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example_usage.py

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+#!/usr/bin/env python3
+"""
+Mobile VLA 사용 예제
+"""
+
+import torch
+from transformers import AutoTokenizer, AutoProcessor
+from PIL import Image
+import numpy as np
+
+def load_mobile_vla_model(model_name="minuum/mobile-vla"):
+    """Mobile VLA 모델 로드"""
+    
+    # 여기서 실제 모델 로딩 로직 구현
+    print(f"Loading Mobile VLA model: {model_name}")
+    
+    # 실제 구현에서는 MobileVLATrainer를 사용
+    # from robovlms.train.mobile_vla_trainer import MobileVLATrainer
+    # model = MobileVLATrainer.from_pretrained(model_name)
+    
+    return None  # 플레이스홀더
+
+def predict_action(model, image_path, task_description):
+    """액션 예측"""
+    
+    # 이미지 로드
+    image = Image.open(image_path).convert("RGB")
+    
+    # 전처리 (실제 구현에서는 mobile_vla_collate_fn 사용)
+    # processed = preprocess_image(image)
+    
+    # 예측 (플레이스홀더)
+    dummy_action = [0.5, 0.2, 0.1]  # [linear_x, linear_y, angular_z]
+    
+    return dummy_action
+
+def main():
+    """메인 실행 함수"""
+    
+    print("🚀 Mobile VLA 예제 실행")
+    
+    # 모델 로드
+    model = load_mobile_vla_model()
+    
+    # 예제 예측
+    task = "Navigate around obstacles to track the target cup"
+    action = predict_action(model, "example_image.jpg", task)
+    
+    print(f"Task: {task}")
+    print(f"Predicted Action: {action}")
+    print(f"  - Linear X (forward/backward): {action[0]:.3f}")
+    print(f"  - Linear Y (left/right): {action[1]:.3f}")
+    print(f"  - Angular Z (rotation): {action[2]:.3f}")
+
+if __name__ == "__main__":
+    main()