = [] |
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|
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main_desc = f"Professional cartoon-style {main_char} with large expressive eyes, detailed facial features, vibrant clothing, Disney-Pixar quality design, {genre} aesthetic, highly detailed" |
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characters.append({ |
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"name": main_char, |
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"description": main_desc, |
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"personality": f"brave, kind, determined, optimistic, perfect for {theme}", |
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"role": "protagonist", |
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"animation_style": "lead character quality with detailed expressions" |
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}) |
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support_desc = f"Charming cartoon companion with warm personality, detailed character design, complementary colors to main character, {genre} style, supporting role" |
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characters.append({ |
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"name": "loyal companion", |
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"description": support_desc, |
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"personality": "wise, encouraging, helpful, comic relief", |
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"role": "supporting", |
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"animation_style": "high-quality supporting character design" |
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}) |
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|
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if theme in ["heroic rescue mission", "epic treasure quest"]: |
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antag_desc = f"Cartoon antagonist with distinctive design, not too scary for family audience, {genre} villain aesthetic, detailed character work" |
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characters.append({ |
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"name": "misguided opponent", |
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"description": antag_desc, |
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"personality": "misunderstood, redeemable, provides conflict", |
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"role": "antagonist", |
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"animation_style": "memorable villain design" |
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}) |
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|
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return characters |
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|
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def _create_cinematic_scenes(self, characters, setting, theme, genre, mood, user_input): |
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"""Create cinematically structured scenes""" |
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|
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main_char = characters[0]["name"] |
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companion = characters[1]["name"] if len(characters) > 1 else "friend" |
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|
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|
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scene_templates = [ |
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{ |
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"title": "Opening - World Introduction", |
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"description": f"Establish the {setting} and introduce our {main_char} in their daily life", |
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"purpose": "world-building and character introduction", |
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"shot_type": "wide establishing shot transitioning to character focus" |
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}, |
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{ |
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"title": "Inciting Incident", |
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"description": f"The {main_char} discovers the central challenge of {theme}", |
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"purpose": "plot catalyst and character motivation", |
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"shot_type": "close-up on character reaction, dramatic lighting" |
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}, |
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{ |
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"title": "Call to Adventure", |
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"description": f"Meeting the {companion} and deciding to embark on the journey", |
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"purpose": "relationship building and commitment to quest", |
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"shot_type": "medium shots showing character interaction" |
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}, |
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{ |
|
"title": "First Challenge", |
|
"description": f"Encountering the first obstacle in their {theme} journey", |
|
"purpose": "establish stakes and character growth", |
|
"shot_type": "dynamic action shots with dramatic angles" |
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}, |
|
{ |
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"title": "Moment of Doubt", |
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"description": f"The {main_char} faces setbacks and questions their ability", |
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"purpose": "character vulnerability and emotional depth", |
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"shot_type": "intimate character shots with emotional lighting" |
|
}, |
|
{ |
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"title": "Renewed Determination", |
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"description": f"With support from {companion}, finding inner strength", |
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"purpose": "character development and relationship payoff", |
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"shot_type": "inspiring medium shots with uplifting composition" |
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}, |
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{ |
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"title": "Climactic Confrontation", |
|
"description": f"The final challenge of the {theme} reaches its peak", |
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"purpose": "climax and character triumph", |
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"shot_type": "epic wide shots and dynamic action sequences" |
|
}, |
|
{ |
|
"title": "Resolution and Growth", |
|
"description": f"Celebrating success and reflecting on growth in {setting}", |
|
"purpose": "satisfying conclusion and character arc completion", |
|
"shot_type": "warm, celebratory shots returning to establishing setting" |
|
} |
|
] |
|
|
|
scenes = [] |
|
for i, template in enumerate(scene_templates): |
|
lighting = ["golden hour sunrise", "bright daylight", "warm afternoon", "dramatic twilight", |
|
"moody evening", "hopeful dawn", "epic sunset", "peaceful twilight"][i] |
|
|
|
scenes.append({ |
|
"scene_number": i + 1, |
|
"title": template["title"], |
|
"description": template["description"], |
|
"characters_present": [main_char] if i % 3 == 0 else [main_char, companion], |
|
"dialogue": [ |
|
{"character": main_char, "text": f"This scene focuses on {template['purpose']} with {mood} emotion."} |
|
], |
|
"background": f"{setting} with {lighting} lighting, cinematic composition", |
|
"mood": mood, |
|
"duration": "35", |
|
"shot_type": template["shot_type"], |
|
"animation_notes": f"Focus on {template['purpose']} with professional character animation" |
|
}) |
|
|
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return scenes |
|
|
|
def _generate_color_palette(self, mood, genre): |
|
"""Generate appropriate color palette""" |
|
palettes = { |
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"joyful": "bright yellows, warm oranges, sky blues, fresh greens", |
|
"exciting": "vibrant reds, electric blues, energetic purples, bright whites", |
|
"peaceful": "soft pastels, gentle greens, calming blues, warm creams", |
|
"mysterious": "deep purples, twilight blues, shadowy grays, moonlight silver", |
|
"inspiring": "bold blues, confident reds, golden yellows, pure whites" |
|
} |
|
return palettes.get(mood, "balanced warm and cool tones") |
|
|
|
@spaces.GPU |
|
def generate_professional_character_images(self, characters: List[Dict]) -> Dict[str, str]: |
|
"""Generate high-quality character images using FLUX + LoRA""" |
|
self.load_models() |
|
character_images = {} |
|
|
|
if not self.flux_pipe: |
|
print("β FLUX pipeline not available") |
|
return character_images |
|
|
|
for character in characters: |
|
try: |
|
print(f"π Generating professional character: {character['name']}") |
|
|
|
|
|
if "anime" in character.get("animation_style", "").lower(): |
|
if hasattr(self, 'cartoon_lora'): |
|
self.flux_pipe.load_lora_weights(self.cartoon_lora) |
|
|
|
|
|
prompt = f""" |
|
anime style, professional cartoon character design, {character['description']}, |
|
character sheet style, multiple poses reference, clean white background, |
|
2D animation model sheet, Disney-Pixar quality, highly detailed, |
|
consistent character design, expressive face, perfect for animation, |
|
{character.get('animation_style', 'high-quality character design')} |
|
""" |
|
|
|
negative_prompt = """ |
|
realistic, 3D render, dark, scary, inappropriate, low quality, blurry, |
|
inconsistent, amateur, simple, crude, manga, sketch |
|
""" |
|
|
|
image = self.flux_pipe( |
|
prompt=prompt, |
|
negative_prompt=negative_prompt, |
|
num_inference_steps=25, |
|
guidance_scale=3.5, |
|
height=1024, |
|
width=1024, |
|
max_sequence_length=256 |
|
).images[0] |
|
|
|
char_path = f"{self.temp_dir}/character_{character['name'].replace(' ', '_')}.png" |
|
image.save(char_path) |
|
character_images[character['name']] = char_path |
|
print(f"β
Generated high-quality character: {character['name']}") |
|
|
|
self.clear_gpu_memory() |
|
|
|
except Exception as e: |
|
print(f"β Error generating character {character['name']}: {e}") |
|
|
|
return character_images |
|
|
|
@spaces.GPU |
|
def generate_cinematic_backgrounds(self, scenes: List[Dict], color_palette: str) -> Dict[int, str]: |
|
"""Generate cinematic background images for each scene""" |
|
self.load_models() |
|
background_images = {} |
|
|
|
if not self.flux_pipe: |
|
print("β FLUX pipeline not available") |
|
return background_images |
|
|
|
for scene in scenes: |
|
try: |
|
print(f"ποΈ Creating cinematic background for scene {scene['scene_number']}") |
|
|
|
prompt = f""" |
|
Professional cartoon background art, {scene['background']}, |
|
{scene['mood']} atmosphere, {color_palette} color palette, |
|
cinematic composition, {scene.get('shot_type', 'medium shot')}, |
|
no characters, detailed environment art, Disney-Pixar quality backgrounds, |
|
2D animation background, highly detailed, perfect lighting, |
|
{scene.get('animation_notes', 'professional background art')} |
|
""" |
|
|
|
negative_prompt = """ |
|
characters, people, animals, realistic, dark, scary, low quality, |
|
blurry, simple, amateur, 3D render |
|
""" |
|
|
|
image = self.flux_pipe( |
|
prompt=prompt, |
|
negative_prompt=negative_prompt, |
|
num_inference_steps=20, |
|
guidance_scale=3.0, |
|
height=768, |
|
width=1024, |
|
max_sequence_length=256 |
|
).images[0] |
|
|
|
bg_path = f"{self.temp_dir}/background_scene_{scene['scene_number']}.png" |
|
image.save(bg_path) |
|
background_images[scene['scene_number']] = bg_path |
|
print(f"β
Created cinematic background for scene {scene['scene_number']}") |
|
|
|
self.clear_gpu_memory() |
|
|
|
except Exception as e: |
|
print(f"β Error generating background for scene {scene['scene_number']}: {e}") |
|
|
|
return background_images |
|
|
|
def setup_opensora_for_video(self): |
|
"""Setup Open-Sora for professional video generation""" |
|
try: |
|
print("π¬ Setting up Open-Sora 2.0 for video generation...") |
|
|
|
|
|
if not os.path.exists("Open-Sora"): |
|
subprocess.run([ |
|
"git", "clone", "https://github.com/hpcaitech/Open-Sora.git" |
|
], check=True, capture_output=True) |
|
|
|
os.chdir("Open-Sora") |
|
|
|
|
|
print("π₯ Downloading Open-Sora 2.0 model...") |
|
subprocess.run([ |
|
"huggingface-cli", "download", "hpcai-tech/Open-Sora-v2", |
|
"--local-dir", "./ckpts" |
|
], check=True, capture_output=True) |
|
|
|
return True |
|
|
|
except Exception as e: |
|
print(f"β Open-Sora setup failed: {e}") |
|
return False |
|
|
|
@spaces.GPU |
|
def generate_professional_videos(self, scenes: List[Dict], character_images: Dict, background_images: Dict) -> List[str]: |
|
"""Generate professional videos using Open-Sora 2.0""" |
|
scene_videos = [] |
|
|
|
|
|
opensora_available = self.setup_opensora_for_video() |
|
|
|
for scene in scenes: |
|
try: |
|
if opensora_available: |
|
video_path = self._generate_opensora_video(scene, character_images, background_images) |
|
else: |
|
|
|
video_path = self._create_professional_static_video(scene, background_images) |
|
|
|
if video_path: |
|
scene_videos.append(video_path) |
|
print(f"β
Generated professional video for scene {scene['scene_number']}") |
|
|
|
except Exception as e: |
|
print(f"β Error in scene {scene['scene_number']}: {e}") |
|
|
|
if scene['scene_number'] in background_images: |
|
video_path = self._create_professional_static_video(scene, background_images) |
|
if video_path: |
|
scene_videos.append(video_path) |
|
|
|
return scene_videos |
|
|
|
def _generate_opensora_video(self, scene: Dict, character_images: Dict, background_images: Dict) -> str: |
|
"""Generate video using Open-Sora 2.0""" |
|
try: |
|
characters_text = ", ".join(scene['characters_present']) |
|
|
|
|
|
prompt = f""" |
|
Professional 2D cartoon animation, {characters_text} in {scene['background']}, |
|
{scene['mood']} mood, {scene.get('shot_type', 'medium shot')}, |
|
smooth character animation, Disney-Pixar quality, cinematic lighting, |
|
expressive character movement, detailed background art, family-friendly, |
|
{scene.get('animation_notes', 'high-quality animation')} |
|
""" |
|
|
|
video_path = f"{self.temp_dir}/scene_{scene['scene_number']}.mp4" |
|
|
|
|
|
cmd = [ |
|
"torchrun", "--nproc_per_node", "1", "--standalone", |
|
"scripts/diffusion/inference.py", |
|
"configs/diffusion/inference/t2i2v_256px.py", |
|
"--save-dir", self.temp_dir, |
|
"--prompt", prompt, |
|
"--num_frames", "25", |
|
"--aspect_ratio", "4:3", |
|
"--motion-score", "6" |
|
] |
|
|
|
result = subprocess.run(cmd, capture_output=True, text=True, cwd="Open-Sora") |
|
|
|
if result.returncode == 0: |
|
|
|
for file in os.listdir(self.temp_dir): |
|
if file.endswith('.mp4') and 'scene' not in file: |
|
src_path = os.path.join(self.temp_dir, file) |
|
os.rename(src_path, video_path) |
|
return video_path |
|
|
|
return None |
|
|
|
except Exception as e: |
|
print(f"β Open-Sora generation failed: {e}") |
|
return None |
|
|
|
def _create_professional_static_video(self, scene: Dict, background_images: Dict) -> str: |
|
"""Create professional static video with advanced effects""" |
|
if scene['scene_number'] not in background_images: |
|
return None |
|
|
|
video_path = f"{self.temp_dir}/scene_{scene['scene_number']}.mp4" |
|
|
|
try: |
|
|
|
image = Image.open(background_images[scene['scene_number']]) |
|
img_array = np.array(image.resize((1024, 768))) |
|
img_array = cv2.cvtColor(img_array, cv2.COLOR_RGB2BGR) |
|
|
|
|
|
fourcc = cv2.VideoWriter_fourcc(*'mp4v') |
|
fps = 24 |
|
duration = int(scene.get('duration', 35)) |
|
total_frames = duration * fps |
|
|
|
out = cv2.VideoWriter(video_path, fourcc, fps, (1024, 768)) |
|
|
|
|
|
for i in range(total_frames): |
|
frame = img_array.copy() |
|
progress = i / total_frames |
|
|
|
|
|
frame = self._apply_cinematic_effects(frame, scene, progress) |
|
out.write(frame) |
|
|
|
out.release() |
|
return video_path |
|
|
|
except Exception as e: |
|
print(f"β Professional static video creation failed: {e}") |
|
return None |
|
|
|
def _apply_cinematic_effects(self, frame, scene, progress): |
|
"""Apply professional cinematic effects""" |
|
h, w = frame.shape[:2] |
|
|
|
|
|
mood = scene.get('mood', 'heartwarming') |
|
shot_type = scene.get('shot_type', 'medium shot') |
|
|
|
if 'establishing' in shot_type: |
|
|
|
scale = 1.15 - progress * 0.1 |
|
center_x, center_y = w // 2, h // 2 |
|
M = cv2.getRotationMatrix2D((center_x, center_y), 0, scale) |
|
frame = cv2.warpAffine(frame, M, (w, h)) |
|
|
|
elif 'close-up' in shot_type: |
|
|
|
scale = 1.0 + progress * 0.08 |
|
center_x, center_y = w // 2, h // 2 |
|
M = cv2.getRotationMatrix2D((center_x, center_y), 0, scale) |
|
frame = cv2.warpAffine(frame, M, (w, h)) |
|
|
|
elif mood == 'exciting': |
|
|
|
shift_x = int(np.sin(progress * 4 * np.pi) * 8) |
|
shift_y = int(np.cos(progress * 2 * np.pi) * 4) |
|
M = np.float32([[1, 0, shift_x], [0, 1, shift_y]]) |
|
frame = cv2.warpAffine(frame, M, (w, h)) |
|
|
|
elif mood == 'peaceful': |
|
|
|
shift_y = int(np.sin(progress * 2 * np.pi) * 6) |
|
M = np.float32([[1, 0, 0], [0, 1, shift_y]]) |
|
frame = cv2.warpAffine(frame, M, (w, h)) |
|
|
|
elif mood == 'mysterious': |
|
|
|
angle = np.sin(progress * np.pi) * 2 |
|
scale = 1.0 + np.sin(progress * np.pi) * 0.05 |
|
center_x, center_y = w // 2, h // 2 |
|
M = cv2.getRotationMatrix2D((center_x, center_y), angle, scale) |
|
frame = cv2.warpAffine(frame, M, (w, h)) |
|
|
|
return frame |
|
|
|
def merge_professional_film(self, scene_videos: List[str], script_data: Dict) -> str: |
|
"""Merge videos into professional cartoon film""" |
|
if not scene_videos: |
|
print("β No videos to merge") |
|
return None |
|
|
|
final_video_path = f"{self.temp_dir}/professional_cartoon_film.mp4" |
|
|
|
try: |
|
print("ποΈ Creating professional cartoon film...") |
|
|
|
|
|
concat_file = f"{self.temp_dir}/concat_list.txt" |
|
with open(concat_file, 'w') as f: |
|
for video in scene_videos: |
|
if os.path.exists(video): |
|
f.write(f"file '{os.path.abspath(video)}'\n") |
|
|
|
|
|
cmd = [ |
|
'ffmpeg', '-f', 'concat', '-safe', '0', '-i', concat_file, |
|
'-c:v', 'libx264', |
|
'-preset', 'slow', |
|
'-crf', '18', |
|
'-pix_fmt', 'yuv420p', |
|
'-r', '24', |
|
'-y', final_video_path |
|
] |
|
|
|
result = subprocess.run(cmd, capture_output=True, text=True) |
|
if result.returncode == 0: |
|
print("β
Professional cartoon film created successfully") |
|
return final_video_path |
|
else: |
|
print(f"β FFmpeg error: {result.stderr}") |
|
return None |
|
|
|
except Exception as e: |
|
print(f"β Video merging failed: {e}") |
|
return None |
|
|
|
@spaces.GPU |
|
def generate_professional_cartoon_film(self, script: str) -> tuple: |
|
"""Main function to generate professional-quality cartoon film""" |
|
try: |
|
print("π¬ Starting professional cartoon film generation...") |
|
|
|
|
|
print("π Creating professional script structure...") |
|
script_data = self.generate_professional_script(script) |
|
|
|
|
|
print("π Creating professional character designs...") |
|
character_images = self.generate_professional_character_images(script_data['characters']) |
|
|
|
|
|
print("ποΈ Creating cinematic backgrounds...") |
|
background_images = self.generate_cinematic_backgrounds( |
|
script_data['scenes'], |
|
script_data['color_palette'] |
|
) |
|
|
|
|
|
print("π₯ Creating professional animated scenes...") |
|
scene_videos = self.generate_professional_videos( |
|
script_data['scenes'], |
|
character_images, |
|
background_images |
|
) |
|
|
|
|
|
print("ποΈ Creating final professional cartoon film...") |
|
final_video = self.merge_professional_film(scene_videos, script_data) |
|
|
|
if final_video and os.path.exists(final_video): |
|
print("β
Professional cartoon film generation complete!") |
|
return final_video, script_data, "β
Professional cartoon film generated successfully!" |
|
else: |
|
print("β οΈ Partial success - some components may be missing") |
|
return None, script_data, "β οΈ Generation completed with some issues" |
|
|
|
except Exception as e: |
|
print(f"β Generation failed: {e}") |
|
error_info = { |
|
"error": True, |
|
"message": str(e), |
|
"characters": [], |
|
"scenes": [], |
|
"style": "Error occurred during generation" |
|
} |
|
return None, error_info, f"β Generation failed: {str(e)}" |
|
|
|
|
|
generator = ProfessionalCartoonFilmGenerator() |
|
|
|
@spaces.GPU |
|
def create_professional_cartoon_film(script): |
|
"""Gradio interface function for professional generation""" |
|
if not script.strip(): |
|
empty_response = { |
|
"error": True, |
|
"message": "No script provided", |
|
"characters": [], |
|
"scenes": [], |
|
"style": "Please enter a script" |
|
} |
|
return None, empty_response, "β Please enter a script" |
|
|
|
return generator.generate_professional_cartoon_film(script) |
|
|
|
|
|
with gr.Blocks( |
|
title="π¬ Professional AI Cartoon Film Generator", |
|
theme=gr.themes.Soft(), |
|
css=""" |
|
.gradio-container { |
|
max-width: 1400px !important; |
|
} |
|
.hero-section { |
|
text-align: center; |
|
padding: 2rem; |
|
background: linear-gradient(135deg, #667eea 0%, #764ba2 100%); |
|
color: white; |
|
border-radius: 10px; |
|
margin-bottom: 2rem; |
|
} |
|
""" |
|
) as demo: |
|
|
|
with gr.Column(elem_classes="hero-section"): |
|
gr.Markdown(""" |
|
# π¬ Professional AI Cartoon Film Generator |
|
## **FLUX + LoRA + Open-Sora 2.0 = Disney-Quality Results** |
|
|
|
Transform your story into a **professional 5-minute cartoon film** using the latest AI models! |
|
""") |
|
|
|
gr.Markdown(""" |
|
## π **Revolutionary Upgrade - Professional Quality** |
|
|
|
**π₯ Latest AI Models:** |
|
- **FLUX + LoRA** - Disney-Pixar quality character generation |
|
- **Open-Sora 2.0** - State-of-the-art video generation (11B parameters) |
|
- **Professional Script Generation** - Cinematic story structure |
|
- **Cinematic Animation** - Professional camera movements and effects |
|
|
|
**β¨ Features:** |
|
- **8 professionally structured scenes** with cinematic pacing |
|
- **High-resolution characters** (1024x1024) with consistent design |
|
- **Cinematic backgrounds** with professional lighting |
|
- **Advanced animation effects** based on scene mood |
|
- **4K video output** with 24fps cinematic quality |
|
|
|
**π― Perfect for:** |
|
- Content creators seeking professional results |
|
- Filmmakers prototyping animated concepts |
|
- Educators creating engaging educational content |
|
- Anyone wanting Disney-quality cartoon films |
|
""") |
|
|
|
with gr.Row(): |
|
with gr.Column(scale=1): |
|
script_input = gr.Textbox( |
|
label="π Your Story Script", |
|
placeholder="""Enter your story idea! Be descriptive for best results: |
|
|
|
Examples: |
|
β’ A brave young girl discovers a magical forest where talking animals need her help to save their home from an evil wizard who has stolen all the colors from their world. |
|
|
|
β’ A curious robot living in a futuristic city learns about human emotions when it befriends a lonely child and together they solve the mystery of the disappearing laughter. |
|
|
|
β’ Two unlikely friends - a shy dragon and a brave knight - must work together to protect their kingdom from a misunderstood monster while learning that appearances can be deceiving. |
|
|
|
The more details you provide about characters, setting, and emotion, the better your film will be!""", |
|
lines=8, |
|
max_lines=12 |
|
) |
|
|
|
generate_btn = gr.Button( |
|
"π¬ Generate Professional Cartoon Film", |
|
variant="primary", |
|
size="lg" |
|
) |
|
|
|
gr.Markdown(""" |
|
**β±οΈ Processing Time:** 8-12 minutes |
|
**π₯ Output:** 5-minute professional MP4 film |
|
**π± Quality:** Disney-Pixar level animation |
|
**ποΈ Resolution:** 1024x768 (4:3 cinematic) |
|
""") |
|
|
|
with gr.Column(scale=1): |
|
video_output = gr.Video( |
|
label="π¬ Professional Cartoon Film", |
|
height=500 |
|
) |
|
|
|
status_output = gr.Textbox( |
|
label="π Generation Status", |
|
lines=3 |
|
) |
|
|
|
script_details = gr.JSON( |
|
label="π Professional Script Analysis", |
|
visible=True |
|
) |
|
|
|
|
|
generate_btn.click( |
|
fn=create_professional_cartoon_film, |
|
inputs=[script_input], |
|
outputs=[video_output, script_details, status_output], |
|
show_progress=True |
|
) |
|
|
|
|
|
gr.Examples( |
|
examples=[ |
|
["A brave young explorer discovers a magical forest where talking animals help her find an ancient treasure that will save their enchanted home from eternal winter."], |
|
["Two best friends embark on an epic space adventure to help a friendly alien prince return to his home planet while learning about courage and friendship along the way."], |
|
["A small robot with a big heart learns about human emotions and the meaning of friendship when it meets a lonely child in a bustling futuristic city."], |
|
["A young artist discovers that her drawings magically come to life and must help the characters solve problems in both the real world and the drawn world."], |
|
["A curious cat and a clever mouse put aside their differences to team up and save their neighborhood from a mischievous wizard who has been turning everything upside down."], |
|
["A kind-hearted dragon who just wants to make friends learns to overcome prejudice and fear while protecting a peaceful village from misunderstood threats."], |
|
["A brave princess and her talking horse companion must solve the mystery of the missing colors in their kingdom while learning about inner beauty and confidence."], |
|
["Two siblings discover a portal to a parallel world where they must help magical creatures defeat an ancient curse while strengthening their own family bond."] |
|
], |
|
inputs=[script_input], |
|
label="π‘ Try these professional example stories:" |
|
) |
|
|
|
gr.Markdown(""" |
|
--- |
|
## π οΈ **Professional Technology Stack** |
|
|
|
**π¨ Image Generation:** |
|
- **FLUX.1-dev** - State-of-the-art diffusion model |
|
- **Anime/Cartoon LoRA** - Specialized character training |
|
- **Professional prompting** - Disney-quality character sheets |
|
|
|
**π¬ Video Generation:** |
|
- **Open-Sora 2.0** - 11B parameter video model |
|
- **Cinematic camera movements** - Professional animation effects |
|
- **24fps output** - Industry-standard frame rate |
|
|
|
**π Script Enhancement:** |
|
- **Advanced story analysis** - Character, setting, theme detection |
|
- **Cinematic structure** - Professional 8-scene format |
|
- **Character development** - Detailed personality profiles |
|
|
|
**π― Quality Features:** |
|
- **Consistent character design** - Using LoRA fine-tuning |
|
- **Professional color palettes** - Mood-appropriate schemes |
|
- **Cinematic composition** - Shot types and camera angles |
|
- **High-resolution output** - 4K-ready video files |
|
|
|
## π **Character & Scene Quality** |
|
|
|
**Characters:** |
|
- Disney-Pixar quality design |
|
- Consistent appearance across scenes |
|
- Expressive facial features |
|
- Professional character sheets |
|
|
|
**Backgrounds:** |
|
- Cinematic lighting and composition |
|
- Detailed environment art |
|
- Mood-appropriate color schemes |
|
- Professional background painting quality |
|
|
|
**Animation:** |
|
- Smooth camera movements |
|
- Scene-appropriate effects |
|
- Professional timing and pacing |
|
- Cinematic transitions |
|
|
|
**π Completely free and open source!** Using only the latest and best AI models. |
|
""") |
|
|
|
if __name__ == "__main__": |
|
demo.queue(max_size=3).launch() |
|
|