| """
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| Simple example script to test Moondream2 model.
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| Based on the README usage example.
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| """
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|
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| from transformers import AutoModelForCausalLM, AutoTokenizer
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| from PIL import Image
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| import torch
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| import os
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|
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| def main():
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| print("Loading Moondream2 model...")
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| print(f"CUDA available: {torch.cuda.is_available()}")
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|
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| model_id = "vikhyatk/moondream2"
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| print(f"Loading model from HuggingFace: {model_id}...")
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|
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| device = "cuda" if torch.cuda.is_available() else "cpu"
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| print(f"Using device: {device}")
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|
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| model = AutoModelForCausalLM.from_pretrained(
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| model_id,
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| trust_remote_code=True,
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| device_map=device if device == "cuda" else None
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| )
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| if device == "cpu":
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| model = model.to(device)
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|
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| tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
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|
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| print("Model loaded successfully!")
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|
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|
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| import sys
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| if len(sys.argv) > 1:
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| image_path = sys.argv[1]
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| image = Image.open(image_path).convert("RGB")
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| print(f"Loaded image from: {image_path}")
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| else:
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| print("\nNo image provided. Creating a simple test image...")
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|
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| from PIL import ImageDraw
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| img = Image.new('RGB', (400, 300), color='white')
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| draw = ImageDraw.Draw(img)
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| draw.rectangle([50, 50, 350, 250], fill='lightblue', outline='black', width=3)
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| draw.text((150, 140), "Test Image", fill='black')
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| image = img
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| print("Created test image with a blue rectangle and text.")
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|
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| print("\n" + "="*50)
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| print("Testing Captioning (Short)")
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| print("="*50)
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| try:
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| result = model.caption(image, length="short")
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| print(f"Short caption: {result['caption']}")
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| except Exception as e:
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| print(f"Error during captioning: {e}")
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|
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| print("\n" + "="*50)
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| print("Testing Visual Query")
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| print("="*50)
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| try:
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| question = "What is in this image?"
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| result = model.query(image, question)
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| print(f"Question: {question}")
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| print(f"Answer: {result['answer']}")
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| except Exception as e:
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| print(f"Error during query: {e}")
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|
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| print("\n" + "="*50)
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| print("Testing complete!")
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| print("="*50)
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|
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| if __name__ == "__main__":
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| main()
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|