model.py

import numpy as np
import cv2
import torch
import moviepy.editor as mp
from transformers import AutoModelForCausalLM, AutoTokenizer

# Load AI Pose Model
tokenizer = AutoTokenizer.from_pretrained("CompVis/posegpt")
model = AutoModelForCausalLM.from_pretrained("CompVis/posegpt")

# Memory Storage for Characters
character_memory = {}

def generate_stick_animation(story, character_name):
    global character_memory

    # Assign unique ID to character
    if character_name not in character_memory:
        character_memory[character_name] = {"pose": (250, 200), "size": 20}

    char_pose = character_memory[character_name]["pose"]

    # Convert story to keyframes using AI
    inputs = tokenizer(story, return_tensors="pt")
    output = model.generate(**inputs, max_length=50)

    # Generate Stick Figure Animation
    frames = []
    for i in range(20):  # More frames for smoother motion
        img = np.ones((500, 500, 3), dtype=np.uint8) * 255  # White background

        # Stick Figure Body
        cv2.line(img, (char_pose[0], char_pose[1] + i * 3), (char_pose[0], char_pose[1] + 100 + i * 3), (0, 0, 0), 5)
        cv2.circle(img, (char_pose[0], char_pose[1] - 20 + i * 3), 20, (0, 0, 0), -1)  # Head
        cv2.line(img, (char_pose[0] - 50, char_pose[1] + 50 + i * 3), (char_pose[0] + 50, char_pose[1] + 50 + i * 3), (0, 0, 0), 5)  # Arms

        # Black & White Filter
        gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

        frames.append(gray)

    return frames

# Extra Features
def add_camera_effects(frames, effect):
    if effect == "Shake":
        return [cv2.warpAffine(frame, np.float32([[1, 0, np.random.randint(-5, 5)], [0, 1, np.random.randint(-5, 5)]]), (500, 500)) for frame in frames]
    elif effect == "Zoom":
        return [cv2.resize(frame, (600, 600))[50:550, 50:550] for frame in frames]
    elif effect == "Slow Motion":
        return frames * 2  # Duplicate frames for slow-motion effect
    return frames

def add_background(frames, background):
    if background == "Dark Forest":
        return [cv2.addWeighted(frame, 0.8, cv2.imread("dark_forest.jpg", 0), 0.2, 0) for frame in frames]
    elif background == "Haunted House":
        return [cv2.addWeighted(frame, 0.8, cv2.imread("haunted_house.jpg", 0), 0.2, 0) for frame in frames]
    return frames

def add_sound(video_path, sound_type):
    if sound_type == "Horror":
        sound = mp.AudioFileClip("horror_music.mp3")
    elif sound_type == "Action":
        sound = mp.AudioFileClip("action_music.mp3")
    else:
        return video_path
    video = mp.VideoFileClip(video_path)
    final = video.set_audio(sound)
    final_path = video_path.replace(".mp4", "_sound.mp4")
    final.write_videofile(final_path)
    return final_path