130 lines
4.0 KiB
Python
130 lines
4.0 KiB
Python
"""
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Example usage script for ComfyUI Universal Image Loader
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This script demonstrates how to use the ImageLoader node programmatically.
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"""
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import base64
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import io
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from PIL import Image
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import torch
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# Import the node
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from imgloader_node import ImageLoader
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def create_test_image():
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"""Create a simple test image for demonstration."""
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# Create a simple gradient image
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img = Image.new('RGB', (200, 200))
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pixels = img.load()
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for i in range(200):
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for j in range(200):
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pixels[j, i] = (i, j, (i + j) % 255)
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return img
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def image_to_base64(img):
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"""Convert PIL image to base64 string."""
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buffer = io.BytesIO()
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img.save(buffer, format='PNG')
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return base64.b64encode(buffer.getvalue()).decode('utf-8')
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def main():
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"""Demonstrate the ImageLoader node functionality."""
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print("ComfyUI Universal Image Loader - Example Usage")
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print("=" * 50)
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# Create an instance of the node
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loader = ImageLoader()
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# Create a test image
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test_img = create_test_image()
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test_base64 = image_to_base64(test_img)
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test_data_url = f"data:image/png;base64,{test_base64}"
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print("1. Testing Base64 Input")
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print("-" * 20)
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# Test with base64 string
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image_tensor, mask_tensor = loader.load_image(base64=test_base64)
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print(f"Image tensor shape: {image_tensor.shape}")
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print(f"Mask tensor shape: {mask_tensor.shape}")
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print(f"Image value range: {image_tensor.min():.3f} - {image_tensor.max():.3f}")
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print()
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print("2. Testing Data URL Input")
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print("-" * 20)
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# Test with data URL
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image_tensor, mask_tensor = loader.load_image(base64=test_data_url)
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print(f"Image tensor shape: {image_tensor.shape}")
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print(f"Mask tensor shape: {mask_tensor.shape}")
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print()
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print("3. Testing Input Precedence")
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print("-" * 20)
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# Test precedence: filepath should take priority over base64
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image_tensor, mask_tensor = loader.load_image(
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filepath="nonexistent.png",
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base64=test_data_url
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)
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print(f"With multiple inputs, filepath was attempted first (even if it fails):")
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print(f"Image tensor shape: {image_tensor.shape}")
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print(f"Is fallback: {image_tensor.shape == (1, 1, 1, 3)}")
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# Test with valid base64 only
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image_tensor, mask_tensor = loader.load_image(base64=test_data_url)
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print(f"With base64 only:")
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print(f"Image tensor shape: {image_tensor.shape}")
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print(f"Success: {image_tensor.shape != (1, 1, 1, 3)}")
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print()
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print("4. Testing Empty Input Handling")
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print("-" * 20)
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# Test with no inputs
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image_tensor, mask_tensor = loader.load_image()
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print(f"Empty input result:")
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print(f"Image tensor shape: {image_tensor.shape}")
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print(f"Mask tensor shape: {mask_tensor.shape}")
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print(f"Is fallback: {image_tensor.shape == (1, 1, 1, 3)}")
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print()
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print("5. Testing Alpha Channel Handling")
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print("-" * 20)
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# Create RGBA image with alpha channel
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rgba_img = Image.new('RGBA', (100, 100), (255, 0, 0, 128))
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rgba_base64 = image_to_base64(rgba_img)
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image_tensor, mask_tensor = loader.load_image(base64=rgba_base64)
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print(f"RGBA image processing:")
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print(f"Image tensor shape: {image_tensor.shape}")
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print(f"Mask tensor shape: {mask_tensor.shape}")
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print(f"Alpha values (should be ~0.5): {mask_tensor.mean():.3f}")
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print()
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print("6. Node Configuration Info")
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print("-" * 20)
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# Display node configuration
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input_types = ImageLoader.INPUT_TYPES()
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print(f"Node category: {ImageLoader.CATEGORY}")
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print(f"Return types: {ImageLoader.RETURN_TYPES}")
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print(f"Return names: {ImageLoader.RETURN_NAMES}")
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print(f"Function name: {ImageLoader.FUNCTION}")
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print(f"Optional inputs: {list(input_types['optional'].keys())}")
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print()
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print("Example completed successfully!")
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print("The ImageLoader node is ready for use in ComfyUI workflows.")
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if __name__ == "__main__":
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main()
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