4.2.3 Dynamic Scene Generation and Integration

AI MONSTER's technology allows for the deep integration of monsters with their environments, creating cohesive and immersive scenes.

1. Procedural Environment Generation

2. AI-driven creation of entire ecosystems and habitats suited to the monsters.

3. Dynamic adjustment of environments based on monster characteristics and story requirements.

4. Lighting and Atmosphere Adaptation

5. Automatic adjustment of scene lighting to enhance the mood and highlight monster features.

6. Generation of atmospheric effects (fog, particles, etc.) that interact realistically with monsters.

7. Composite Shot Optimization

8. AI analysis of live-action footage to determine optimal monster placement and interaction.

9. Real-time adjustment of monster renders to match plate photography lighting and camera movement.

Example: AI-Powered Scene Composition System

import cv2
import numpy as np
from transformers import SegformerImageProcessor, SegformerForSemanticSegmentation

class AISceneCompositor:
    def __init__(self):
        self.processor = SegformerImageProcessor.from_pretrained("nvidia/segformer-b5-finetuned-ade-640-640")
        self.model = SegformerForSemanticSegmentation.from_pretrained("nvidia/segformer-b5-finetuned-ade-640-640")

    def analyze_plate(self, image_path):
        image = cv2.imread(image_path)
        image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
        inputs = self.processor(images=image, return_tensors="pt")
        outputs = self.model(**inputs)
        logits = outputs.logits.squeeze()
        segmentation = logits.argmax(dim=0).numpy()
        return image, segmentation

    def find_monster_placement(self, segmentation, monster_size):
        # Simplified placement strategy - find the largest non-sky area
        ground = (segmentation != self.model.config.id2label['sky'])
        kernel = np.ones((monster_size, monster_size), np.uint8)
        possible_placements = cv2.dilate(ground.astype(np.uint8), kernel)
        best_location = np.unravel_index(possible_placements.argmax(), possible_placements.shape)
        return best_location

    def adjust_monster_lighting(self, monster_render, plate_image, location):
        # Simplified lighting adjustment - match average color around placement
        y, x = location
        surrounding = plate_image[y-50:y+50, x-50:x+50]
        avg_color = surrounding.mean(axis=(0, 1))
        adjusted_render = monster_render * avg_color / 255
        return adjusted_render.astype(np.uint8)

    def composite_shot(self, plate_path, monster_render_path):
        plate, segmentation = self.analyze_plate(plate_path)
        monster = cv2.imread(monster_render_path, cv2.IMREAD_UNCHANGED)
        
        placement = self.find_monster_placement(segmentation, monster.shape[0])
        adjusted_monster = self.adjust_monster_lighting(monster, plate, placement)
        
        y, x = placement
        h, w = monster.shape[:2]
        roi = plate[y:y+h, x:x+w]
        
        # Simple alpha compositing
        alpha = adjusted_monster[:, :, 3] / 255.0
        for c in range(3):
            roi[:, :, c] = roi[:, :, c] * (1 - alpha) + adjusted_monster[:, :, c] * alpha
        
        plate[y:y+h, x:x+w] = roi
        return plate

# Usage
compositor = AISceneCompositor()
composite = compositor.composite_shot("beach_scene.jpg", "sea_monster_render.png")
cv2.imwrite("final_composite.jpg", cv2.cvtColor(composite, cv2.COLOR_RGB2BGR))